From fb6a7e04f56b1f1ac089f68d196d84600e400ea3 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Wed, 7 Dec 2022 22:15:35 +0530
Subject: [PATCH 01/74] Work-in-progress refactor of the backend, to move most
 of the logic to diffusion-kit and keeping this as a UI around that engine.
 Does not work yet.

---
 ui/sd_internal/__init__.py       |   1 -
 ui/sd_internal/app.py            | 156 ++++++++++++
 ui/sd_internal/device_manager.py |  23 +-
 ui/sd_internal/model_manager.py  | 141 +++++++++++
 ui/sd_internal/runtime2.py       |  95 ++++++++
 ui/sd_internal/task_manager.py   |  89 ++-----
 ui/server.py                     | 396 +++++--------------------------
 7 files changed, 484 insertions(+), 417 deletions(-)
 create mode 100644 ui/sd_internal/app.py
 create mode 100644 ui/sd_internal/model_manager.py
 create mode 100644 ui/sd_internal/runtime2.py

diff --git a/ui/sd_internal/__init__.py b/ui/sd_internal/__init__.py
index a2abe294..9f71f249 100644
--- a/ui/sd_internal/__init__.py
+++ b/ui/sd_internal/__init__.py
@@ -40,7 +40,6 @@ class Request:
             "num_outputs": self.num_outputs,
             "num_inference_steps": self.num_inference_steps,
             "guidance_scale": self.guidance_scale,
-            "hypernetwork_strengtgh": self.guidance_scale,
             "width": self.width,
             "height": self.height,
             "seed": self.seed,
diff --git a/ui/sd_internal/app.py b/ui/sd_internal/app.py
new file mode 100644
index 00000000..09242319
--- /dev/null
+++ b/ui/sd_internal/app.py
@@ -0,0 +1,156 @@
+import os
+import socket
+import sys
+import json
+import traceback
+
+from sd_internal import task_manager
+
+SD_DIR = os.getcwd()
+
+SD_UI_DIR = os.getenv('SD_UI_PATH', None)
+sys.path.append(os.path.dirname(SD_UI_DIR))
+
+CONFIG_DIR = os.path.abspath(os.path.join(SD_UI_DIR, '..', 'scripts'))
+MODELS_DIR = os.path.abspath(os.path.join(SD_DIR, '..', 'models'))
+
+USER_UI_PLUGINS_DIR = os.path.abspath(os.path.join(SD_DIR, '..', 'plugins', 'ui'))
+CORE_UI_PLUGINS_DIR = os.path.abspath(os.path.join(SD_UI_DIR, 'plugins', 'ui'))
+UI_PLUGINS_SOURCES = ((CORE_UI_PLUGINS_DIR, 'core'), (USER_UI_PLUGINS_DIR, 'user'))
+
+STABLE_DIFFUSION_MODEL_EXTENSIONS = ['.ckpt', '.safetensors']
+VAE_MODEL_EXTENSIONS = ['.vae.pt', '.ckpt']
+HYPERNETWORK_MODEL_EXTENSIONS = ['.pt']
+
+OUTPUT_DIRNAME = "Stable Diffusion UI" # in the user's home folder
+TASK_TTL = 15 * 60 # Discard last session's task timeout
+APP_CONFIG_DEFAULTS = {
+    # auto: selects the cuda device with the most free memory, cuda: use the currently active cuda device.
+    'render_devices': 'auto', # valid entries: 'auto', 'cpu' or 'cuda:N' (where N is a GPU index)
+    'update_branch': 'main',
+    'ui': {
+        'open_browser_on_start': True,
+    },
+}
+DEFAULT_MODELS = [
+    # needed to support the legacy installations
+    'custom-model', # Check if user has a custom model, use it first.
+    'sd-v1-4', # Default fallback.
+]
+
+def init():
+    os.makedirs(USER_UI_PLUGINS_DIR, exist_ok=True)
+
+    update_render_threads()
+
+def getConfig(default_val=APP_CONFIG_DEFAULTS):
+    try:
+        config_json_path = os.path.join(CONFIG_DIR, 'config.json')
+        if not os.path.exists(config_json_path):
+            return default_val
+        with open(config_json_path, 'r', encoding='utf-8') as f:
+            config = json.load(f)
+            if 'net' not in config:
+                config['net'] = {}
+            if os.getenv('SD_UI_BIND_PORT') is not None:
+                config['net']['listen_port'] = int(os.getenv('SD_UI_BIND_PORT'))
+            if os.getenv('SD_UI_BIND_IP') is not None:
+                config['net']['listen_to_network'] = (os.getenv('SD_UI_BIND_IP') == '0.0.0.0')
+            return config
+    except Exception as e:
+        print(str(e))
+        print(traceback.format_exc())
+        return default_val
+
+def setConfig(config):
+    try: # config.json
+        config_json_path = os.path.join(CONFIG_DIR, 'config.json')
+        with open(config_json_path, 'w', encoding='utf-8') as f:
+            json.dump(config, f)
+    except:
+        print(traceback.format_exc())
+
+    try: # config.bat
+        config_bat_path = os.path.join(CONFIG_DIR, 'config.bat')
+        config_bat = []
+
+        if 'update_branch' in config:
+            config_bat.append(f"@set update_branch={config['update_branch']}")
+
+        config_bat.append(f"@set SD_UI_BIND_PORT={config['net']['listen_port']}")
+        bind_ip = '0.0.0.0' if config['net']['listen_to_network'] else '127.0.0.1'
+        config_bat.append(f"@set SD_UI_BIND_IP={bind_ip}")
+
+        config_bat.append(f"@set test_sd2={'Y' if config.get('test_sd2', False) else 'N'}")
+
+        if len(config_bat) > 0:
+            with open(config_bat_path, 'w', encoding='utf-8') as f:
+                f.write('\r\n'.join(config_bat))
+    except:
+        print(traceback.format_exc())
+
+    try: # config.sh
+        config_sh_path = os.path.join(CONFIG_DIR, 'config.sh')
+        config_sh = ['#!/bin/bash']
+
+        if 'update_branch' in config:
+            config_sh.append(f"export update_branch={config['update_branch']}")
+
+        config_sh.append(f"export SD_UI_BIND_PORT={config['net']['listen_port']}")
+        bind_ip = '0.0.0.0' if config['net']['listen_to_network'] else '127.0.0.1'
+        config_sh.append(f"export SD_UI_BIND_IP={bind_ip}")
+
+        config_sh.append(f"export test_sd2=\"{'Y' if config.get('test_sd2', False) else 'N'}\"")
+
+        if len(config_sh) > 1:
+            with open(config_sh_path, 'w', encoding='utf-8') as f:
+                f.write('\n'.join(config_sh))
+    except:
+        print(traceback.format_exc())
+
+def save_model_to_config(ckpt_model_name, vae_model_name, hypernetwork_model_name):
+    config = getConfig()
+    if 'model' not in config:
+        config['model'] = {}
+
+    config['model']['stable-diffusion'] = ckpt_model_name
+    config['model']['vae'] = vae_model_name
+    config['model']['hypernetwork'] = hypernetwork_model_name
+
+    if vae_model_name is None or vae_model_name == "":
+        del config['model']['vae']
+    if hypernetwork_model_name is None or hypernetwork_model_name == "":
+        del config['model']['hypernetwork']
+
+    setConfig(config)
+
+def update_render_threads():
+    config = getConfig()
+    render_devices = config.get('render_devices', 'auto')
+    active_devices = task_manager.get_devices()['active'].keys()
+
+    print('requesting for render_devices', render_devices)
+    task_manager.update_render_threads(render_devices, active_devices)
+
+def getUIPlugins():
+    plugins = []
+
+    for plugins_dir, dir_prefix in UI_PLUGINS_SOURCES:
+        for file in os.listdir(plugins_dir):
+            if file.endswith('.plugin.js'):
+                plugins.append(f'/plugins/{dir_prefix}/{file}')
+
+    return plugins
+
+def getIPConfig():
+    ips = socket.gethostbyname_ex(socket.gethostname())
+    ips[2].append(ips[0])
+    return ips[2]
+
+def open_browser():
+    config = getConfig()
+    ui = config.get('ui', {})
+    net = config.get('net', {'listen_port':9000})
+    port = net.get('listen_port', 9000)
+    if ui.get('open_browser_on_start', True):
+        import webbrowser; webbrowser.open(f"http://localhost:{port}")
diff --git a/ui/sd_internal/device_manager.py b/ui/sd_internal/device_manager.py
index d2c6430b..3c1d8bf1 100644
--- a/ui/sd_internal/device_manager.py
+++ b/ui/sd_internal/device_manager.py
@@ -82,7 +82,7 @@ def auto_pick_devices(currently_active_devices):
     devices = list(map(lambda x: x['device'], devices))
     return devices
 
-def device_init(thread_data, device):
+def device_init(context, device):
     '''
     This function assumes the 'device' has already been verified to be compatible.
     `get_device_delta()` has already filtered out incompatible devices.
@@ -91,21 +91,22 @@ def device_init(thread_data, device):
     validate_device_id(device, log_prefix='device_init')
 
     if device == 'cpu':
-        thread_data.device = 'cpu'
-        thread_data.device_name = get_processor_name()
-        print('Render device CPU available as', thread_data.device_name)
+        context.device = 'cpu'
+        context.device_name = get_processor_name()
+        context.precision = 'full'
+        print('Render device CPU available as', context.device_name)
         return
 
-    thread_data.device_name = torch.cuda.get_device_name(device)
-    thread_data.device = device
+    context.device_name = torch.cuda.get_device_name(device)
+    context.device = device
 
     # Force full precision on 1660 and 1650 NVIDIA cards to avoid creating green images
-    device_name = thread_data.device_name.lower()
-    thread_data.force_full_precision = (('nvidia' in device_name or 'geforce' in device_name) and (' 1660' in device_name or ' 1650' in device_name)) or ('Quadro T2000' in device_name)
-    if thread_data.force_full_precision:
-        print('forcing full precision on NVIDIA 16xx cards, to avoid green images. GPU detected: ', thread_data.device_name)
+    device_name = context.device_name.lower()
+    force_full_precision = (('nvidia' in device_name or 'geforce' in device_name) and (' 1660' in device_name or ' 1650' in device_name)) or ('Quadro T2000' in device_name)
+    if force_full_precision:
+        print('forcing full precision on NVIDIA 16xx cards, to avoid green images. GPU detected: ', context.device_name)
         # Apply force_full_precision now before models are loaded.
-        thread_data.precision = 'full'
+        context.precision = 'full'
 
     print(f'Setting {device} as active')
     torch.cuda.device(device)
diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
new file mode 100644
index 00000000..3941b130
--- /dev/null
+++ b/ui/sd_internal/model_manager.py
@@ -0,0 +1,141 @@
+import os
+
+from sd_internal import app
+import picklescan.scanner
+import rich
+
+default_model_to_load = None
+default_vae_to_load = None
+default_hypernetwork_to_load = None
+
+known_models = {}
+
+def init():
+    global default_model_to_load, default_vae_to_load, default_hypernetwork_to_load
+
+    default_model_to_load = resolve_ckpt_to_use()
+    default_vae_to_load = resolve_vae_to_use()
+    default_hypernetwork_to_load = resolve_hypernetwork_to_use()
+
+    getModels() # run this once, to cache the picklescan results
+
+def resolve_model_to_use(model_name:str, model_type:str, model_dir:str, model_extensions:list, default_models=[]):
+    config = app.getConfig()
+
+    model_dirs = [os.path.join(app.MODELS_DIR, model_dir), app.SD_DIR]
+    if not model_name: # When None try user configured model.
+        # config = getConfig()
+        if 'model' in config and model_type in config['model']:
+            model_name = config['model'][model_type]
+
+    if model_name:
+        is_sd2 = config.get('test_sd2', False)
+        if model_name.startswith('sd2_') and not is_sd2: # temp hack, until SD2 is unified with 1.4
+            print('ERROR: Cannot use SD 2.0 models with SD 1.0 code. Using the sd-v1-4 model instead!')
+            model_name = 'sd-v1-4'
+
+        # Check models directory
+        models_dir_path = os.path.join(app.MODELS_DIR, model_dir, model_name)
+        for model_extension in model_extensions:
+            if os.path.exists(models_dir_path + model_extension):
+                return models_dir_path + model_extension
+            if os.path.exists(model_name + model_extension):
+                return os.path.abspath(model_name + model_extension)
+
+    # Default locations
+    if model_name in default_models:
+        default_model_path = os.path.join(app.SD_DIR, model_name)
+        for model_extension in model_extensions:
+            if os.path.exists(default_model_path + model_extension):
+                return default_model_path + model_extension
+
+    # Can't find requested model, check the default paths.
+    for default_model in default_models:
+        for model_dir in model_dirs:
+            default_model_path = os.path.join(model_dir, default_model)
+            for model_extension in model_extensions:
+                if os.path.exists(default_model_path + model_extension):
+                    if model_name is not None:
+                        print(f'Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}')
+                    return default_model_path + model_extension
+
+    raise Exception('No valid models found.')
+
+def resolve_ckpt_to_use(model_name:str=None):
+    return resolve_model_to_use(model_name, model_type='stable-diffusion', model_dir='stable-diffusion', model_extensions=app.STABLE_DIFFUSION_MODEL_EXTENSIONS, default_models=app.APP_CONFIG_DEFAULT_MODELS)
+
+def resolve_vae_to_use(model_name:str=None):
+    try:
+        return resolve_model_to_use(model_name, model_type='vae', model_dir='vae', model_extensions=app.VAE_MODEL_EXTENSIONS, default_models=[])
+    except:
+        return None
+
+def resolve_hypernetwork_to_use(model_name:str=None):
+    try:
+        return resolve_model_to_use(model_name, model_type='hypernetwork', model_dir='hypernetwork', model_extensions=app.HYPERNETWORK_MODEL_EXTENSIONS, default_models=[])
+    except:
+        return None
+
+def is_malicious_model(file_path):
+    try:
+        scan_result = picklescan.scanner.scan_file_path(file_path)
+        if scan_result.issues_count > 0 or scan_result.infected_files > 0:
+            rich.print(":warning: [bold red]Scan %s: %d scanned, %d issue, %d infected.[/bold red]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files))
+            return True
+        else:
+            rich.print("Scan %s: [green]%d scanned, %d issue, %d infected.[/green]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files))
+            return False
+    except Exception as e:
+        print('error while scanning', file_path, 'error:', e)
+    return False
+
+def getModels():
+    models = {
+        'active': {
+            'stable-diffusion': 'sd-v1-4',
+            'vae': '',
+            'hypernetwork': '',
+        },
+        'options': {
+            'stable-diffusion': ['sd-v1-4'],
+            'vae': [],
+            'hypernetwork': [],
+        },
+    }
+
+    def listModels(models_dirname, model_type, model_extensions):
+        models_dir = os.path.join(app.MODELS_DIR, models_dirname)
+        if not os.path.exists(models_dir):
+            os.makedirs(models_dir)
+
+        for file in os.listdir(models_dir):
+            for model_extension in model_extensions:
+                if not file.endswith(model_extension):
+                    continue
+
+                model_path = os.path.join(models_dir, file)
+                mtime = os.path.getmtime(model_path)
+                mod_time = known_models[model_path] if model_path in known_models else -1
+                if mod_time != mtime:
+                    if is_malicious_model(model_path):
+                        models['scan-error'] = file
+                        return
+                known_models[model_path] = mtime
+
+                model_name = file[:-len(model_extension)]
+                models['options'][model_type].append(model_name)
+
+        models['options'][model_type] = [*set(models['options'][model_type])] # remove duplicates
+        models['options'][model_type].sort()
+
+    # custom models
+    listModels(models_dirname='stable-diffusion', model_type='stable-diffusion', model_extensions=app.STABLE_DIFFUSION_MODEL_EXTENSIONS)
+    listModels(models_dirname='vae', model_type='vae', model_extensions=app.VAE_MODEL_EXTENSIONS)
+    listModels(models_dirname='hypernetwork', model_type='hypernetwork', model_extensions=app.HYPERNETWORK_MODEL_EXTENSIONS)
+
+    # legacy
+    custom_weight_path = os.path.join(app.SD_DIR, 'custom-model.ckpt')
+    if os.path.exists(custom_weight_path):
+        models['options']['stable-diffusion'].append('custom-model')
+
+    return models
diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
new file mode 100644
index 00000000..32befcde
--- /dev/null
+++ b/ui/sd_internal/runtime2.py
@@ -0,0 +1,95 @@
+import threading
+import queue
+
+from sd_internal import device_manager, Request, Response, Image as ResponseImage
+
+from modules import model_loader, image_generator, image_utils
+
+thread_data = threading.local()
+'''
+runtime data (bound locally to this thread), for e.g. device, references to loaded models, optimization flags etc
+'''
+
+def init(device):
+    '''
+    Initializes the fields that will be bound to this runtime's thread_data, and sets the current torch device
+    '''
+    thread_data.stop_processing = False
+    thread_data.temp_images = {}
+
+    thread_data.models = {}
+    thread_data.loaded_model_paths = {}
+
+    thread_data.device = None
+    thread_data.device_name = None
+    thread_data.precision = 'autocast'
+    thread_data.vram_optimizations = ('TURBO', 'MOVE_MODELS')
+
+    device_manager.device_init(thread_data, device)
+
+    reload_models()
+
+def destroy():
+    model_loader.unload_sd_model(thread_data)
+    model_loader.unload_gfpgan_model(thread_data)
+    model_loader.unload_realesrgan_model(thread_data)
+
+def reload_models(req: Request=None):
+    if is_hypernetwork_reload_necessary(task.request):
+        current_state = ServerStates.LoadingModel
+        runtime.reload_hypernetwork()
+
+    if is_model_reload_necessary(task.request):
+        current_state = ServerStates.LoadingModel
+        runtime.reload_model()
+
+def load_models():
+    if ckpt_file_path == None:
+        ckpt_file_path = default_model_to_load
+    if vae_file_path == None:
+        vae_file_path = default_vae_to_load
+    if hypernetwork_file_path == None:
+        hypernetwork_file_path = default_hypernetwork_to_load
+    if ckpt_file_path == current_model_path and vae_file_path == current_vae_path:
+        return
+    current_state = ServerStates.LoadingModel
+    try:
+        from sd_internal import runtime2
+        runtime.thread_data.hypernetwork_file = hypernetwork_file_path
+        runtime.thread_data.ckpt_file = ckpt_file_path
+        runtime.thread_data.vae_file = vae_file_path
+        runtime.load_model_ckpt()
+        runtime.load_hypernetwork()
+        current_model_path = ckpt_file_path
+        current_vae_path = vae_file_path
+        current_hypernetwork_path = hypernetwork_file_path
+        current_state_error = None
+        current_state = ServerStates.Online
+    except Exception as e:
+        current_model_path = None
+        current_vae_path = None
+        current_state_error = e
+        current_state = ServerStates.Unavailable
+        print(traceback.format_exc())
+
+def make_image(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
+    try:
+        images = image_generator.make_image(context=thread_data, args=get_mk_img_args(req))
+    except UserInitiatedStop:
+        pass
+
+def get_mk_img_args(req: Request):
+    args = req.json()
+
+    if req.init_image is not None:
+        args['init_image'] = image_utils.base64_str_to_img(req.init_image)
+
+    if req.mask is not None:
+        args['mask'] = image_utils.base64_str_to_img(req.mask)
+
+    return args
+
+def on_image_step(x_samples, i):
+    pass
+
+image_generator.on_image_step = on_image_step
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 41fc00f6..4c2b5c6c 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -177,50 +177,14 @@ manager_lock = threading.RLock()
 render_threads = []
 current_state = ServerStates.Init
 current_state_error:Exception = None
-current_model_path = None
-current_vae_path = None
-current_hypernetwork_path = None
 tasks_queue = []
 task_cache = TaskCache()
-default_model_to_load = None
-default_vae_to_load = None
-default_hypernetwork_to_load = None
 weak_thread_data = weakref.WeakKeyDictionary()
 
-def preload_model(ckpt_file_path=None, vae_file_path=None, hypernetwork_file_path=None):
-    global current_state, current_state_error, current_model_path, current_vae_path, current_hypernetwork_path
-    if ckpt_file_path == None:
-        ckpt_file_path = default_model_to_load
-    if vae_file_path == None:
-        vae_file_path = default_vae_to_load
-    if hypernetwork_file_path == None:
-        hypernetwork_file_path = default_hypernetwork_to_load
-    if ckpt_file_path == current_model_path and vae_file_path == current_vae_path:
-        return
-    current_state = ServerStates.LoadingModel
-    try:
-        from . import runtime
-        runtime.thread_data.hypernetwork_file = hypernetwork_file_path
-        runtime.thread_data.ckpt_file = ckpt_file_path
-        runtime.thread_data.vae_file = vae_file_path
-        runtime.load_model_ckpt()
-        runtime.load_hypernetwork()
-        current_model_path = ckpt_file_path
-        current_vae_path = vae_file_path
-        current_hypernetwork_path = hypernetwork_file_path
-        current_state_error = None
-        current_state = ServerStates.Online
-    except Exception as e:
-        current_model_path = None
-        current_vae_path = None
-        current_state_error = e
-        current_state = ServerStates.Unavailable
-        print(traceback.format_exc())
-
 def thread_get_next_task():
-    from . import runtime
+    from sd_internal import runtime2
     if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
-        print('Render thread on device', runtime.thread_data.device, 'failed to acquire manager lock.')
+        print('Render thread on device', runtime2.thread_data.device, 'failed to acquire manager lock.')
         return None
     if len(tasks_queue) <= 0:
         manager_lock.release()
@@ -228,7 +192,7 @@ def thread_get_next_task():
     task = None
     try:  # Select a render task.
         for queued_task in tasks_queue:
-            if queued_task.render_device and runtime.thread_data.device != queued_task.render_device:
+            if queued_task.render_device and runtime2.thread_data.device != queued_task.render_device:
                 # Is asking for a specific render device.
                 if is_alive(queued_task.render_device) > 0:
                     continue  # requested device alive, skip current one.
@@ -237,7 +201,7 @@ def thread_get_next_task():
                     queued_task.error = Exception(queued_task.render_device + ' is not currently active.')
                     task = queued_task
                     break
-            if not queued_task.render_device and runtime.thread_data.device == 'cpu' and is_alive() > 1:
+            if not queued_task.render_device and runtime2.thread_data.device == 'cpu' and is_alive() > 1:
                 # not asking for any specific devices, cpu want to grab task but other render devices are alive.
                 continue  # Skip Tasks, don't run on CPU unless there is nothing else or user asked for it.
             task = queued_task
@@ -249,30 +213,31 @@ def thread_get_next_task():
         manager_lock.release()
 
 def thread_render(device):
-    global current_state, current_state_error, current_model_path, current_vae_path, current_hypernetwork_path
-    from . import runtime
+    global current_state, current_state_error
+
+    from sd_internal import runtime2
     try:
-        runtime.thread_init(device)
+        runtime2.init(device)
     except Exception as e:
         print(traceback.format_exc())
         weak_thread_data[threading.current_thread()] = {
             'error': e
         }
         return
+
     weak_thread_data[threading.current_thread()] = {
-        'device': runtime.thread_data.device,
-        'device_name': runtime.thread_data.device_name,
+        'device': runtime2.thread_data.device,
+        'device_name': runtime2.thread_data.device_name,
         'alive': True
     }
-    if runtime.thread_data.device != 'cpu' or is_alive() == 1:
-        preload_model()
-        current_state = ServerStates.Online
+
+    current_state = ServerStates.Online
+
     while True:
         task_cache.clean()
         if not weak_thread_data[threading.current_thread()]['alive']:
-            print(f'Shutting down thread for device {runtime.thread_data.device}')
-            runtime.unload_models()
-            runtime.unload_filters()
+            print(f'Shutting down thread for device {runtime2.thread_data.device}')
+            runtime2.destroy()
             return
         if isinstance(current_state_error, SystemExit):
             current_state = ServerStates.Unavailable
@@ -291,24 +256,17 @@ def thread_render(device):
             task.response = {"status": 'failed', "detail": str(task.error)}
             task.buffer_queue.put(json.dumps(task.response))
             continue
-        print(f'Session {task.request.session_id} starting task {id(task)} on {runtime.thread_data.device_name}')
+        print(f'Session {task.request.session_id} starting task {id(task)} on {runtime2.thread_data.device_name}')
         if not task.lock.acquire(blocking=False): raise Exception('Got locked task from queue.')
         try:
-            if runtime.is_hypernetwork_reload_necessary(task.request):
-                runtime.reload_hypernetwork()
-                current_hypernetwork_path = task.request.use_hypernetwork_model
-                
-            if runtime.is_model_reload_necessary(task.request):
-                current_state = ServerStates.LoadingModel
-                runtime.reload_model()
-                current_model_path = task.request.use_stable_diffusion_model
-                current_vae_path = task.request.use_vae_model
+            current_state = ServerStates.LoadingModel
+            runtime2.reload_models(task.request)
 
             def step_callback():
                 global current_state_error
 
                 if isinstance(current_state_error, SystemExit) or isinstance(current_state_error, StopAsyncIteration) or isinstance(task.error, StopAsyncIteration):
-                    runtime.thread_data.stop_processing = True
+                    runtime2.thread_data.stop_processing = True
                     if isinstance(current_state_error, StopAsyncIteration):
                         task.error = current_state_error
                         current_state_error = None
@@ -317,7 +275,7 @@ def thread_render(device):
                     task_cache.keep(task.request.session_id, TASK_TTL)
 
             current_state = ServerStates.Rendering
-            task.response = runtime.mk_img(task.request, task.buffer_queue, task.temp_images, step_callback)
+            task.response = runtime2.make_image(task.request, task.buffer_queue, task.temp_images, step_callback)
         except Exception as e:
             task.error = e
             print(traceback.format_exc())
@@ -331,7 +289,7 @@ def thread_render(device):
         elif task.error is not None:
             print(f'Session {task.request.session_id} task {id(task)} failed!')
         else:
-            print(f'Session {task.request.session_id} task {id(task)} completed by {runtime.thread_data.device_name}.')
+            print(f'Session {task.request.session_id} task {id(task)} completed by {runtime2.thread_data.device_name}.')
         current_state = ServerStates.Online
 
 def get_cached_task(session_id:str, update_ttl:bool=False):
@@ -493,8 +451,7 @@ def render(req : ImageRequest):
     if task and not task.response and not task.error and not task.lock.locked():
         # Unstarted task pending, deny queueing more than one.
         raise ConnectionRefusedError(f'Session {req.session_id} has an already pending task.')
-    #
-    from . import runtime
+
     r = Request()
     r.session_id = req.session_id
     r.prompt = req.prompt
diff --git a/ui/server.py b/ui/server.py
index 804994a2..7922d8f3 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -2,64 +2,21 @@
 Notes:
     async endpoints always run on the main thread. Without they run on the thread pool.
 """
-import json
-import traceback
-
-import sys
 import os
-import socket
-import picklescan.scanner
-import rich
-
-SD_DIR = os.getcwd()
-print('started in ', SD_DIR)
-
-SD_UI_DIR = os.getenv('SD_UI_PATH', None)
-sys.path.append(os.path.dirname(SD_UI_DIR))
-
-CONFIG_DIR = os.path.abspath(os.path.join(SD_UI_DIR, '..', 'scripts'))
-MODELS_DIR = os.path.abspath(os.path.join(SD_DIR, '..', 'models'))
-
-USER_UI_PLUGINS_DIR = os.path.abspath(os.path.join(SD_DIR, '..', 'plugins', 'ui'))
-CORE_UI_PLUGINS_DIR = os.path.abspath(os.path.join(SD_UI_DIR, 'plugins', 'ui'))
-UI_PLUGINS_SOURCES = ((CORE_UI_PLUGINS_DIR, 'core'), (USER_UI_PLUGINS_DIR, 'user'))
-
-STABLE_DIFFUSION_MODEL_EXTENSIONS = ['.ckpt', '.safetensors']
-VAE_MODEL_EXTENSIONS = ['.vae.pt', '.ckpt']
-HYPERNETWORK_MODEL_EXTENSIONS = ['.pt']
-
-OUTPUT_DIRNAME = "Stable Diffusion UI" # in the user's home folder
-TASK_TTL = 15 * 60 # Discard last session's task timeout
-APP_CONFIG_DEFAULTS = {
-    # auto: selects the cuda device with the most free memory, cuda: use the currently active cuda device.
-    'render_devices': 'auto', # valid entries: 'auto', 'cpu' or 'cuda:N' (where N is a GPU index)
-    'update_branch': 'main',
-    'ui': {
-        'open_browser_on_start': True,
-    },
-}
-APP_CONFIG_DEFAULT_MODELS = [
-    # needed to support the legacy installations
-    'custom-model', # Check if user has a custom model, use it first.
-    'sd-v1-4', # Default fallback.
-]
+import traceback
+import logging
+from typing import List, Union
 
 from fastapi import FastAPI, HTTPException
 from fastapi.staticfiles import StaticFiles
 from starlette.responses import FileResponse, JSONResponse, StreamingResponse
 from pydantic import BaseModel
-import logging
-#import queue, threading, time
-from typing import Any, Generator, Hashable, List, Optional, Union
 
-from sd_internal import Request, Response, task_manager
+from sd_internal import app, model_manager, task_manager
 
-app = FastAPI()
+print('started in ', app.SD_DIR)
 
-modifiers_cache = None
-outpath = os.path.join(os.path.expanduser("~"), OUTPUT_DIRNAME)
-
-os.makedirs(USER_UI_PLUGINS_DIR, exist_ok=True)
+server_api = FastAPI()
 
 # don't show access log entries for URLs that start with the given prefix
 ACCESS_LOG_SUPPRESS_PATH_PREFIXES = ['/ping', '/image', '/modifier-thumbnails']
@@ -74,132 +31,6 @@ class NoCacheStaticFiles(StaticFiles):
 
         return super().is_not_modified(response_headers, request_headers)
 
-app.mount('/media', NoCacheStaticFiles(directory=os.path.join(SD_UI_DIR, 'media')), name="media")
-
-for plugins_dir, dir_prefix in UI_PLUGINS_SOURCES:
-    app.mount(f'/plugins/{dir_prefix}', NoCacheStaticFiles(directory=plugins_dir), name=f"plugins-{dir_prefix}")
-
-def getConfig(default_val=APP_CONFIG_DEFAULTS):
-    try:
-        config_json_path = os.path.join(CONFIG_DIR, 'config.json')
-        if not os.path.exists(config_json_path):
-            return default_val
-        with open(config_json_path, 'r', encoding='utf-8') as f:
-            config = json.load(f)
-            if 'net' not in config:
-                config['net'] = {}
-            if os.getenv('SD_UI_BIND_PORT') is not None:
-                config['net']['listen_port'] = int(os.getenv('SD_UI_BIND_PORT'))
-            if os.getenv('SD_UI_BIND_IP') is not None:
-                config['net']['listen_to_network'] = ( os.getenv('SD_UI_BIND_IP') == '0.0.0.0' )
-            return config
-    except Exception as e:
-        print(str(e))
-        print(traceback.format_exc())
-        return default_val
-
-def setConfig(config):
-    print( json.dumps(config) )
-    try: # config.json
-        config_json_path = os.path.join(CONFIG_DIR, 'config.json')
-        with open(config_json_path, 'w', encoding='utf-8') as f:
-            json.dump(config, f)
-    except:
-        print(traceback.format_exc())
-
-    try: # config.bat
-        config_bat_path = os.path.join(CONFIG_DIR, 'config.bat')
-        config_bat = []
-
-        if 'update_branch' in config:
-            config_bat.append(f"@set update_branch={config['update_branch']}")
-
-        config_bat.append(f"@set SD_UI_BIND_PORT={config['net']['listen_port']}")
-        bind_ip = '0.0.0.0' if config['net']['listen_to_network'] else '127.0.0.1'
-        config_bat.append(f"@set SD_UI_BIND_IP={bind_ip}")
-
-        config_bat.append(f"@set test_sd2={'Y' if config.get('test_sd2', False) else 'N'}")
-
-        if len(config_bat) > 0:
-            with open(config_bat_path, 'w', encoding='utf-8') as f:
-                f.write('\r\n'.join(config_bat))
-    except:
-        print(traceback.format_exc())
-
-    try: # config.sh
-        config_sh_path = os.path.join(CONFIG_DIR, 'config.sh')
-        config_sh = ['#!/bin/bash']
-
-        if 'update_branch' in config:
-            config_sh.append(f"export update_branch={config['update_branch']}")
-
-        config_sh.append(f"export SD_UI_BIND_PORT={config['net']['listen_port']}")
-        bind_ip = '0.0.0.0' if config['net']['listen_to_network'] else '127.0.0.1'
-        config_sh.append(f"export SD_UI_BIND_IP={bind_ip}")
-
-        config_sh.append(f"export test_sd2=\"{'Y' if config.get('test_sd2', False) else 'N'}\"")
-
-        if len(config_sh) > 1:
-            with open(config_sh_path, 'w', encoding='utf-8') as f:
-                f.write('\n'.join(config_sh))
-    except:
-        print(traceback.format_exc())
-
-def resolve_model_to_use(model_name:str, model_type:str, model_dir:str, model_extensions:list, default_models=[]):
-    config = getConfig()
-
-    model_dirs = [os.path.join(MODELS_DIR, model_dir), SD_DIR]
-    if not model_name: # When None try user configured model.
-        # config = getConfig()
-        if 'model' in config and model_type in config['model']:
-            model_name = config['model'][model_type]
-    if model_name:
-        is_sd2 = config.get('test_sd2', False)
-        if model_name.startswith('sd2_') and not is_sd2: # temp hack, until SD2 is unified with 1.4
-            print('ERROR: Cannot use SD 2.0 models with SD 1.0 code. Using the sd-v1-4 model instead!')
-            model_name = 'sd-v1-4'
-
-        # Check models directory
-        models_dir_path = os.path.join(MODELS_DIR, model_dir, model_name)
-        for model_extension in model_extensions:
-            if os.path.exists(models_dir_path + model_extension):
-                return models_dir_path
-            if os.path.exists(model_name + model_extension):
-                # Direct Path to file
-                model_name = os.path.abspath(model_name)
-                return model_name
-    # Default locations
-    if model_name in default_models:
-        default_model_path = os.path.join(SD_DIR, model_name)
-        for model_extension in model_extensions:
-            if os.path.exists(default_model_path + model_extension):
-                return default_model_path
-    # Can't find requested model, check the default paths.
-    for default_model in default_models:
-        for model_dir in model_dirs:
-            default_model_path = os.path.join(model_dir, default_model)
-            for model_extension in model_extensions:
-                if os.path.exists(default_model_path + model_extension):
-                    if model_name is not None:
-                        print(f'Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}')
-                    return default_model_path
-    raise Exception('No valid models found.')
-
-def resolve_ckpt_to_use(model_name:str=None):
-    return resolve_model_to_use(model_name, model_type='stable-diffusion', model_dir='stable-diffusion', model_extensions=STABLE_DIFFUSION_MODEL_EXTENSIONS, default_models=APP_CONFIG_DEFAULT_MODELS)
-
-def resolve_vae_to_use(model_name:str=None):
-    try:
-        return resolve_model_to_use(model_name, model_type='vae', model_dir='vae', model_extensions=VAE_MODEL_EXTENSIONS, default_models=[])
-    except:
-        return None
-
-def resolve_hypernetwork_to_use(model_name:str=None):
-    try:
-        return resolve_model_to_use(model_name, model_type='hypernetwork', model_dir='hypernetwork', model_extensions=HYPERNETWORK_MODEL_EXTENSIONS, default_models=[])
-    except:
-        return None
-
 class SetAppConfigRequest(BaseModel):
     update_branch: str = None
     render_devices: Union[List[str], List[int], str, int] = None
@@ -209,9 +40,25 @@ class SetAppConfigRequest(BaseModel):
     listen_port: int = None
     test_sd2: bool = None
 
-@app.post('/app_config')
+class LogSuppressFilter(logging.Filter):
+    def filter(self, record: logging.LogRecord) -> bool:
+        path = record.getMessage()
+        for prefix in ACCESS_LOG_SUPPRESS_PATH_PREFIXES:
+            if path.find(prefix) != -1:
+                return False
+        return True
+
+# don't log certain requests
+logging.getLogger('uvicorn.access').addFilter(LogSuppressFilter())
+
+server_api.mount('/media', NoCacheStaticFiles(directory=os.path.join(app.SD_UI_DIR, 'media')), name="media")
+
+for plugins_dir, dir_prefix in app.UI_PLUGINS_SOURCES:
+    app.mount(f'/plugins/{dir_prefix}', NoCacheStaticFiles(directory=plugins_dir), name=f"plugins-{dir_prefix}")
+
+@server_api.post('/app_config')
 async def setAppConfig(req : SetAppConfigRequest):
-    config = getConfig()
+    config = app.getConfig()
     if req.update_branch is not None:
         config['update_branch'] = req.update_branch
     if req.render_devices is not None:
@@ -231,121 +78,48 @@ async def setAppConfig(req : SetAppConfigRequest):
     if req.test_sd2 is not None:
         config['test_sd2'] = req.test_sd2
     try:
-        setConfig(config)
+        app.setConfig(config)
 
         if req.render_devices:
-            update_render_threads()
+            app.update_render_threads()
 
         return JSONResponse({'status': 'OK'}, headers=NOCACHE_HEADERS)
     except Exception as e:
         print(traceback.format_exc())
         raise HTTPException(status_code=500, detail=str(e))
 
-def is_malicious_model(file_path):
-    try:
-        scan_result = picklescan.scanner.scan_file_path(file_path)
-        if scan_result.issues_count > 0 or scan_result.infected_files > 0:
-            rich.print(":warning: [bold red]Scan %s: %d scanned, %d issue, %d infected.[/bold red]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files))
-            return True
-        else:
-            rich.print("Scan %s: [green]%d scanned, %d issue, %d infected.[/green]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files))
-            return False
-    except Exception as e:
-        print('error while scanning', file_path, 'error:', e)
-    return False
+def update_render_devices_in_config(config, render_devices):
+    if render_devices not in ('cpu', 'auto') and not render_devices.startswith('cuda:'):
+        raise HTTPException(status_code=400, detail=f'Invalid render device requested: {render_devices}')
 
-known_models = {}
-def getModels():
-    models = {
-        'active': {
-            'stable-diffusion': 'sd-v1-4',
-            'vae': '',
-            'hypernetwork': '',
-        },
-        'options': {
-            'stable-diffusion': ['sd-v1-4'],
-            'vae': [],
-            'hypernetwork': [],
-        },
-    }
+    if render_devices.startswith('cuda:'):
+        render_devices = render_devices.split(',')
 
-    def listModels(models_dirname, model_type, model_extensions):
-        models_dir = os.path.join(MODELS_DIR, models_dirname)
-        if not os.path.exists(models_dir):
-            os.makedirs(models_dir)
+    config['render_devices'] = render_devices
 
-        for file in os.listdir(models_dir):
-            for model_extension in model_extensions:
-                if not file.endswith(model_extension):
-                    continue
-
-                model_path = os.path.join(models_dir, file)
-                mtime = os.path.getmtime(model_path)
-                mod_time = known_models[model_path] if model_path in known_models else -1
-                if mod_time != mtime:
-                    if is_malicious_model(model_path):
-                        models['scan-error'] = file
-                        return
-                known_models[model_path] = mtime
-
-                model_name = file[:-len(model_extension)]
-                models['options'][model_type].append(model_name)
-
-        models['options'][model_type] = [*set(models['options'][model_type])] # remove duplicates
-        models['options'][model_type].sort()
-
-    # custom models
-    listModels(models_dirname='stable-diffusion', model_type='stable-diffusion', model_extensions=STABLE_DIFFUSION_MODEL_EXTENSIONS)
-    listModels(models_dirname='vae', model_type='vae', model_extensions=VAE_MODEL_EXTENSIONS)
-    listModels(models_dirname='hypernetwork', model_type='hypernetwork', model_extensions=HYPERNETWORK_MODEL_EXTENSIONS)
-    # legacy
-    custom_weight_path = os.path.join(SD_DIR, 'custom-model.ckpt')
-    if os.path.exists(custom_weight_path):
-        models['options']['stable-diffusion'].append('custom-model')
-
-    return models
-
-def getUIPlugins():
-    plugins = []
-
-    for plugins_dir, dir_prefix in UI_PLUGINS_SOURCES:
-        for file in os.listdir(plugins_dir):
-            if file.endswith('.plugin.js'):
-                plugins.append(f'/plugins/{dir_prefix}/{file}')
-
-    return plugins
-
-def getIPConfig():
-    ips = socket.gethostbyname_ex(socket.gethostname())
-    ips[2].append(ips[0])
-    return ips[2]
-
-@app.get('/get/{key:path}')
+@server_api.get('/get/{key:path}')
 def read_web_data(key:str=None):
     if not key: # /get without parameters, stable-diffusion easter egg.
         raise HTTPException(status_code=418, detail="StableDiffusion is drawing a teapot!") # HTTP418 I'm a teapot
     elif key == 'app_config':
-        config = getConfig(default_val=None)
-        if config is None:
-            config = APP_CONFIG_DEFAULTS
-        return JSONResponse(config, headers=NOCACHE_HEADERS)
+        return JSONResponse(app.getConfig(), headers=NOCACHE_HEADERS)
     elif key == 'system_info':
-        config = getConfig()
+        config = app.getConfig()
         system_info = {
             'devices': task_manager.get_devices(),
-            'hosts': getIPConfig(),
+            'hosts': app.getIPConfig(),
+            'default_output_dir': os.path.join(os.path.expanduser("~"), app.OUTPUT_DIRNAME),
         }
         system_info['devices']['config'] = config.get('render_devices', "auto")
         return JSONResponse(system_info, headers=NOCACHE_HEADERS)
     elif key == 'models':
-        return JSONResponse(getModels(), headers=NOCACHE_HEADERS)
-    elif key == 'modifiers': return FileResponse(os.path.join(SD_UI_DIR, 'modifiers.json'), headers=NOCACHE_HEADERS)
-    elif key == 'output_dir': return JSONResponse({ 'output_dir': outpath }, headers=NOCACHE_HEADERS)
-    elif key == 'ui_plugins': return JSONResponse(getUIPlugins(), headers=NOCACHE_HEADERS)
+        return JSONResponse(model_manager.getModels(), headers=NOCACHE_HEADERS)
+    elif key == 'modifiers': return FileResponse(os.path.join(app.SD_UI_DIR, 'modifiers.json'), headers=NOCACHE_HEADERS)
+    elif key == 'ui_plugins': return JSONResponse(app.getUIPlugins(), headers=NOCACHE_HEADERS)
     else:
         raise HTTPException(status_code=404, detail=f'Request for unknown {key}') # HTTP404 Not Found
 
-@app.get('/ping') # Get server and optionally session status.
+@server_api.get('/ping') # Get server and optionally session status.
 def ping(session_id:str=None):
     if task_manager.is_alive() <= 0: # Check that render threads are alive.
         if task_manager.current_state_error: raise HTTPException(status_code=500, detail=str(task_manager.current_state_error))
@@ -372,38 +146,14 @@ def ping(session_id:str=None):
     response['devices'] = task_manager.get_devices()
     return JSONResponse(response, headers=NOCACHE_HEADERS)
 
-def save_model_to_config(ckpt_model_name, vae_model_name, hypernetwork_model_name):
-    config = getConfig()
-    if 'model' not in config:
-        config['model'] = {}
-
-    config['model']['stable-diffusion'] = ckpt_model_name
-    config['model']['vae'] = vae_model_name
-    config['model']['hypernetwork'] = hypernetwork_model_name
-
-    if vae_model_name is None or vae_model_name == "":
-        del config['model']['vae']
-    if hypernetwork_model_name is None or hypernetwork_model_name == "":
-        del config['model']['hypernetwork']
-
-    setConfig(config)
-
-def update_render_devices_in_config(config, render_devices):
-    if render_devices not in ('cpu', 'auto') and not render_devices.startswith('cuda:'):
-        raise HTTPException(status_code=400, detail=f'Invalid render device requested: {render_devices}')
-
-    if render_devices.startswith('cuda:'):
-        render_devices = render_devices.split(',')
-
-    config['render_devices'] = render_devices
-
-@app.post('/render')
+@server_api.post('/render')
 def render(req : task_manager.ImageRequest):
     try:
-        save_model_to_config(req.use_stable_diffusion_model, req.use_vae_model, req.use_hypernetwork_model)
-        req.use_stable_diffusion_model = resolve_ckpt_to_use(req.use_stable_diffusion_model)
-        req.use_vae_model = resolve_vae_to_use(req.use_vae_model)
-        req.use_hypernetwork_model = resolve_hypernetwork_to_use(req.use_hypernetwork_model)
+        app.save_model_to_config(req.use_stable_diffusion_model, req.use_vae_model, req.use_hypernetwork_model)
+        req.use_stable_diffusion_model = model_manager.resolve_ckpt_to_use(req.use_stable_diffusion_model)
+        req.use_vae_model = model_manager.resolve_vae_to_use(req.use_vae_model)
+        req.use_hypernetwork_model = model_manager.resolve_hypernetwork_to_use(req.use_hypernetwork_model)
+
         new_task = task_manager.render(req)
         response = {
             'status': str(task_manager.current_state), 
@@ -419,7 +169,7 @@ def render(req : task_manager.ImageRequest):
     except Exception as e:
         raise HTTPException(status_code=500, detail=str(e))
 
-@app.get('/image/stream/{session_id:str}/{task_id:int}')
+@server_api.get('/image/stream/{session_id:str}/{task_id:int}')
 def stream(session_id:str, task_id:int):
     #TODO Move to WebSockets ??
     task = task_manager.get_cached_task(session_id, update_ttl=True)
@@ -433,7 +183,7 @@ def stream(session_id:str, task_id:int):
     #print(f'Session {session_id} opened live render stream {id(task.buffer_queue)}')
     return StreamingResponse(task.read_buffer_generator(), media_type='application/json')
 
-@app.get('/image/stop')
+@server_api.get('/image/stop')
 def stop(session_id:str=None):
     if not session_id:
         if task_manager.current_state == task_manager.ServerStates.Online or task_manager.current_state == task_manager.ServerStates.Unavailable:
@@ -446,7 +196,7 @@ def stop(session_id:str=None):
     task.error = StopAsyncIteration('')
     return {'OK'}
 
-@app.get('/image/tmp/{session_id}/{img_id:int}')
+@server_api.get('/image/tmp/{session_id}/{img_id:int}')
 def get_image(session_id, img_id):
     task = task_manager.get_cached_task(session_id, update_ttl=True)
     if not task: raise HTTPException(status_code=410, detail=f'Session {session_id} has not submitted a task.') # HTTP410 Gone
@@ -458,49 +208,17 @@ def get_image(session_id, img_id):
     except KeyError as e:
         raise HTTPException(status_code=500, detail=str(e))
 
-@app.get('/')
+@server_api.get('/')
 def read_root():
-    return FileResponse(os.path.join(SD_UI_DIR, 'index.html'), headers=NOCACHE_HEADERS)
+    return FileResponse(os.path.join(app.SD_UI_DIR, 'index.html'), headers=NOCACHE_HEADERS)
 
-@app.on_event("shutdown")
+@server_api.on_event("shutdown")
 def shutdown_event(): # Signal render thread to close on shutdown
     task_manager.current_state_error = SystemExit('Application shutting down.')
 
-# don't log certain requests
-class LogSuppressFilter(logging.Filter):
-    def filter(self, record: logging.LogRecord) -> bool:
-        path = record.getMessage()
-        for prefix in ACCESS_LOG_SUPPRESS_PATH_PREFIXES:
-            if path.find(prefix) != -1:
-                return False
-        return True
-logging.getLogger('uvicorn.access').addFilter(LogSuppressFilter())
-
-# Check models and prepare cache for UI open
-getModels()
-
-# Start the task_manager
-task_manager.default_model_to_load = resolve_ckpt_to_use()
-task_manager.default_vae_to_load = resolve_vae_to_use()
-task_manager.default_hypernetwork_to_load = resolve_hypernetwork_to_use()
-
-def update_render_threads():
-    config = getConfig()
-    render_devices = config.get('render_devices', 'auto')
-    active_devices = task_manager.get_devices()['active'].keys()
-
-    print('requesting for render_devices', render_devices)
-    task_manager.update_render_threads(render_devices, active_devices)
-
-update_render_threads()
+# Init the app
+model_manager.init()
+app.init()
 
 # start the browser ui
-def open_browser():
-    config = getConfig()
-    ui = config.get('ui', {})
-    net = config.get('net', {'listen_port':9000})
-    port = net.get('listen_port', 9000)
-    if ui.get('open_browser_on_start', True):
-        import webbrowser; webbrowser.open(f"http://localhost:{port}")
-
-open_browser()
+app.open_browser()

From bad89160cc224916fd4b367791d3a0442cc105ec Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Thu, 8 Dec 2022 13:50:46 +0530
Subject: [PATCH 02/74] Work-in-progress model loading

---
 ui/sd_internal/app.py           |  4 ----
 ui/sd_internal/model_manager.py | 25 ++++++++++++-------------
 ui/sd_internal/runtime2.py      | 29 +++++++++++++++++++++++++----
 ui/sd_internal/task_manager.py  |  6 +++---
 4 files changed, 40 insertions(+), 24 deletions(-)

diff --git a/ui/sd_internal/app.py b/ui/sd_internal/app.py
index 09242319..00d2e718 100644
--- a/ui/sd_internal/app.py
+++ b/ui/sd_internal/app.py
@@ -18,10 +18,6 @@ USER_UI_PLUGINS_DIR = os.path.abspath(os.path.join(SD_DIR, '..', 'plugins', 'ui'
 CORE_UI_PLUGINS_DIR = os.path.abspath(os.path.join(SD_UI_DIR, 'plugins', 'ui'))
 UI_PLUGINS_SOURCES = ((CORE_UI_PLUGINS_DIR, 'core'), (USER_UI_PLUGINS_DIR, 'user'))
 
-STABLE_DIFFUSION_MODEL_EXTENSIONS = ['.ckpt', '.safetensors']
-VAE_MODEL_EXTENSIONS = ['.vae.pt', '.ckpt']
-HYPERNETWORK_MODEL_EXTENSIONS = ['.pt']
-
 OUTPUT_DIRNAME = "Stable Diffusion UI" # in the user's home folder
 TASK_TTL = 15 * 60 # Discard last session's task timeout
 APP_CONFIG_DEFAULTS = {
diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index 3941b130..906038e1 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -4,6 +4,10 @@ from sd_internal import app
 import picklescan.scanner
 import rich
 
+STABLE_DIFFUSION_MODEL_EXTENSIONS = ['.ckpt', '.safetensors']
+VAE_MODEL_EXTENSIONS = ['.vae.pt', '.ckpt']
+HYPERNETWORK_MODEL_EXTENSIONS = ['.pt']
+
 default_model_to_load = None
 default_vae_to_load = None
 default_hypernetwork_to_load = None
@@ -59,22 +63,17 @@ def resolve_model_to_use(model_name:str, model_type:str, model_dir:str, model_ex
                         print(f'Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}')
                     return default_model_path + model_extension
 
-    raise Exception('No valid models found.')
+    print(f'No valid models found for model_name: {model_name}')
+    return None
 
 def resolve_ckpt_to_use(model_name:str=None):
-    return resolve_model_to_use(model_name, model_type='stable-diffusion', model_dir='stable-diffusion', model_extensions=app.STABLE_DIFFUSION_MODEL_EXTENSIONS, default_models=app.APP_CONFIG_DEFAULT_MODELS)
+    return resolve_model_to_use(model_name, model_type='stable-diffusion', model_dir='stable-diffusion', model_extensions=STABLE_DIFFUSION_MODEL_EXTENSIONS, default_models=app.APP_CONFIG_DEFAULT_MODELS)
 
 def resolve_vae_to_use(model_name:str=None):
-    try:
-        return resolve_model_to_use(model_name, model_type='vae', model_dir='vae', model_extensions=app.VAE_MODEL_EXTENSIONS, default_models=[])
-    except:
-        return None
+    return resolve_model_to_use(model_name, model_type='vae', model_dir='vae', model_extensions=VAE_MODEL_EXTENSIONS, default_models=[])
 
 def resolve_hypernetwork_to_use(model_name:str=None):
-    try:
-        return resolve_model_to_use(model_name, model_type='hypernetwork', model_dir='hypernetwork', model_extensions=app.HYPERNETWORK_MODEL_EXTENSIONS, default_models=[])
-    except:
-        return None
+    return resolve_model_to_use(model_name, model_type='hypernetwork', model_dir='hypernetwork', model_extensions=HYPERNETWORK_MODEL_EXTENSIONS, default_models=[])
 
 def is_malicious_model(file_path):
     try:
@@ -129,9 +128,9 @@ def getModels():
         models['options'][model_type].sort()
 
     # custom models
-    listModels(models_dirname='stable-diffusion', model_type='stable-diffusion', model_extensions=app.STABLE_DIFFUSION_MODEL_EXTENSIONS)
-    listModels(models_dirname='vae', model_type='vae', model_extensions=app.VAE_MODEL_EXTENSIONS)
-    listModels(models_dirname='hypernetwork', model_type='hypernetwork', model_extensions=app.HYPERNETWORK_MODEL_EXTENSIONS)
+    listModels(models_dirname='stable-diffusion', model_type='stable-diffusion', model_extensions=STABLE_DIFFUSION_MODEL_EXTENSIONS)
+    listModels(models_dirname='vae', model_type='vae', model_extensions=VAE_MODEL_EXTENSIONS)
+    listModels(models_dirname='hypernetwork', model_type='hypernetwork', model_extensions=HYPERNETWORK_MODEL_EXTENSIONS)
 
     # legacy
     custom_weight_path = os.path.join(app.SD_DIR, 'custom-model.ckpt')
diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index 32befcde..fc8d944d 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -1,7 +1,8 @@
 import threading
 import queue
 
-from sd_internal import device_manager, Request, Response, Image as ResponseImage
+from sd_internal import device_manager, model_manager
+from sd_internal import Request, Response, Image as ResponseImage
 
 from modules import model_loader, image_generator, image_utils
 
@@ -18,7 +19,7 @@ def init(device):
     thread_data.temp_images = {}
 
     thread_data.models = {}
-    thread_data.loaded_model_paths = {}
+    thread_data.model_paths = {}
 
     thread_data.device = None
     thread_data.device_name = None
@@ -27,14 +28,34 @@ def init(device):
 
     device_manager.device_init(thread_data, device)
 
-    reload_models()
+    load_default_models()
 
 def destroy():
     model_loader.unload_sd_model(thread_data)
     model_loader.unload_gfpgan_model(thread_data)
     model_loader.unload_realesrgan_model(thread_data)
 
-def reload_models(req: Request=None):
+def load_default_models():
+    thread_data.model_paths['stable-diffusion'] = model_manager.default_model_to_load
+    thread_data.model_paths['vae'] = model_manager.default_vae_to_load
+
+    model_loader.load_sd_model(thread_data)
+
+def reload_models_if_necessary(req: Request=None):
+    needs_model_reload = False
+    if 'stable-diffusion' not in thread_data.models or thread_data.ckpt_file != req.use_stable_diffusion_model or thread_data.vae_file != req.use_vae_model:
+        thread_data.ckpt_file = req.use_stable_diffusion_model
+        thread_data.vae_file = req.use_vae_model
+        needs_model_reload = True
+
+    if thread_data.device != 'cpu':
+        if (thread_data.precision == 'autocast' and (req.use_full_precision or not thread_data.model_is_half)) or \
+            (thread_data.precision == 'full' and not req.use_full_precision and not thread_data.force_full_precision):
+            thread_data.precision = 'full' if req.use_full_precision else 'autocast'
+            needs_model_reload = True
+
+    return needs_model_reload
+
     if is_hypernetwork_reload_necessary(task.request):
         current_state = ServerStates.LoadingModel
         runtime.reload_hypernetwork()
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 7a58ac14..04cc9a69 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -310,9 +310,6 @@ def thread_render(device):
         print(f'Session {task.request.session_id} starting task {id(task)} on {runtime2.thread_data.device_name}')
         if not task.lock.acquire(blocking=False): raise Exception('Got locked task from queue.')
         try:
-            current_state = ServerStates.LoadingModel
-            runtime2.reload_models(task.request)
-
             def step_callback():
                 global current_state_error
 
@@ -323,6 +320,9 @@ def thread_render(device):
                         current_state_error = None
                         print(f'Session {task.request.session_id} sent cancel signal for task {id(task)}')
 
+            current_state = ServerStates.LoadingModel
+            runtime2.reload_models_if_necessary(task.request)
+
             current_state = ServerStates.Rendering
             task.response = runtime2.make_image(task.request, task.buffer_queue, task.temp_images, step_callback)
             # Before looping back to the generator, mark cache as still alive.

From f4a6910ab45181d1f530bdc7a2c9d6e52c6cc90b Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Thu, 8 Dec 2022 21:39:09 +0530
Subject: [PATCH 03/74] Work-in-progress: refactored the end-to-end codebase.
 Missing: hypernetworks, turbo config, and SD 2. Not tested yet

---
 scripts/on_sd_start.bat          |   5 -
 scripts/on_sd_start.sh           |   5 -
 ui/index.html                    |   1 -
 ui/media/js/parameters.js        |  19 +--
 ui/sd_internal/__init__.py       |   7 ++
 ui/sd_internal/app.py            |   5 -
 ui/sd_internal/device_manager.py |  10 +-
 ui/sd_internal/model_manager.py  |  98 ++++++++++-----
 ui/sd_internal/runtime2.py       | 209 ++++++++++++++++++++++---------
 ui/sd_internal/task_manager.py   |   2 +-
 ui/server.py                     |   6 +-
 11 files changed, 239 insertions(+), 128 deletions(-)

diff --git a/scripts/on_sd_start.bat b/scripts/on_sd_start.bat
index 2bcf56d2..d8981226 100644
--- a/scripts/on_sd_start.bat
+++ b/scripts/on_sd_start.bat
@@ -199,12 +199,7 @@ call WHERE uvicorn > .tmp
 
 
 
-if not exist "..\models\stable-diffusion" mkdir "..\models\stable-diffusion"
 if not exist "..\models\vae" mkdir "..\models\vae"
-if not exist "..\models\hypernetwork" mkdir "..\models\hypernetwork"
-echo. > "..\models\stable-diffusion\Put your custom ckpt files here.txt"
-echo. > "..\models\vae\Put your VAE files here.txt"
-echo. > "..\models\hypernetwork\Put your hypernetwork files here.txt"
 
 @if exist "sd-v1-4.ckpt" (
     for %%I in ("sd-v1-4.ckpt") do if "%%~zI" EQU "4265380512" (
diff --git a/scripts/on_sd_start.sh b/scripts/on_sd_start.sh
index 8682c5cc..3e1c9c58 100755
--- a/scripts/on_sd_start.sh
+++ b/scripts/on_sd_start.sh
@@ -159,12 +159,7 @@ fi
 
 
 
-mkdir -p "../models/stable-diffusion"
 mkdir -p "../models/vae"
-mkdir -p "../models/hypernetwork"
-echo "" > "../models/stable-diffusion/Put your custom ckpt files here.txt"
-echo "" > "../models/vae/Put your VAE files here.txt"
-echo "" > "../models/hypernetwork/Put your hypernetwork files here.txt"
 
 if [ -f "sd-v1-4.ckpt" ]; then
     model_size=`find "sd-v1-4.ckpt" -printf "%s"`
diff --git a/ui/index.html b/ui/index.html
index d3fb6da3..0094201b 100644
--- a/ui/index.html
+++ b/ui/index.html
@@ -409,7 +409,6 @@
 async function init() {
     await initSettings()
     await getModels()
-    await getDiskPath()
     await getAppConfig()
     await loadUIPlugins()
     await loadModifiers()
diff --git a/ui/media/js/parameters.js b/ui/media/js/parameters.js
index 5c522d7e..3643d1ec 100644
--- a/ui/media/js/parameters.js
+++ b/ui/media/js/parameters.js
@@ -327,20 +327,10 @@ autoPickGPUsField.addEventListener('click', function() {
     gpuSettingEntry.style.display = (this.checked ? 'none' : '')
 })
 
-async function getDiskPath() {
-    try {
-        var diskPath = getSetting("diskPath")
-        if (diskPath == '' || diskPath == undefined || diskPath == "undefined") {
-            let res = await fetch('/get/output_dir')
-            if (res.status === 200) {
-                res = await res.json()
-                res = res.output_dir
-
-                setSetting("diskPath", res)
-            }
-        }
-    } catch (e) {
-        console.log('error fetching output dir path', e)
+async function setDiskPath(defaultDiskPath) {
+    var diskPath = getSetting("diskPath")
+    if (diskPath == '' || diskPath == undefined || diskPath == "undefined") {
+        setSetting("diskPath", defaultDiskPath)
     }
 }
 
@@ -415,6 +405,7 @@ async function getSystemInfo() {
 
         setDeviceInfo(devices)
         setHostInfo(res['hosts'])
+        setDiskPath(res['default_output_dir'])
     } catch (e) {
         console.log('error fetching devices', e)
     }
diff --git a/ui/sd_internal/__init__.py b/ui/sd_internal/__init__.py
index bf16bb5e..b001d3f9 100644
--- a/ui/sd_internal/__init__.py
+++ b/ui/sd_internal/__init__.py
@@ -105,6 +105,10 @@ class Response:
     request: Request
     images: list
 
+    def __init__(self, request: Request, images: list):
+        self.request = request
+        self.images = images
+
     def json(self):
         res = {
             "status": 'succeeded',
@@ -116,3 +120,6 @@ class Response:
             res["output"].append(image.json())
 
         return res
+
+class UserInitiatedStop(Exception):
+    pass
diff --git a/ui/sd_internal/app.py b/ui/sd_internal/app.py
index 00d2e718..d1cec46f 100644
--- a/ui/sd_internal/app.py
+++ b/ui/sd_internal/app.py
@@ -28,11 +28,6 @@ APP_CONFIG_DEFAULTS = {
         'open_browser_on_start': True,
     },
 }
-DEFAULT_MODELS = [
-    # needed to support the legacy installations
-    'custom-model', # Check if user has a custom model, use it first.
-    'sd-v1-4', # Default fallback.
-]
 
 def init():
     os.makedirs(USER_UI_PLUGINS_DIR, exist_ok=True)
diff --git a/ui/sd_internal/device_manager.py b/ui/sd_internal/device_manager.py
index 3c1d8bf1..4de6b265 100644
--- a/ui/sd_internal/device_manager.py
+++ b/ui/sd_internal/device_manager.py
@@ -101,10 +101,8 @@ def device_init(context, device):
     context.device = device
 
     # Force full precision on 1660 and 1650 NVIDIA cards to avoid creating green images
-    device_name = context.device_name.lower()
-    force_full_precision = (('nvidia' in device_name or 'geforce' in device_name) and (' 1660' in device_name or ' 1650' in device_name)) or ('Quadro T2000' in device_name)
-    if force_full_precision:
-        print('forcing full precision on NVIDIA 16xx cards, to avoid green images. GPU detected: ', context.device_name)
+    if needs_to_force_full_precision(context.device_name):
+        print(f'forcing full precision on this GPU, to avoid green images. GPU detected: {context.device_name}')
         # Apply force_full_precision now before models are loaded.
         context.precision = 'full'
 
@@ -113,6 +111,10 @@ def device_init(context, device):
 
     return
 
+def needs_to_force_full_precision(context):
+    device_name = context.device_name.lower()
+    return (('nvidia' in device_name or 'geforce' in device_name) and (' 1660' in device_name or ' 1650' in device_name)) or ('Quadro T2000' in device_name)
+
 def validate_device_id(device, log_prefix=''):
     def is_valid():
         if not isinstance(device, str):
diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index 906038e1..a8b249a2 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -1,32 +1,39 @@
 import os
 
-from sd_internal import app
+from sd_internal import app, device_manager
+from sd_internal import Request
 import picklescan.scanner
 import rich
 
-STABLE_DIFFUSION_MODEL_EXTENSIONS = ['.ckpt', '.safetensors']
-VAE_MODEL_EXTENSIONS = ['.vae.pt', '.ckpt']
-HYPERNETWORK_MODEL_EXTENSIONS = ['.pt']
-
-default_model_to_load = None
-default_vae_to_load = None
-default_hypernetwork_to_load = None
+KNOWN_MODEL_TYPES = ['stable-diffusion', 'vae', 'hypernetwork', 'gfpgan', 'realesrgan']
+MODEL_EXTENSIONS = {
+    'stable-diffusion': ['.ckpt', '.safetensors'],
+    'vae': ['.vae.pt', '.ckpt'],
+    'hypernetwork': ['.pt'],
+    'gfpgan': ['.pth'],
+    'realesrgan': ['.pth'],
+}
+DEFAULT_MODELS = {
+    'stable-diffusion': [ # needed to support the legacy installations
+        'custom-model', # only one custom model file was supported initially, creatively named 'custom-model'
+        'sd-v1-4', # Default fallback.
+    ],
+    'gfpgan': ['GFPGANv1.3'],
+    'realesrgan': ['RealESRGAN_x4plus'],
+}
 
 known_models = {}
 
 def init():
-    global default_model_to_load, default_vae_to_load, default_hypernetwork_to_load
-
-    default_model_to_load = resolve_ckpt_to_use()
-    default_vae_to_load = resolve_vae_to_use()
-    default_hypernetwork_to_load = resolve_hypernetwork_to_use()
-
+    make_model_folders()
     getModels() # run this once, to cache the picklescan results
 
-def resolve_model_to_use(model_name:str, model_type:str, model_dir:str, model_extensions:list, default_models=[]):
+def resolve_model_to_use(model_name:str, model_type:str):
+    model_extensions = MODEL_EXTENSIONS.get(model_type, [])
+    default_models = DEFAULT_MODELS.get(model_type, [])
     config = app.getConfig()
 
-    model_dirs = [os.path.join(app.MODELS_DIR, model_dir), app.SD_DIR]
+    model_dirs = [os.path.join(app.MODELS_DIR, model_type), app.SD_DIR]
     if not model_name: # When None try user configured model.
         # config = getConfig()
         if 'model' in config and model_type in config['model']:
@@ -39,7 +46,7 @@ def resolve_model_to_use(model_name:str, model_type:str, model_dir:str, model_ex
             model_name = 'sd-v1-4'
 
         # Check models directory
-        models_dir_path = os.path.join(app.MODELS_DIR, model_dir, model_name)
+        models_dir_path = os.path.join(app.MODELS_DIR, model_type, model_name)
         for model_extension in model_extensions:
             if os.path.exists(models_dir_path + model_extension):
                 return models_dir_path + model_extension
@@ -66,14 +73,32 @@ def resolve_model_to_use(model_name:str, model_type:str, model_dir:str, model_ex
     print(f'No valid models found for model_name: {model_name}')
     return None
 
-def resolve_ckpt_to_use(model_name:str=None):
-    return resolve_model_to_use(model_name, model_type='stable-diffusion', model_dir='stable-diffusion', model_extensions=STABLE_DIFFUSION_MODEL_EXTENSIONS, default_models=app.APP_CONFIG_DEFAULT_MODELS)
+def resolve_sd_model_to_use(model_name:str=None):
+    return resolve_model_to_use(model_name, model_type='stable-diffusion')
 
-def resolve_vae_to_use(model_name:str=None):
-    return resolve_model_to_use(model_name, model_type='vae', model_dir='vae', model_extensions=VAE_MODEL_EXTENSIONS, default_models=[])
+def resolve_vae_model_to_use(model_name:str=None):
+    return resolve_model_to_use(model_name, model_type='vae')
 
-def resolve_hypernetwork_to_use(model_name:str=None):
-    return resolve_model_to_use(model_name, model_type='hypernetwork', model_dir='hypernetwork', model_extensions=HYPERNETWORK_MODEL_EXTENSIONS, default_models=[])
+def resolve_hypernetwork_model_to_use(model_name:str=None):
+    return resolve_model_to_use(model_name, model_type='hypernetwork')
+
+def resolve_gfpgan_model_to_use(model_name:str=None):
+    return resolve_model_to_use(model_name, model_type='gfpgan')
+
+def resolve_realesrgan_model_to_use(model_name:str=None):
+    return resolve_model_to_use(model_name, model_type='realesrgan')
+
+def make_model_folders():
+    for model_type in KNOWN_MODEL_TYPES:
+        model_dir_path = os.path.join(app.MODELS_DIR, model_type)
+
+        os.makedirs(model_dir_path, exist_ok=True)
+
+        help_file_name = f'Place your {model_type} model files here.txt'
+        help_file_contents = f'Supported extensions: {" or ".join(MODEL_EXTENSIONS.get(model_type))}'
+
+        with open(os.path.join(model_dir_path, help_file_name)) as f:
+            f.write(help_file_contents)
 
 def is_malicious_model(file_path):
     try:
@@ -102,8 +127,9 @@ def getModels():
         },
     }
 
-    def listModels(models_dirname, model_type, model_extensions):
-        models_dir = os.path.join(app.MODELS_DIR, models_dirname)
+    def listModels(model_type):
+        model_extensions = MODEL_EXTENSIONS.get(model_type, [])
+        models_dir = os.path.join(app.MODELS_DIR, model_type)
         if not os.path.exists(models_dir):
             os.makedirs(models_dir)
 
@@ -128,9 +154,9 @@ def getModels():
         models['options'][model_type].sort()
 
     # custom models
-    listModels(models_dirname='stable-diffusion', model_type='stable-diffusion', model_extensions=STABLE_DIFFUSION_MODEL_EXTENSIONS)
-    listModels(models_dirname='vae', model_type='vae', model_extensions=VAE_MODEL_EXTENSIONS)
-    listModels(models_dirname='hypernetwork', model_type='hypernetwork', model_extensions=HYPERNETWORK_MODEL_EXTENSIONS)
+    listModels(model_type='stable-diffusion')
+    listModels(model_type='vae')
+    listModels(model_type='hypernetwork')
 
     # legacy
     custom_weight_path = os.path.join(app.SD_DIR, 'custom-model.ckpt')
@@ -138,3 +164,19 @@ def getModels():
         models['options']['stable-diffusion'].append('custom-model')
 
     return models
+
+def is_sd_model_reload_necessary(thread_data, req: Request):
+    needs_model_reload = False
+    if 'stable-diffusion' not in thread_data.models or \
+        thread_data.model_paths['stable-diffusion'] != req.use_stable_diffusion_model or \
+        thread_data.model_paths['vae'] != req.use_vae_model:
+
+        needs_model_reload = True
+
+    if thread_data.device != 'cpu':
+        if (thread_data.precision == 'autocast' and req.use_full_precision) or \
+            (thread_data.precision == 'full' and not req.use_full_precision and not device_manager.needs_to_force_full_precision(thread_data)):
+            thread_data.precision = 'full' if req.use_full_precision else 'autocast'
+            needs_model_reload = True
+
+    return needs_model_reload
diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index fc8d944d..840cec09 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -1,16 +1,23 @@
 import threading
 import queue
+import time
+import json
+import os
+import base64
+import re
 
 from sd_internal import device_manager, model_manager
-from sd_internal import Request, Response, Image as ResponseImage
+from sd_internal import Request, Response, Image as ResponseImage, UserInitiatedStop
 
-from modules import model_loader, image_generator, image_utils
+from modules import model_loader, image_generator, image_utils, image_filters
 
 thread_data = threading.local()
 '''
 runtime data (bound locally to this thread), for e.g. device, references to loaded models, optimization flags etc
 '''
 
+filename_regex = re.compile('[^a-zA-Z0-9]')
+
 def init(device):
     '''
     Initializes the fields that will be bound to this runtime's thread_data, and sets the current torch device
@@ -28,89 +35,167 @@ def init(device):
 
     device_manager.device_init(thread_data, device)
 
-    load_default_models()
+    init_and_load_default_models()
 
 def destroy():
     model_loader.unload_sd_model(thread_data)
     model_loader.unload_gfpgan_model(thread_data)
     model_loader.unload_realesrgan_model(thread_data)
 
-def load_default_models():
-    thread_data.model_paths['stable-diffusion'] = model_manager.default_model_to_load
-    thread_data.model_paths['vae'] = model_manager.default_vae_to_load
+def init_and_load_default_models():
+    # init default model paths
+    thread_data.model_paths['stable-diffusion'] = model_manager.resolve_sd_model_to_use()
+    thread_data.model_paths['vae'] = model_manager.resolve_vae_model_to_use()
+    thread_data.model_paths['hypernetwork'] = model_manager.resolve_hypernetwork_model_to_use()
+    thread_data.model_paths['gfpgan'] = model_manager.resolve_gfpgan_model_to_use()
+    thread_data.model_paths['realesrgan'] = model_manager.resolve_realesrgan_model_to_use()
 
+    # load mandatory models
     model_loader.load_sd_model(thread_data)
 
-def reload_models_if_necessary(req: Request=None):
-    needs_model_reload = False
-    if 'stable-diffusion' not in thread_data.models or thread_data.ckpt_file != req.use_stable_diffusion_model or thread_data.vae_file != req.use_vae_model:
-        thread_data.ckpt_file = req.use_stable_diffusion_model
-        thread_data.vae_file = req.use_vae_model
-        needs_model_reload = True
+def reload_models_if_necessary(req: Request):
+    if model_manager.is_sd_model_reload_necessary(thread_data, req):
+        thread_data.model_paths['stable-diffusion'] = req.use_stable_diffusion_model
+        thread_data.model_paths['vae'] = req.use_vae_model
 
-    if thread_data.device != 'cpu':
-        if (thread_data.precision == 'autocast' and (req.use_full_precision or not thread_data.model_is_half)) or \
-            (thread_data.precision == 'full' and not req.use_full_precision and not thread_data.force_full_precision):
-            thread_data.precision = 'full' if req.use_full_precision else 'autocast'
-            needs_model_reload = True
+        model_loader.load_sd_model(thread_data)
 
-    return needs_model_reload
+    # if is_hypernetwork_reload_necessary(task.request):
+    #     current_state = ServerStates.LoadingModel
+    #     runtime.reload_hypernetwork()
 
-    if is_hypernetwork_reload_necessary(task.request):
-        current_state = ServerStates.LoadingModel
-        runtime.reload_hypernetwork()
+def make_images(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
+    images, user_stopped = generate_images(req, data_queue, task_temp_images, step_callback)
+    images = apply_filters(req, images, user_stopped)
 
-    if is_model_reload_necessary(task.request):
-        current_state = ServerStates.LoadingModel
-        runtime.reload_model()
+    save_images(req, images)
 
-def load_models():
-    if ckpt_file_path == None:
-        ckpt_file_path = default_model_to_load
-    if vae_file_path == None:
-        vae_file_path = default_vae_to_load
-    if hypernetwork_file_path == None:
-        hypernetwork_file_path = default_hypernetwork_to_load
-    if ckpt_file_path == current_model_path and vae_file_path == current_vae_path:
-        return
-    current_state = ServerStates.LoadingModel
-    try:
-        from sd_internal import runtime2
-        runtime.thread_data.hypernetwork_file = hypernetwork_file_path
-        runtime.thread_data.ckpt_file = ckpt_file_path
-        runtime.thread_data.vae_file = vae_file_path
-        runtime.load_model_ckpt()
-        runtime.load_hypernetwork()
-        current_model_path = ckpt_file_path
-        current_vae_path = vae_file_path
-        current_hypernetwork_path = hypernetwork_file_path
-        current_state_error = None
-        current_state = ServerStates.Online
-    except Exception as e:
-        current_model_path = None
-        current_vae_path = None
-        current_state_error = e
-        current_state = ServerStates.Unavailable
-        print(traceback.format_exc())
+    return Response(req, images=construct_response(req, images))
+
+def generate_images(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
+    thread_data.temp_images.clear()
+
+    image_generator.on_image_step = make_step_callback(req, data_queue, task_temp_images, step_callback)
 
-def make_image(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
     try:
         images = image_generator.make_image(context=thread_data, args=get_mk_img_args(req))
+        user_stopped = False
     except UserInitiatedStop:
-        pass
+        images = []
+        user_stopped = True
+        if not hasattr(thread_data, 'partial_x_samples') or thread_data.partial_x_samples is None:
+            return images
+        for i in range(req.num_outputs):
+            images[i] = image_utils.latent_to_img(thread_data, thread_data.partial_x_samples[i].unsqueeze(0))
+        
+        del thread_data.partial_x_samples
+    finally:
+        model_loader.gc(thread_data)
+    
+    images = [(image, req.seed + i, False) for i, image in enumerate(images)]
+
+    return images, user_stopped
+
+def apply_filters(req: Request, images: list, user_stopped):
+    if user_stopped or (req.use_face_correction is None and req.use_upscale is None):
+        return images
+
+    filters = []
+    if req.use_face_correction.startswith('GFPGAN'): filters.append((image_filters.apply_gfpgan, model_manager.resolve_gfpgan_model_to_use(req.use_face_correction)))
+    if req.use_upscale.startswith('RealESRGAN'): filters.append((image_filters.apply_realesrgan, model_manager.resolve_realesrgan_model_to_use(req.use_upscale)))
+
+    filtered_images = []
+    for img, seed, _ in images:
+        for filter_fn, filter_model_path in filters:
+            img = filter_fn(thread_data, img, filter_model_path)
+
+        filtered_images.append((img, seed, True))
+
+    if not req.show_only_filtered_image:
+        filtered_images = images + filtered_images
+
+    return filtered_images
+
+def save_images(req: Request, images: list):
+    if req.save_to_disk_path is None:
+        return
+
+    def get_image_id(i):
+        img_id = base64.b64encode(int(time.time()+i).to_bytes(8, 'big')).decode() # Generate unique ID based on time.
+        img_id = img_id.translate({43:None, 47:None, 61:None})[-8:] # Remove + / = and keep last 8 chars.
+        return img_id
+
+    def get_image_basepath(i):
+        session_out_path = os.path.join(req.save_to_disk_path, filename_regex.sub('_', req.session_id))
+        os.makedirs(session_out_path, exist_ok=True)
+        prompt_flattened = filename_regex.sub('_', req.prompt)[:50]
+        return os.path.join(session_out_path, f"{prompt_flattened}_{get_image_id(i)}")
+
+    for i, img_data in enumerate(images):
+        img, seed, filtered = img_data
+        img_path = get_image_basepath(i)
+
+        if not filtered or req.show_only_filtered_image:
+            img_metadata_path = img_path + '.txt'
+            metadata = req.json()
+            metadata['seed'] = seed
+            with open(img_metadata_path, 'w', encoding='utf-8') as f:
+                f.write(metadata)
+
+        img_path += '_filtered' if filtered else ''
+        img_path += '.' + req.output_format
+        img.save(img_path, quality=req.output_quality)
+
+def construct_response(req: Request, images: list):
+    return [
+        ResponseImage(
+            data=image_utils.img_to_base64_str(img, req.output_format, req.output_quality),
+            seed=seed
+        ) for img, seed, _ in images
+    ]
 
 def get_mk_img_args(req: Request):
     args = req.json()
 
-    if req.init_image is not None:
-        args['init_image'] = image_utils.base64_str_to_img(req.init_image)
-
-    if req.mask is not None:
-        args['mask'] = image_utils.base64_str_to_img(req.mask)
+    args['init_image'] = image_utils.base64_str_to_img(req.init_image) if req.init_image is not None else None
+    args['mask'] = image_utils.base64_str_to_img(req.mask) if req.mask is not None else None
 
     return args
 
-def on_image_step(x_samples, i):
-    pass
+def make_step_callback(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
+    n_steps = req.num_inference_steps if req.init_image is None else int(req.num_inference_steps * req.prompt_strength)
+    last_callback_time = -1
 
-image_generator.on_image_step = on_image_step
+    def update_temp_img(req, x_samples, task_temp_images: list):
+        partial_images = []
+        for i in range(req.num_outputs):
+            img = image_utils.latent_to_img(thread_data, x_samples[i].unsqueeze(0))
+            buf = image_utils.img_to_buffer(img, output_format='JPEG')
+
+            del img
+
+            thread_data.temp_images[f'{req.request_id}/{i}'] = buf
+            task_temp_images[i] = buf
+            partial_images.append({'path': f'/image/tmp/{req.request_id}/{i}'})
+        return partial_images
+
+    def on_image_step(x_samples, i):
+        nonlocal last_callback_time
+
+        thread_data.partial_x_samples = x_samples
+        step_time = time.time() - last_callback_time if last_callback_time != -1 else -1
+        last_callback_time = time.time()
+
+        progress = {"step": i, "step_time": step_time, "total_steps": n_steps}
+
+        if req.stream_image_progress and i % 5 == 0:
+            progress['output'] = update_temp_img(req, x_samples, task_temp_images)
+
+        data_queue.put(json.dumps(progress))
+
+        step_callback()
+
+        if thread_data.stop_processing:
+            raise UserInitiatedStop("User requested that we stop processing")
+
+    return on_image_step
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 04cc9a69..c6ab9737 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -324,7 +324,7 @@ def thread_render(device):
             runtime2.reload_models_if_necessary(task.request)
 
             current_state = ServerStates.Rendering
-            task.response = runtime2.make_image(task.request, task.buffer_queue, task.temp_images, step_callback)
+            task.response = runtime2.make_images(task.request, task.buffer_queue, task.temp_images, step_callback)
             # Before looping back to the generator, mark cache as still alive.
             task_cache.keep(id(task), TASK_TTL)
             session_cache.keep(task.request.session_id, TASK_TTL)
diff --git a/ui/server.py b/ui/server.py
index 1cb4c910..fd2557e2 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -137,9 +137,9 @@ def ping(session_id:str=None):
 def render(req : task_manager.ImageRequest):
     try:
         app.save_model_to_config(req.use_stable_diffusion_model, req.use_vae_model, req.use_hypernetwork_model)
-        req.use_stable_diffusion_model = model_manager.resolve_ckpt_to_use(req.use_stable_diffusion_model)
-        req.use_vae_model = model_manager.resolve_vae_to_use(req.use_vae_model)
-        req.use_hypernetwork_model = model_manager.resolve_hypernetwork_to_use(req.use_hypernetwork_model)
+        req.use_stable_diffusion_model = model_manager.resolve_sd_model_to_use(req.use_stable_diffusion_model)
+        req.use_vae_model = model_manager.resolve_vae_model_to_use(req.use_vae_model)
+        req.use_hypernetwork_model = model_manager.resolve_hypernetwork_model_to_use(req.use_hypernetwork_model)
 
         new_task = task_manager.render(req)
         response = {

From 27c61132871c21d3c7c30197c5f6bc14429ec82e Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 9 Dec 2022 13:29:06 +0530
Subject: [PATCH 04/74] Support hypernetworks; moves the hypernetwork module to
 diffusion-kit

---
 ui/sd_internal/hypernetwork.py  | 198 --------------------------------
 ui/sd_internal/model_manager.py |   1 -
 ui/sd_internal/runtime2.py      |  11 +-
 3 files changed, 8 insertions(+), 202 deletions(-)
 delete mode 100644 ui/sd_internal/hypernetwork.py

diff --git a/ui/sd_internal/hypernetwork.py b/ui/sd_internal/hypernetwork.py
deleted file mode 100644
index 979a74f3..00000000
--- a/ui/sd_internal/hypernetwork.py
+++ /dev/null
@@ -1,198 +0,0 @@
-# this is basically a cut down version of https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob/c9a2cfdf2a53d37c2de1908423e4f548088667ef/modules/hypernetworks/hypernetwork.py, mostly for feature parity
-# I, c0bra5, don't really understand how deep learning works. I just know how to port stuff.
-
-import inspect
-import torch
-import optimizedSD.splitAttention
-from . import runtime
-from einops import rearrange
-
-optimizer_dict = {optim_name : cls_obj for optim_name, cls_obj in inspect.getmembers(torch.optim, inspect.isclass) if optim_name != "Optimizer"}
-
-loaded_hypernetwork = None
-
-class HypernetworkModule(torch.nn.Module):
-    multiplier = 0.5
-    activation_dict = {
-        "linear": torch.nn.Identity,
-        "relu": torch.nn.ReLU,
-        "leakyrelu": torch.nn.LeakyReLU,
-        "elu": torch.nn.ELU,
-        "swish": torch.nn.Hardswish,
-        "tanh": torch.nn.Tanh,
-        "sigmoid": torch.nn.Sigmoid,
-    }
-    activation_dict.update({cls_name.lower(): cls_obj for cls_name, cls_obj in inspect.getmembers(torch.nn.modules.activation) if inspect.isclass(cls_obj) and cls_obj.__module__ == 'torch.nn.modules.activation'})
-
-    def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, weight_init='Normal',
-                 add_layer_norm=False, use_dropout=False, activate_output=False, last_layer_dropout=False):
-        super().__init__()
-
-        assert layer_structure is not None, "layer_structure must not be None"
-        assert layer_structure[0] == 1, "Multiplier Sequence should start with size 1!"
-        assert layer_structure[-1] == 1, "Multiplier Sequence should end with size 1!"
-
-        linears = []
-        for i in range(len(layer_structure) - 1):
-
-            # Add a fully-connected layer
-            linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1])))
-
-            # Add an activation func except last layer
-            if activation_func == "linear" or activation_func is None or (i >= len(layer_structure) - 2 and not activate_output):
-                pass
-            elif activation_func in self.activation_dict:
-                linears.append(self.activation_dict[activation_func]())
-            else:
-                raise RuntimeError(f'hypernetwork uses an unsupported activation function: {activation_func}')
-
-            # Add layer normalization
-            if add_layer_norm:
-                linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1])))
-
-            # Add dropout except last layer
-            if use_dropout and (i < len(layer_structure) - 3 or last_layer_dropout and i < len(layer_structure) - 2):
-                linears.append(torch.nn.Dropout(p=0.3))
-
-        self.linear = torch.nn.Sequential(*linears)
-
-        self.fix_old_state_dict(state_dict)
-        self.load_state_dict(state_dict)
-
-        self.to(runtime.thread_data.device)
-
-    def fix_old_state_dict(self, state_dict):
-        changes = {
-            'linear1.bias': 'linear.0.bias',
-            'linear1.weight': 'linear.0.weight',
-            'linear2.bias': 'linear.1.bias',
-            'linear2.weight': 'linear.1.weight',
-        }
-
-        for fr, to in changes.items():
-            x = state_dict.get(fr, None)
-            if x is None:
-                continue
-
-            del state_dict[fr]
-            state_dict[to] = x
-
-    def forward(self, x: torch.Tensor):
-        return x + self.linear(x) * runtime.thread_data.hypernetwork_strength
-
-def apply_hypernetwork(hypernetwork, context, layer=None):
-    hypernetwork_layers = hypernetwork.get(context.shape[2], None)
-
-    if hypernetwork_layers is None:
-        return context, context
-
-    if layer is not None:
-        layer.hyper_k = hypernetwork_layers[0]
-        layer.hyper_v = hypernetwork_layers[1]
-
-    context_k = hypernetwork_layers[0](context)
-    context_v = hypernetwork_layers[1](context)
-    return context_k, context_v
-
-def get_kv(context, hypernetwork):
-    if hypernetwork is None:
-        return context, context
-    else:
-        return apply_hypernetwork(runtime.thread_data.hypernetwork, context)
-
-# This might need updating as the optimisedSD code changes
-# I think yall have a system for this (patch files in sd_internal) but idk how it works and no amount of searching gave me any clue
-# just in case for attribution https://github.com/easydiffusion/diffusion-kit/blob/e8ea0cadd543056059cd951e76d4744de76327d2/optimizedSD/splitAttention.py#L171
-def new_cross_attention_forward(self, x, context=None, mask=None):
-    h = self.heads
-
-    q = self.to_q(x)
-    # default context
-    context = context if context is not None else x() if inspect.isfunction(x) else x
-    # hypernetwork!
-    context_k, context_v =  get_kv(context, runtime.thread_data.hypernetwork)
-    k = self.to_k(context_k)
-    v = self.to_v(context_v)
-    del context, x
-
-    q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
-
-
-    limit = k.shape[0]
-    att_step = self.att_step
-    q_chunks = list(torch.tensor_split(q, limit//att_step, dim=0))
-    k_chunks = list(torch.tensor_split(k, limit//att_step, dim=0))
-    v_chunks = list(torch.tensor_split(v, limit//att_step, dim=0))
-
-    q_chunks.reverse()
-    k_chunks.reverse()
-    v_chunks.reverse()
-    sim = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device)
-    del k, q, v
-    for i in range (0, limit, att_step):
-
-        q_buffer = q_chunks.pop()
-        k_buffer = k_chunks.pop()
-        v_buffer = v_chunks.pop()
-        sim_buffer = torch.einsum('b i d, b j d -> b i j', q_buffer, k_buffer) * self.scale
-
-        del k_buffer, q_buffer
-        # attention, what we cannot get enough of, by chunks
-
-        sim_buffer = sim_buffer.softmax(dim=-1)
-
-        sim_buffer = torch.einsum('b i j, b j d -> b i d', sim_buffer, v_buffer)
-        del v_buffer
-        sim[i:i+att_step,:,:] = sim_buffer
-
-        del sim_buffer
-    sim = rearrange(sim, '(b h) n d -> b n (h d)', h=h)
-    return self.to_out(sim)
-
-
-def load_hypernetwork(path: str):
-
-    state_dict = torch.load(path, map_location='cpu')
-
-    layer_structure = state_dict.get('layer_structure', [1, 2, 1])
-    activation_func = state_dict.get('activation_func', None)
-    weight_init = state_dict.get('weight_initialization', 'Normal')
-    add_layer_norm = state_dict.get('is_layer_norm', False)
-    use_dropout = state_dict.get('use_dropout', False)
-    activate_output = state_dict.get('activate_output', True)
-    last_layer_dropout = state_dict.get('last_layer_dropout', False)
-    # this is a bit verbose so leaving it commented out for the poor soul who ever has to debug this
-    # print(f"layer_structure: {layer_structure}")
-    # print(f"activation_func: {activation_func}")
-    # print(f"weight_init: {weight_init}")
-    # print(f"add_layer_norm: {add_layer_norm}")
-    # print(f"use_dropout: {use_dropout}")
-    # print(f"activate_output: {activate_output}")
-    # print(f"last_layer_dropout: {last_layer_dropout}")
-
-    layers = {}
-    for size, sd in state_dict.items():
-        if type(size) == int:
-            layers[size] = (
-                HypernetworkModule(size, sd[0], layer_structure, activation_func, weight_init, add_layer_norm,
-                                   use_dropout, activate_output, last_layer_dropout=last_layer_dropout),
-                HypernetworkModule(size, sd[1], layer_structure, activation_func, weight_init, add_layer_norm,
-                                   use_dropout, activate_output, last_layer_dropout=last_layer_dropout),
-            )
-    print(f"hypernetwork loaded")
-    return layers
-
-
-
-# overriding of original function
-old_cross_attention_forward = optimizedSD.splitAttention.CrossAttention.forward
-# hijacks the cross attention forward function to add hyper network support
-def hijack_cross_attention():
-    print("hypernetwork functionality added to cross attention")
-    optimizedSD.splitAttention.CrossAttention.forward = new_cross_attention_forward
-# there was a cop on board
-def unhijack_cross_attention_forward():
-    print("hypernetwork functionality removed from cross attention")
-    optimizedSD.splitAttention.CrossAttention.forward = old_cross_attention_forward
-
-hijack_cross_attention()
\ No newline at end of file
diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index a8b249a2..21acb540 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -70,7 +70,6 @@ def resolve_model_to_use(model_name:str, model_type:str):
                         print(f'Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}')
                     return default_model_path + model_extension
 
-    print(f'No valid models found for model_name: {model_name}')
     return None
 
 def resolve_sd_model_to_use(model_name:str=None):
diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index 840cec09..90a868a5 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -41,6 +41,7 @@ def destroy():
     model_loader.unload_sd_model(thread_data)
     model_loader.unload_gfpgan_model(thread_data)
     model_loader.unload_realesrgan_model(thread_data)
+    model_loader.unload_hypernetwork_model(thread_data)
 
 def init_and_load_default_models():
     # init default model paths
@@ -60,9 +61,13 @@ def reload_models_if_necessary(req: Request):
 
         model_loader.load_sd_model(thread_data)
 
-    # if is_hypernetwork_reload_necessary(task.request):
-    #     current_state = ServerStates.LoadingModel
-    #     runtime.reload_hypernetwork()
+    if thread_data.model_paths.get('hypernetwork') != req.use_hypernetwork_model:
+        thread_data.model_paths['hypernetwork'] = req.use_hypernetwork_model
+
+        if thread_data.model_paths['hypernetwork'] is not None:
+            model_loader.load_hypernetwork_model(thread_data)
+        else:
+            model_loader.unload_hypernetwork_model(thread_data)
 
 def make_images(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
     images, user_stopped = generate_images(req, data_queue, task_temp_images, step_callback)

From 16410d90b81d9ceec1cc71e347224faae491d40c Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 9 Dec 2022 15:21:49 +0530
Subject: [PATCH 05/74] Use the simplified model loading API in diffusion-kit;
 Catch and report exceptions while generating images

---
 ui/sd_internal/runtime2.py | 29 +++++++++++++++++++++--------
 1 file changed, 21 insertions(+), 8 deletions(-)

diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index 90a868a5..0af0ead4 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -5,6 +5,7 @@ import json
 import os
 import base64
 import re
+import traceback
 
 from sd_internal import device_manager, model_manager
 from sd_internal import Request, Response, Image as ResponseImage, UserInitiatedStop
@@ -38,10 +39,10 @@ def init(device):
     init_and_load_default_models()
 
 def destroy():
-    model_loader.unload_sd_model(thread_data)
-    model_loader.unload_gfpgan_model(thread_data)
-    model_loader.unload_realesrgan_model(thread_data)
-    model_loader.unload_hypernetwork_model(thread_data)
+    model_loader.unload_model(thread_data, 'stable-diffusion')
+    model_loader.unload_model(thread_data, 'gfpgan')
+    model_loader.unload_model(thread_data, 'realesrgan')
+    model_loader.unload_model(thread_data, 'hypernetwork')
 
 def init_and_load_default_models():
     # init default model paths
@@ -52,24 +53,36 @@ def init_and_load_default_models():
     thread_data.model_paths['realesrgan'] = model_manager.resolve_realesrgan_model_to_use()
 
     # load mandatory models
-    model_loader.load_sd_model(thread_data)
+    model_loader.load_model(thread_data, 'stable-diffusion')
 
 def reload_models_if_necessary(req: Request):
     if model_manager.is_sd_model_reload_necessary(thread_data, req):
         thread_data.model_paths['stable-diffusion'] = req.use_stable_diffusion_model
         thread_data.model_paths['vae'] = req.use_vae_model
 
-        model_loader.load_sd_model(thread_data)
+        model_loader.load_model(thread_data, 'stable-diffusion')
 
     if thread_data.model_paths.get('hypernetwork') != req.use_hypernetwork_model:
         thread_data.model_paths['hypernetwork'] = req.use_hypernetwork_model
 
         if thread_data.model_paths['hypernetwork'] is not None:
-            model_loader.load_hypernetwork_model(thread_data)
+            model_loader.load_model(thread_data, 'hypernetwork')
         else:
-            model_loader.unload_hypernetwork_model(thread_data)
+            model_loader.unload_model(thread_data, 'hypernetwork')
 
 def make_images(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
+    try:
+        return _make_images_internal(req, data_queue, task_temp_images, step_callback)
+    except Exception as e:
+        print(traceback.format_exc())
+
+        data_queue.put(json.dumps({
+            "status": 'failed',
+            "detail": str(e)
+        }))
+        raise e
+
+def _make_images_internal(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
     images, user_stopped = generate_images(req, data_queue, task_temp_images, step_callback)
     images = apply_filters(req, images, user_stopped)
 

From accfec9007a75214d781228b8eb91928c47b6f3d Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 9 Dec 2022 15:22:56 +0530
Subject: [PATCH 06/74] Space

---
 ui/server.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/ui/server.py b/ui/server.py
index fd2557e2..b3c54342 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -20,7 +20,6 @@ server_api = FastAPI()
 
 # don't show access log entries for URLs that start with the given prefix
 ACCESS_LOG_SUPPRESS_PATH_PREFIXES = ['/ping', '/image', '/modifier-thumbnails']
-
 NOCACHE_HEADERS={"Cache-Control": "no-cache, no-store, must-revalidate", "Pragma": "no-cache", "Expires": "0"}
 
 class NoCacheStaticFiles(StaticFiles):

From aa59575df39b8fec43b2a09bddec573961c0d3dd Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 9 Dec 2022 15:24:55 +0530
Subject: [PATCH 07/74] Remove unused patch files

---
 ui/sd_internal/ddim_callback.patch     | 162 -------------------------
 ui/sd_internal/ddim_callback_sd2.patch |  84 -------------
 2 files changed, 246 deletions(-)
 delete mode 100644 ui/sd_internal/ddim_callback.patch
 delete mode 100644 ui/sd_internal/ddim_callback_sd2.patch

diff --git a/ui/sd_internal/ddim_callback.patch b/ui/sd_internal/ddim_callback.patch
deleted file mode 100644
index e4dd69e0..00000000
--- a/ui/sd_internal/ddim_callback.patch
+++ /dev/null
@@ -1,162 +0,0 @@
-diff --git a/optimizedSD/ddpm.py b/optimizedSD/ddpm.py
-index 79058bc..a473411 100644
---- a/optimizedSD/ddpm.py
-+++ b/optimizedSD/ddpm.py
-@@ -564,12 +564,12 @@ class UNet(DDPM):
-                                         unconditional_guidance_scale=unconditional_guidance_scale,
-                                         callback=callback, img_callback=img_callback)
- 
-+        yield from samples
-+
-         if(self.turbo):
-             self.model1.to("cpu")
-             self.model2.to("cpu")
- 
--        return samples
--
-     @torch.no_grad()
-     def plms_sampling(self, cond,b, img,
-                       ddim_use_original_steps=False,
-@@ -608,10 +608,10 @@ class UNet(DDPM):
-             old_eps.append(e_t)
-             if len(old_eps) >= 4:
-                 old_eps.pop(0)
--            if callback: callback(i)
--            if img_callback: img_callback(pred_x0, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(pred_x0, i)
- 
--        return img
-+        yield from img_callback(img, len(iterator)-1)
- 
-     @torch.no_grad()
-     def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,
-@@ -740,13 +740,13 @@ class UNet(DDPM):
-                                           unconditional_guidance_scale=unconditional_guidance_scale,
-                                           unconditional_conditioning=unconditional_conditioning)
- 
--            if callback: callback(i)
--            if img_callback: img_callback(x_dec, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x_dec, i)
-         
-         if mask is not None:
--            return x0 * mask + (1. - mask) * x_dec
-+            x_dec = x0 * mask + (1. - mask) * x_dec
- 
--        return x_dec
-+        yield from img_callback(x_dec, len(iterator)-1)
- 
- 
-     @torch.no_grad()
-@@ -820,12 +820,12 @@ class UNet(DDPM):
- 
- 
-             d = to_d(x, sigma_hat, denoised)
--            if callback: callback(i)
--            if img_callback: img_callback(x, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x, i)
-             dt = sigmas[i + 1] - sigma_hat
-             # Euler method
-             x = x + d * dt
--        return x
-+        yield from img_callback(x, len(sigmas)-1)
- 
-     @torch.no_grad()
-     def euler_ancestral_sampling(self,ac,x, S, cond, unconditional_conditioning = None, unconditional_guidance_scale = 1,extra_args=None, callback=None, disable=None, img_callback=None):
-@@ -852,14 +852,14 @@ class UNet(DDPM):
-             denoised = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
- 
-             sigma_down, sigma_up = get_ancestral_step(sigmas[i], sigmas[i + 1])
--            if callback: callback(i)
--            if img_callback: img_callback(x, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x, i)
-             d = to_d(x, sigmas[i], denoised)
-             # Euler method
-             dt = sigma_down - sigmas[i]
-             x = x + d * dt
-             x = x + torch.randn_like(x) * sigma_up
--        return x
-+        yield from img_callback(x, len(sigmas)-1)
- 
- 
- 
-@@ -892,8 +892,8 @@ class UNet(DDPM):
-             denoised = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
- 
-             d = to_d(x, sigma_hat, denoised)
--            if callback: callback(i)
--            if img_callback: img_callback(x, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x, i)
-             dt = sigmas[i + 1] - sigma_hat
-             if sigmas[i + 1] == 0:
-                 # Euler method
-@@ -913,7 +913,7 @@ class UNet(DDPM):
-                 d_2 = to_d(x_2, sigmas[i + 1], denoised_2)
-                 d_prime = (d + d_2) / 2
-                 x = x + d_prime * dt
--        return x
-+        yield from img_callback(x, len(sigmas)-1)
- 
- 
-     @torch.no_grad()
-@@ -944,8 +944,8 @@ class UNet(DDPM):
-             e_t_uncond, e_t = (x_in  + eps * c_out).chunk(2)
-             denoised = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
- 
--            if callback: callback(i)
--            if img_callback: img_callback(x, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x, i)
-             
-             d = to_d(x, sigma_hat, denoised)
-             # Midpoint method, where the midpoint is chosen according to a rho=3 Karras schedule
-@@ -966,7 +966,7 @@ class UNet(DDPM):
- 
-             d_2 = to_d(x_2, sigma_mid, denoised_2)
-             x = x + d_2 * dt_2
--        return x
-+        yield from img_callback(x, len(sigmas)-1)
- 
- 
-     @torch.no_grad()
-@@ -994,8 +994,8 @@ class UNet(DDPM):
- 
- 
-             sigma_down, sigma_up = get_ancestral_step(sigmas[i], sigmas[i + 1])
--            if callback: callback(i)
--            if img_callback: img_callback(x, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x, i)
-             d = to_d(x, sigmas[i], denoised)
-             # Midpoint method, where the midpoint is chosen according to a rho=3 Karras schedule
-             sigma_mid = ((sigmas[i] ** (1 / 3) + sigma_down ** (1 / 3)) / 2) ** 3
-@@ -1016,7 +1016,7 @@ class UNet(DDPM):
-             d_2 = to_d(x_2, sigma_mid, denoised_2)
-             x = x + d_2 * dt_2
-             x = x + torch.randn_like(x) * sigma_up
--        return x
-+        yield from img_callback(x, len(sigmas)-1)
- 
- 
-     @torch.no_grad()
-@@ -1042,8 +1042,8 @@ class UNet(DDPM):
-             e_t_uncond, e_t = (x_in  + eps * c_out).chunk(2)
-             denoised = e_t_uncond + unconditional_guidance_scale * (e_t - e_t_uncond)
- 
--            if callback: callback(i)
--            if img_callback: img_callback(x, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(x, i)
- 
-             d = to_d(x, sigmas[i], denoised)
-             ds.append(d)
-@@ -1054,4 +1054,4 @@ class UNet(DDPM):
-             cur_order = min(i + 1, order)
-             coeffs = [linear_multistep_coeff(cur_order, sigmas.cpu(), i, j) for j in range(cur_order)]
-             x = x + sum(coeff * d for coeff, d in zip(coeffs, reversed(ds)))
--        return x
-+        yield from img_callback(x, len(sigmas)-1)
diff --git a/ui/sd_internal/ddim_callback_sd2.patch b/ui/sd_internal/ddim_callback_sd2.patch
deleted file mode 100644
index cadf81ca..00000000
--- a/ui/sd_internal/ddim_callback_sd2.patch
+++ /dev/null
@@ -1,84 +0,0 @@
-diff --git a/ldm/models/diffusion/ddim.py b/ldm/models/diffusion/ddim.py
-index 27ead0e..6215939 100644
---- a/ldm/models/diffusion/ddim.py
-+++ b/ldm/models/diffusion/ddim.py
-@@ -100,7 +100,7 @@ class DDIMSampler(object):
-         size = (batch_size, C, H, W)
-         print(f'Data shape for DDIM sampling is {size}, eta {eta}')
- 
--        samples, intermediates = self.ddim_sampling(conditioning, size,
-+        samples = self.ddim_sampling(conditioning, size,
-                                                     callback=callback,
-                                                     img_callback=img_callback,
-                                                     quantize_denoised=quantize_x0,
-@@ -117,7 +117,8 @@ class DDIMSampler(object):
-                                                     dynamic_threshold=dynamic_threshold,
-                                                     ucg_schedule=ucg_schedule
-                                                     )
--        return samples, intermediates
-+        # return samples, intermediates
-+        yield from samples
- 
-     @torch.no_grad()
-     def ddim_sampling(self, cond, shape,
-@@ -168,14 +169,15 @@ class DDIMSampler(object):
-                                       unconditional_conditioning=unconditional_conditioning,
-                                       dynamic_threshold=dynamic_threshold)
-             img, pred_x0 = outs
--            if callback: callback(i)
--            if img_callback: img_callback(pred_x0, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(pred_x0, i)
- 
-             if index % log_every_t == 0 or index == total_steps - 1:
-                 intermediates['x_inter'].append(img)
-                 intermediates['pred_x0'].append(pred_x0)
- 
--        return img, intermediates
-+        # return img, intermediates
-+        yield from img_callback(pred_x0, len(iterator)-1)
- 
-     @torch.no_grad()
-     def p_sample_ddim(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,
-diff --git a/ldm/models/diffusion/plms.py b/ldm/models/diffusion/plms.py
-index 7002a36..0951f39 100644
---- a/ldm/models/diffusion/plms.py
-+++ b/ldm/models/diffusion/plms.py
-@@ -96,7 +96,7 @@ class PLMSSampler(object):
-         size = (batch_size, C, H, W)
-         print(f'Data shape for PLMS sampling is {size}')
- 
--        samples, intermediates = self.plms_sampling(conditioning, size,
-+        samples = self.plms_sampling(conditioning, size,
-                                                     callback=callback,
-                                                     img_callback=img_callback,
-                                                     quantize_denoised=quantize_x0,
-@@ -112,7 +112,8 @@ class PLMSSampler(object):
-                                                     unconditional_conditioning=unconditional_conditioning,
-                                                     dynamic_threshold=dynamic_threshold,
-                                                     )
--        return samples, intermediates
-+        #return samples, intermediates
-+        yield from samples
- 
-     @torch.no_grad()
-     def plms_sampling(self, cond, shape,
-@@ -165,14 +166,15 @@ class PLMSSampler(object):
-             old_eps.append(e_t)
-             if len(old_eps) >= 4:
-                 old_eps.pop(0)
--            if callback: callback(i)
--            if img_callback: img_callback(pred_x0, i)
-+            if callback: yield from callback(i)
-+            if img_callback: yield from img_callback(pred_x0, i)
- 
-             if index % log_every_t == 0 or index == total_steps - 1:
-                 intermediates['x_inter'].append(img)
-                 intermediates['pred_x0'].append(pred_x0)
- 
--        return img, intermediates
-+        # return img, intermediates
-+        yield from img_callback(pred_x0, len(iterator)-1)
- 
-     @torch.no_grad()
-     def p_sample_plms(self, x, c, t, index, repeat_noise=False, use_original_steps=False, quantize_denoised=False,

From b40fb3a422472fc0fb4e2d68edf9876e8bd881dc Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 9 Dec 2022 15:27:40 +0530
Subject: [PATCH 08/74] Model readme file write flag

---
 ui/sd_internal/model_manager.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index 21acb540..c7d22e1d 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -96,7 +96,7 @@ def make_model_folders():
         help_file_name = f'Place your {model_type} model files here.txt'
         help_file_contents = f'Supported extensions: {" or ".join(MODEL_EXTENSIONS.get(model_type))}'
 
-        with open(os.path.join(model_dir_path, help_file_name)) as f:
+        with open(os.path.join(model_dir_path, help_file_name), 'w', encoding='utf-8') as f:
             f.write(help_file_contents)
 
 def is_malicious_model(file_path):

From 882081400251184f70658af06d1b8dee75364535 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 9 Dec 2022 15:45:36 +0530
Subject: [PATCH 09/74] Simplify the API for resolving model paths; Code
 cleanup

---
 ui/sd_internal/model_manager.py | 17 +----------------
 ui/sd_internal/runtime2.py      | 17 ++++++-----------
 ui/sd_internal/task_manager.py  |  4 ++--
 ui/server.py                    |  6 +++---
 4 files changed, 12 insertions(+), 32 deletions(-)

diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index c7d22e1d..6cf9428a 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -28,7 +28,7 @@ def init():
     make_model_folders()
     getModels() # run this once, to cache the picklescan results
 
-def resolve_model_to_use(model_name:str, model_type:str):
+def resolve_model_to_use(model_name:str=None, model_type:str=None):
     model_extensions = MODEL_EXTENSIONS.get(model_type, [])
     default_models = DEFAULT_MODELS.get(model_type, [])
     config = app.getConfig()
@@ -72,21 +72,6 @@ def resolve_model_to_use(model_name:str, model_type:str):
 
     return None
 
-def resolve_sd_model_to_use(model_name:str=None):
-    return resolve_model_to_use(model_name, model_type='stable-diffusion')
-
-def resolve_vae_model_to_use(model_name:str=None):
-    return resolve_model_to_use(model_name, model_type='vae')
-
-def resolve_hypernetwork_model_to_use(model_name:str=None):
-    return resolve_model_to_use(model_name, model_type='hypernetwork')
-
-def resolve_gfpgan_model_to_use(model_name:str=None):
-    return resolve_model_to_use(model_name, model_type='gfpgan')
-
-def resolve_realesrgan_model_to_use(model_name:str=None):
-    return resolve_model_to_use(model_name, model_type='realesrgan')
-
 def make_model_folders():
     for model_type in KNOWN_MODEL_TYPES:
         model_dir_path = os.path.join(app.MODELS_DIR, model_type)
diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index 0af0ead4..3d4ff8ff 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -39,18 +39,13 @@ def init(device):
     init_and_load_default_models()
 
 def destroy():
-    model_loader.unload_model(thread_data, 'stable-diffusion')
-    model_loader.unload_model(thread_data, 'gfpgan')
-    model_loader.unload_model(thread_data, 'realesrgan')
-    model_loader.unload_model(thread_data, 'hypernetwork')
+    for model_type in ('stable-diffusion', 'hypernetwork', 'gfpgan', 'realesrgan'):
+        model_loader.unload_model(thread_data, model_type)
 
 def init_and_load_default_models():
     # init default model paths
-    thread_data.model_paths['stable-diffusion'] = model_manager.resolve_sd_model_to_use()
-    thread_data.model_paths['vae'] = model_manager.resolve_vae_model_to_use()
-    thread_data.model_paths['hypernetwork'] = model_manager.resolve_hypernetwork_model_to_use()
-    thread_data.model_paths['gfpgan'] = model_manager.resolve_gfpgan_model_to_use()
-    thread_data.model_paths['realesrgan'] = model_manager.resolve_realesrgan_model_to_use()
+    for model_type in ('stable-diffusion', 'vae', 'hypernetwork', 'gfpgan', 'realesrgan'):
+        thread_data.model_paths[model_type] = model_manager.resolve_model_to_use(model_type=model_type)
 
     # load mandatory models
     model_loader.load_model(thread_data, 'stable-diffusion')
@@ -119,8 +114,8 @@ def apply_filters(req: Request, images: list, user_stopped):
         return images
 
     filters = []
-    if req.use_face_correction.startswith('GFPGAN'): filters.append((image_filters.apply_gfpgan, model_manager.resolve_gfpgan_model_to_use(req.use_face_correction)))
-    if req.use_upscale.startswith('RealESRGAN'): filters.append((image_filters.apply_realesrgan, model_manager.resolve_realesrgan_model_to_use(req.use_upscale)))
+    if req.use_face_correction.startswith('GFPGAN'): filters.append((image_filters.apply_gfpgan, model_manager.resolve_model_to_use(req.use_face_correction, model_type='gfpgan')))
+    if req.use_upscale.startswith('RealESRGAN'): filters.append((image_filters.apply_realesrgan, model_manager.resolve_model_to_use(req.use_upscale, model_type='realesrgan')))
 
     filtered_images = []
     for img, seed, _ in images:
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index c6ab9737..aec79239 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -11,10 +11,10 @@ TASK_TTL = 15 * 60 # seconds, Discard last session's task timeout
 
 import torch
 import queue, threading, time, weakref
-from typing import Any, Generator, Hashable, Optional, Union
+from typing import Any, Hashable
 
 from pydantic import BaseModel
-from sd_internal import Request, Response, runtime, device_manager
+from sd_internal import Request, device_manager
 
 THREAD_NAME_PREFIX = 'Runtime-Render/'
 ERR_LOCK_FAILED = ' failed to acquire lock within timeout.'
diff --git a/ui/server.py b/ui/server.py
index b3c54342..ca5cac79 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -136,9 +136,9 @@ def ping(session_id:str=None):
 def render(req : task_manager.ImageRequest):
     try:
         app.save_model_to_config(req.use_stable_diffusion_model, req.use_vae_model, req.use_hypernetwork_model)
-        req.use_stable_diffusion_model = model_manager.resolve_sd_model_to_use(req.use_stable_diffusion_model)
-        req.use_vae_model = model_manager.resolve_vae_model_to_use(req.use_vae_model)
-        req.use_hypernetwork_model = model_manager.resolve_hypernetwork_model_to_use(req.use_hypernetwork_model)
+        req.use_stable_diffusion_model = model_manager.resolve_model_to_use(req.use_stable_diffusion_model, model_type='stable-diffusion')
+        req.use_vae_model = model_manager.resolve_model_to_use(req.use_vae_model, model_type='vae')
+        req.use_hypernetwork_model = model_manager.resolve_model_to_use(req.use_hypernetwork_model, model_type='hypernetwork')
 
         new_task = task_manager.render(req)
         response = {

From 3fbb3f677384f002ecbd1b8501ef081de59fcb42 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 9 Dec 2022 16:09:10 +0530
Subject: [PATCH 10/74] Use const

---
 ui/sd_internal/runtime2.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index 3d4ff8ff..57dd7150 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -44,7 +44,7 @@ def destroy():
 
 def init_and_load_default_models():
     # init default model paths
-    for model_type in ('stable-diffusion', 'vae', 'hypernetwork', 'gfpgan', 'realesrgan'):
+    for model_type in model_manager.KNOWN_MODEL_TYPES:
         thread_data.model_paths[model_type] = model_manager.resolve_model_to_use(model_type=model_type)
 
     # load mandatory models

From 0f656dbf2fae7262ba9996303864675ebe2d1335 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 9 Dec 2022 16:11:08 +0530
Subject: [PATCH 11/74] Typo

---
 ui/server.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ui/server.py b/ui/server.py
index ca5cac79..458bc1aa 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -53,7 +53,7 @@ logging.getLogger('uvicorn.access').addFilter(LogSuppressFilter())
 server_api.mount('/media', NoCacheStaticFiles(directory=os.path.join(app.SD_UI_DIR, 'media')), name="media")
 
 for plugins_dir, dir_prefix in app.UI_PLUGINS_SOURCES:
-    app.mount(f'/plugins/{dir_prefix}', NoCacheStaticFiles(directory=plugins_dir), name=f"plugins-{dir_prefix}")
+    server_api.mount(f'/plugins/{dir_prefix}', NoCacheStaticFiles(directory=plugins_dir), name=f"plugins-{dir_prefix}")
 
 @server_api.post('/app_config')
 async def setAppConfig(req : SetAppConfigRequest):

From dbac2655f53961bb81bf57eab345e4070c9e934d Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 9 Dec 2022 16:14:04 +0530
Subject: [PATCH 12/74] Typo

---
 ui/sd_internal/runtime2.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index 57dd7150..080180a4 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -10,7 +10,7 @@ import traceback
 from sd_internal import device_manager, model_manager
 from sd_internal import Request, Response, Image as ResponseImage, UserInitiatedStop
 
-from modules import model_loader, image_generator, image_utils, image_filters
+from modules import model_loader, image_generator, image_utils, filters as image_filters
 
 thread_data = threading.local()
 '''

From f1de0be679cb84e7d7e804b65652a26d73b6c8f6 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 9 Dec 2022 17:50:33 +0530
Subject: [PATCH 13/74] Fix integration issues after the refactor

---
 scripts/on_sd_start.bat          | 2 +-
 scripts/on_sd_start.sh           | 2 +-
 ui/sd_internal/device_manager.py | 2 +-
 ui/sd_internal/runtime2.py       | 9 +++++++--
 4 files changed, 10 insertions(+), 5 deletions(-)

diff --git a/scripts/on_sd_start.bat b/scripts/on_sd_start.bat
index d8981226..9bac3757 100644
--- a/scripts/on_sd_start.bat
+++ b/scripts/on_sd_start.bat
@@ -393,7 +393,7 @@ call python --version
 
 @if NOT DEFINED SD_UI_BIND_PORT set SD_UI_BIND_PORT=9000
 @if NOT DEFINED SD_UI_BIND_IP set SD_UI_BIND_IP=0.0.0.0
-@uvicorn server:app --app-dir "%SD_UI_PATH%" --port %SD_UI_BIND_PORT% --host %SD_UI_BIND_IP%
+@uvicorn server:server_api --app-dir "%SD_UI_PATH%" --port %SD_UI_BIND_PORT% --host %SD_UI_BIND_IP%
 
 
 @pause
diff --git a/scripts/on_sd_start.sh b/scripts/on_sd_start.sh
index 3e1c9c58..afb95295 100755
--- a/scripts/on_sd_start.sh
+++ b/scripts/on_sd_start.sh
@@ -322,6 +322,6 @@ cd ..
 export SD_UI_PATH=`pwd`/ui
 cd stable-diffusion
 
-uvicorn server:app --app-dir "$SD_UI_PATH" --port ${SD_UI_BIND_PORT:-9000} --host ${SD_UI_BIND_IP:-0.0.0.0}
+uvicorn server:server_api --app-dir "$SD_UI_PATH" --port ${SD_UI_BIND_PORT:-9000} --host ${SD_UI_BIND_IP:-0.0.0.0}
 
 read -p "Press any key to continue"
diff --git a/ui/sd_internal/device_manager.py b/ui/sd_internal/device_manager.py
index 4de6b265..c490a0c6 100644
--- a/ui/sd_internal/device_manager.py
+++ b/ui/sd_internal/device_manager.py
@@ -101,7 +101,7 @@ def device_init(context, device):
     context.device = device
 
     # Force full precision on 1660 and 1650 NVIDIA cards to avoid creating green images
-    if needs_to_force_full_precision(context.device_name):
+    if needs_to_force_full_precision(context):
         print(f'forcing full precision on this GPU, to avoid green images. GPU detected: {context.device_name}')
         # Apply force_full_precision now before models are loaded.
         context.precision = 'full'
diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index 080180a4..0fcf8eb7 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -83,7 +83,12 @@ def _make_images_internal(req: Request, data_queue: queue.Queue, task_temp_image
 
     save_images(req, images)
 
-    return Response(req, images=construct_response(req, images))
+    res = Response(req, images=construct_response(req, images))
+    res = res.json()
+    data_queue.put(json.dumps(res))
+    print('Task completed')
+
+    return res
 
 def generate_images(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
     thread_data.temp_images.clear()
@@ -91,7 +96,7 @@ def generate_images(req: Request, data_queue: queue.Queue, task_temp_images: lis
     image_generator.on_image_step = make_step_callback(req, data_queue, task_temp_images, step_callback)
 
     try:
-        images = image_generator.make_image(context=thread_data, args=get_mk_img_args(req))
+        images = image_generator.make_images(context=thread_data, args=get_mk_img_args(req))
         user_stopped = False
     except UserInitiatedStop:
         images = []

From 79cc84b6117e4885e525821bc3eb078c3013f30c Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 9 Dec 2022 19:39:56 +0530
Subject: [PATCH 14/74] Option to apply color correction (balances the
 histogram) during inpainting; Refactor the runtime to use a general-purpose
 dict

---
 ui/index.html                  |  1 +
 ui/media/js/auto-save.js       |  3 +-
 ui/media/js/main.js            |  8 ++++
 ui/sd_internal/__init__.py     |  4 ++
 ui/sd_internal/runtime2.py     | 83 ++++++++++++++++++++--------------
 ui/sd_internal/task_manager.py |  2 +
 6 files changed, 66 insertions(+), 35 deletions(-)

diff --git a/ui/index.html b/ui/index.html
index 0094201b..30648424 100644
--- a/ui/index.html
+++ b/ui/index.html
@@ -213,6 +213,7 @@
                     <div><ul>
                     <li><b class="settings-subheader">Render Settings</b></li>
                     <li class="pl-5"><input id="stream_image_progress" name="stream_image_progress" type="checkbox"> <label for="stream_image_progress">Show a live preview <small>(uses more VRAM, slower images)</small></label></li>
+                    <li id="apply_color_correction_setting" class="pl-5"><input id="apply_color_correction" name="apply_color_correction" type="checkbox"> <label for="apply_color_correction">Apply color correction <small>(helps during inpainting)</small></label></li>
                     <li class="pl-5"><input id="use_face_correction" name="use_face_correction" type="checkbox"> <label for="use_face_correction">Fix incorrect faces and eyes <small>(uses GFPGAN)</small></label></li>
                     <li class="pl-5">
                         <input id="use_upscale" name="use_upscale" type="checkbox"> <label for="use_upscale">Upscale image by 4x with </label>
diff --git a/ui/media/js/auto-save.js b/ui/media/js/auto-save.js
index f503779a..9025f988 100644
--- a/ui/media/js/auto-save.js
+++ b/ui/media/js/auto-save.js
@@ -39,7 +39,8 @@ const SETTINGS_IDS_LIST = [
     "turbo",
     "use_full_precision",
     "confirm_dangerous_actions",
-    "auto_save_settings"
+    "auto_save_settings",
+    "apply_color_correction"
 ]
 
 const IGNORE_BY_DEFAULT = [
diff --git a/ui/media/js/main.js b/ui/media/js/main.js
index 67ff7a9a..6c08aef7 100644
--- a/ui/media/js/main.js
+++ b/ui/media/js/main.js
@@ -26,6 +26,8 @@ let initImagePreview = document.querySelector("#init_image_preview")
 let initImageSizeBox = document.querySelector("#init_image_size_box")
 let maskImageSelector = document.querySelector("#mask")
 let maskImagePreview = document.querySelector("#mask_preview")
+let applyColorCorrectionField = document.querySelector('#apply_color_correction')
+let colorCorrectionSetting = document.querySelector('#apply_color_correction_setting')
 let promptStrengthSlider = document.querySelector('#prompt_strength_slider')
 let promptStrengthField = document.querySelector('#prompt_strength')
 let samplerField = document.querySelector('#sampler')
@@ -759,6 +761,9 @@ function createTask(task) {
         taskConfig += `, <b>Hypernetwork:</b> ${task.reqBody.use_hypernetwork_model}`
         taskConfig += `, <b>Hypernetwork Strength:</b> ${task.reqBody.hypernetwork_strength}`
     }
+    if (task.reqBody.apply_color_correction) {
+        taskConfig += `, <b>Color Correction:</b> true`
+    }
 
     let taskEntry = document.createElement('div')
     taskEntry.id = `imageTaskContainer-${Date.now()}`
@@ -867,6 +872,7 @@ function getCurrentUserRequest() {
         if (maskSetting.checked) {
             newTask.reqBody.mask = imageInpainter.getImg()
         }
+        newTask.reqBody.apply_color_correction = applyColorCorrectionField.checked
         newTask.reqBody.sampler = 'ddim'
     } else {
         newTask.reqBody.sampler = samplerField.value
@@ -1257,6 +1263,7 @@ function img2imgLoad() {
     promptStrengthContainer.style.display = 'table-row'
     samplerSelectionContainer.style.display = "none"
     initImagePreviewContainer.classList.add("has-image")
+    colorCorrectionSetting.style.display = ''
 
     initImageSizeBox.textContent = initImagePreview.naturalWidth + " x " + initImagePreview.naturalHeight
     imageEditor.setImage(this.src, initImagePreview.naturalWidth, initImagePreview.naturalHeight)
@@ -1271,6 +1278,7 @@ function img2imgUnload() {
     promptStrengthContainer.style.display = "none"
     samplerSelectionContainer.style.display = ""
     initImagePreviewContainer.classList.remove("has-image")
+    colorCorrectionSetting.style.display = 'none'
     imageEditor.setImage(null, parseInt(widthField.value), parseInt(heightField.value))
 
 }
diff --git a/ui/sd_internal/__init__.py b/ui/sd_internal/__init__.py
index b001d3f9..9dd4f066 100644
--- a/ui/sd_internal/__init__.py
+++ b/ui/sd_internal/__init__.py
@@ -7,6 +7,7 @@ class Request:
     negative_prompt: str = ""
     init_image: str = None # base64
     mask: str = None # base64
+    apply_color_correction = False
     num_outputs: int = 1
     num_inference_steps: int = 50
     guidance_scale: float = 7.5
@@ -35,6 +36,7 @@ class Request:
 
     def json(self):
         return {
+            "request_id": self.request_id,
             "session_id": self.session_id,
             "prompt": self.prompt,
             "negative_prompt": self.negative_prompt,
@@ -46,6 +48,7 @@ class Request:
             "seed": self.seed,
             "prompt_strength": self.prompt_strength,
             "sampler": self.sampler,
+            "apply_color_correction": self.apply_color_correction,
             "use_face_correction": self.use_face_correction,
             "use_upscale": self.use_upscale,
             "use_stable_diffusion_model": self.use_stable_diffusion_model,
@@ -71,6 +74,7 @@ class Request:
     save_to_disk_path: {self.save_to_disk_path}
     turbo: {self.turbo}
     use_full_precision: {self.use_full_precision}
+    apply_color_correction: {self.apply_color_correction}
     use_face_correction: {self.use_face_correction}
     use_upscale: {self.use_upscale}
     use_stable_diffusion_model: {self.use_stable_diffusion_model}
diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index 0fcf8eb7..f74acc12 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -78,10 +78,15 @@ def make_images(req: Request, data_queue: queue.Queue, task_temp_images: list, s
         raise e
 
 def _make_images_internal(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
-    images, user_stopped = generate_images(req, data_queue, task_temp_images, step_callback)
-    images = apply_filters(req, images, user_stopped)
+    args = req_to_args(req)
 
-    save_images(req, images)
+    images, user_stopped = generate_images(args, data_queue, task_temp_images, step_callback, req.stream_image_progress)
+    images = apply_color_correction(args, images, user_stopped)
+    images = apply_filters(args, images, user_stopped, req.show_only_filtered_image)
+
+    if req.save_to_disk_path is not None:
+        out_path = os.path.join(req.save_to_disk_path, filename_regex.sub('_', req.session_id))
+        save_images(images, out_path, metadata=req.json(), show_only_filtered_image=req.show_only_filtered_image)
 
     res = Response(req, images=construct_response(req, images))
     res = res.json()
@@ -90,37 +95,48 @@ def _make_images_internal(req: Request, data_queue: queue.Queue, task_temp_image
 
     return res
 
-def generate_images(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
+def generate_images(args: dict, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
     thread_data.temp_images.clear()
 
-    image_generator.on_image_step = make_step_callback(req, data_queue, task_temp_images, step_callback)
+    image_generator.on_image_step = make_step_callback(args, data_queue, task_temp_images, step_callback, stream_image_progress)
 
     try:
-        images = image_generator.make_images(context=thread_data, args=get_mk_img_args(req))
+        images = image_generator.make_images(context=thread_data, args=args)
         user_stopped = False
     except UserInitiatedStop:
         images = []
         user_stopped = True
         if not hasattr(thread_data, 'partial_x_samples') or thread_data.partial_x_samples is None:
             return images
-        for i in range(req.num_outputs):
+        for i in range(args['num_outputs']):
             images[i] = image_utils.latent_to_img(thread_data, thread_data.partial_x_samples[i].unsqueeze(0))
         
         del thread_data.partial_x_samples
     finally:
         model_loader.gc(thread_data)
     
-    images = [(image, req.seed + i, False) for i, image in enumerate(images)]
+    images = [(image, args['seed'] + i, False) for i, image in enumerate(images)]
 
     return images, user_stopped
 
-def apply_filters(req: Request, images: list, user_stopped):
-    if user_stopped or (req.use_face_correction is None and req.use_upscale is None):
+def apply_color_correction(args: dict, images: list, user_stopped):
+    if user_stopped or args['init_image'] is None or not args['apply_color_correction']:
+        return images
+
+    for i, img_info in enumerate(images):
+        img, seed, filtered = img_info
+        img = image_utils.apply_color_correction(orig_image=args['init_image'], image_to_correct=img)
+        images[i] = (img, seed, filtered)
+
+    return images
+
+def apply_filters(args: dict, images: list, user_stopped, show_only_filtered_image):
+    if user_stopped or (args['use_face_correction'] is None and args['use_upscale'] is None):
         return images
 
     filters = []
-    if req.use_face_correction.startswith('GFPGAN'): filters.append((image_filters.apply_gfpgan, model_manager.resolve_model_to_use(req.use_face_correction, model_type='gfpgan')))
-    if req.use_upscale.startswith('RealESRGAN'): filters.append((image_filters.apply_realesrgan, model_manager.resolve_model_to_use(req.use_upscale, model_type='realesrgan')))
+    if args['use_face_correction'].startswith('GFPGAN'): filters.append((image_filters.apply_gfpgan, model_manager.resolve_model_to_use(args['use_face_correction'], model_type='gfpgan')))
+    if args['use_face_correction'].use_upscale.startswith('RealESRGAN'): filters.append((image_filters.apply_realesrgan, model_manager.resolve_model_to_use(args['use_upscale'], model_type='realesrgan')))
 
     filtered_images = []
     for img, seed, _ in images:
@@ -129,13 +145,13 @@ def apply_filters(req: Request, images: list, user_stopped):
 
         filtered_images.append((img, seed, True))
 
-    if not req.show_only_filtered_image:
+    if not show_only_filtered_image:
         filtered_images = images + filtered_images
 
     return filtered_images
 
-def save_images(req: Request, images: list):
-    if req.save_to_disk_path is None:
+def save_images(images: list, save_to_disk_path, metadata: dict, show_only_filtered_image):
+    if save_to_disk_path is None:
         return
 
     def get_image_id(i):
@@ -144,25 +160,24 @@ def save_images(req: Request, images: list):
         return img_id
 
     def get_image_basepath(i):
-        session_out_path = os.path.join(req.save_to_disk_path, filename_regex.sub('_', req.session_id))
-        os.makedirs(session_out_path, exist_ok=True)
-        prompt_flattened = filename_regex.sub('_', req.prompt)[:50]
-        return os.path.join(session_out_path, f"{prompt_flattened}_{get_image_id(i)}")
+        os.makedirs(save_to_disk_path, exist_ok=True)
+        prompt_flattened = filename_regex.sub('_', metadata['prompt'])[:50]
+        return os.path.join(save_to_disk_path, f"{prompt_flattened}_{get_image_id(i)}")
 
     for i, img_data in enumerate(images):
         img, seed, filtered = img_data
         img_path = get_image_basepath(i)
 
-        if not filtered or req.show_only_filtered_image:
+        if not filtered or show_only_filtered_image:
             img_metadata_path = img_path + '.txt'
-            metadata = req.json()
-            metadata['seed'] = seed
+            m = metadata.copy()
+            m['seed'] = seed
             with open(img_metadata_path, 'w', encoding='utf-8') as f:
-                f.write(metadata)
+                f.write(m)
 
         img_path += '_filtered' if filtered else ''
-        img_path += '.' + req.output_format
-        img.save(img_path, quality=req.output_quality)
+        img_path += '.' + metadata['output_format']
+        img.save(img_path, quality=metadata['output_quality'])
 
 def construct_response(req: Request, images: list):
     return [
@@ -172,7 +187,7 @@ def construct_response(req: Request, images: list):
         ) for img, seed, _ in images
     ]
 
-def get_mk_img_args(req: Request):
+def req_to_args(req: Request):
     args = req.json()
 
     args['init_image'] = image_utils.base64_str_to_img(req.init_image) if req.init_image is not None else None
@@ -180,21 +195,21 @@ def get_mk_img_args(req: Request):
 
     return args
 
-def make_step_callback(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
-    n_steps = req.num_inference_steps if req.init_image is None else int(req.num_inference_steps * req.prompt_strength)
+def make_step_callback(args: dict, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
+    n_steps = args['num_inference_steps'] if args['init_image'] is None else int(args['num_inference_steps'] * args['prompt_strength'])
     last_callback_time = -1
 
-    def update_temp_img(req, x_samples, task_temp_images: list):
+    def update_temp_img(x_samples, task_temp_images: list):
         partial_images = []
-        for i in range(req.num_outputs):
+        for i in range(args['num_outputs']):
             img = image_utils.latent_to_img(thread_data, x_samples[i].unsqueeze(0))
             buf = image_utils.img_to_buffer(img, output_format='JPEG')
 
             del img
 
-            thread_data.temp_images[f'{req.request_id}/{i}'] = buf
+            thread_data.temp_images[f"{args['request_id']}/{i}"] = buf
             task_temp_images[i] = buf
-            partial_images.append({'path': f'/image/tmp/{req.request_id}/{i}'})
+            partial_images.append({'path': f"/image/tmp/{args['request_id']}/{i}"})
         return partial_images
 
     def on_image_step(x_samples, i):
@@ -206,8 +221,8 @@ def make_step_callback(req: Request, data_queue: queue.Queue, task_temp_images:
 
         progress = {"step": i, "step_time": step_time, "total_steps": n_steps}
 
-        if req.stream_image_progress and i % 5 == 0:
-            progress['output'] = update_temp_img(req, x_samples, task_temp_images)
+        if stream_image_progress and i % 5 == 0:
+            progress['output'] = update_temp_img(x_samples, task_temp_images)
 
         data_queue.put(json.dumps(progress))
 
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index aec79239..6b0a1d8c 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -76,6 +76,7 @@ class ImageRequest(BaseModel):
     negative_prompt: str = ""
     init_image: str = None # base64
     mask: str = None # base64
+    apply_color_correction: bool = False
     num_outputs: int = 1
     num_inference_steps: int = 50
     guidance_scale: float = 7.5
@@ -522,6 +523,7 @@ def render(req : ImageRequest):
     r.negative_prompt = req.negative_prompt
     r.init_image = req.init_image
     r.mask = req.mask
+    r.apply_color_correction = req.apply_color_correction
     r.num_outputs = req.num_outputs
     r.num_inference_steps = req.num_inference_steps
     r.guidance_scale = req.guidance_scale

From cde8c2d3bd3f307d2c19a3fcdda689b9ab2e26b9 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 9 Dec 2022 21:30:18 +0530
Subject: [PATCH 15/74] Use a logger

---
 ui/sd_internal/app.py            | 23 +++++++++----
 ui/sd_internal/device_manager.py | 23 +++++++------
 ui/sd_internal/model_manager.py  | 23 +++++++++----
 ui/sd_internal/runtime2.py       |  7 ++--
 ui/sd_internal/task_manager.py   | 56 +++++++++++++++++---------------
 ui/server.py                     | 13 ++++----
 6 files changed, 87 insertions(+), 58 deletions(-)

diff --git a/ui/sd_internal/app.py b/ui/sd_internal/app.py
index d1cec46f..c34f2ea6 100644
--- a/ui/sd_internal/app.py
+++ b/ui/sd_internal/app.py
@@ -3,9 +3,21 @@ import socket
 import sys
 import json
 import traceback
+import logging
+from rich.logging import RichHandler
 
 from sd_internal import task_manager
 
+LOG_FORMAT = '[%(threadName)s] %(message)s'
+logging.basicConfig(
+        level=logging.INFO,
+        format=LOG_FORMAT,
+        datefmt="[%X.%f]",
+        handlers=[RichHandler(markup=True)]
+)
+
+log = logging.getLogger()
+
 SD_DIR = os.getcwd()
 
 SD_UI_DIR = os.getenv('SD_UI_PATH', None)
@@ -49,8 +61,7 @@ def getConfig(default_val=APP_CONFIG_DEFAULTS):
                 config['net']['listen_to_network'] = (os.getenv('SD_UI_BIND_IP') == '0.0.0.0')
             return config
     except Exception as e:
-        print(str(e))
-        print(traceback.format_exc())
+        log.warn(traceback.format_exc())
         return default_val
 
 def setConfig(config):
@@ -59,7 +70,7 @@ def setConfig(config):
         with open(config_json_path, 'w', encoding='utf-8') as f:
             json.dump(config, f)
     except:
-        print(traceback.format_exc())
+        log.error(traceback.format_exc())
 
     try: # config.bat
         config_bat_path = os.path.join(CONFIG_DIR, 'config.bat')
@@ -78,7 +89,7 @@ def setConfig(config):
             with open(config_bat_path, 'w', encoding='utf-8') as f:
                 f.write('\r\n'.join(config_bat))
     except:
-        print(traceback.format_exc())
+        log.error(traceback.format_exc())
 
     try: # config.sh
         config_sh_path = os.path.join(CONFIG_DIR, 'config.sh')
@@ -97,7 +108,7 @@ def setConfig(config):
             with open(config_sh_path, 'w', encoding='utf-8') as f:
                 f.write('\n'.join(config_sh))
     except:
-        print(traceback.format_exc())
+        log.error(traceback.format_exc())
 
 def save_model_to_config(ckpt_model_name, vae_model_name, hypernetwork_model_name):
     config = getConfig()
@@ -120,7 +131,7 @@ def update_render_threads():
     render_devices = config.get('render_devices', 'auto')
     active_devices = task_manager.get_devices()['active'].keys()
 
-    print('requesting for render_devices', render_devices)
+    log.debug(f'requesting for render_devices: {render_devices}')
     task_manager.update_render_threads(render_devices, active_devices)
 
 def getUIPlugins():
diff --git a/ui/sd_internal/device_manager.py b/ui/sd_internal/device_manager.py
index c490a0c6..a3f91cfb 100644
--- a/ui/sd_internal/device_manager.py
+++ b/ui/sd_internal/device_manager.py
@@ -2,6 +2,9 @@ import os
 import torch
 import traceback
 import re
+import logging
+
+log = logging.getLogger()
 
 COMPARABLE_GPU_PERCENTILE = 0.65 # if a GPU's free_mem is within this % of the GPU with the most free_mem, it will be picked
 
@@ -34,7 +37,7 @@ def get_device_delta(render_devices, active_devices):
     if 'auto' in render_devices:
         render_devices = auto_pick_devices(active_devices)
         if 'cpu' in render_devices:
-            print('WARNING: Could not find a compatible GPU. Using the CPU, but this will be very slow!')
+            log.warn('WARNING: Could not find a compatible GPU. Using the CPU, but this will be very slow!')
 
     active_devices = set(active_devices)
     render_devices = set(render_devices)
@@ -53,7 +56,7 @@ def auto_pick_devices(currently_active_devices):
     if device_count == 1:
         return ['cuda:0'] if is_device_compatible('cuda:0') else ['cpu']
 
-    print('Autoselecting GPU. Using most free memory.')
+    log.debug('Autoselecting GPU. Using most free memory.')
     devices = []
     for device in range(device_count):
         device = f'cuda:{device}'
@@ -64,7 +67,7 @@ def auto_pick_devices(currently_active_devices):
         mem_free /= float(10**9)
         mem_total /= float(10**9)
         device_name = torch.cuda.get_device_name(device)
-        print(f'{device} detected: {device_name} - Memory (free/total): {round(mem_free, 2)}Gb / {round(mem_total, 2)}Gb')
+        log.debug(f'{device} detected: {device_name} - Memory (free/total): {round(mem_free, 2)}Gb / {round(mem_total, 2)}Gb')
         devices.append({'device': device, 'device_name': device_name, 'mem_free': mem_free})
 
     devices.sort(key=lambda x:x['mem_free'], reverse=True)
@@ -94,7 +97,7 @@ def device_init(context, device):
         context.device = 'cpu'
         context.device_name = get_processor_name()
         context.precision = 'full'
-        print('Render device CPU available as', context.device_name)
+        log.debug(f'Render device CPU available as {context.device_name}')
         return
 
     context.device_name = torch.cuda.get_device_name(device)
@@ -102,11 +105,11 @@ def device_init(context, device):
 
     # Force full precision on 1660 and 1650 NVIDIA cards to avoid creating green images
     if needs_to_force_full_precision(context):
-        print(f'forcing full precision on this GPU, to avoid green images. GPU detected: {context.device_name}')
+        log.warn(f'forcing full precision on this GPU, to avoid green images. GPU detected: {context.device_name}')
         # Apply force_full_precision now before models are loaded.
         context.precision = 'full'
 
-    print(f'Setting {device} as active')
+    log.info(f'Setting {device} as active')
     torch.cuda.device(device)
 
     return
@@ -135,7 +138,7 @@ def is_device_compatible(device):
     try:
         validate_device_id(device, log_prefix='is_device_compatible')
     except:
-        print(str(e))
+        log.error(str(e))
         return False
 
     if device == 'cpu': return True
@@ -144,10 +147,10 @@ def is_device_compatible(device):
         _, mem_total = torch.cuda.mem_get_info(device)
         mem_total /= float(10**9)
         if mem_total < 3.0:
-            print(f'GPU {device} with less than 3 GB of VRAM is not compatible with Stable Diffusion')
+            log.warn(f'GPU {device} with less than 3 GB of VRAM is not compatible with Stable Diffusion')
             return False
     except RuntimeError as e:
-        print(str(e))
+        log.error(str(e))
         return False
     return True
 
@@ -167,5 +170,5 @@ def get_processor_name():
                 if "model name" in line:
                     return re.sub(".*model name.*:", "", line, 1).strip()
     except:
-        print(traceback.format_exc())
+        log.error(traceback.format_exc())
         return "cpu"
diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index 6cf9428a..827434d7 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -1,9 +1,12 @@
 import os
+import logging
+import picklescan.scanner
+import rich
 
 from sd_internal import app, device_manager
 from sd_internal import Request
-import picklescan.scanner
-import rich
+
+log = logging.getLogger()
 
 KNOWN_MODEL_TYPES = ['stable-diffusion', 'vae', 'hypernetwork', 'gfpgan', 'realesrgan']
 MODEL_EXTENSIONS = {
@@ -42,7 +45,7 @@ def resolve_model_to_use(model_name:str=None, model_type:str=None):
     if model_name:
         is_sd2 = config.get('test_sd2', False)
         if model_name.startswith('sd2_') and not is_sd2: # temp hack, until SD2 is unified with 1.4
-            print('ERROR: Cannot use SD 2.0 models with SD 1.0 code. Using the sd-v1-4 model instead!')
+            log.error('ERROR: Cannot use SD 2.0 models with SD 1.0 code. Using the sd-v1-4 model instead!')
             model_name = 'sd-v1-4'
 
         # Check models directory
@@ -67,7 +70,7 @@ def resolve_model_to_use(model_name:str=None, model_type:str=None):
             for model_extension in model_extensions:
                 if os.path.exists(default_model_path + model_extension):
                     if model_name is not None:
-                        print(f'Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}')
+                        log.warn(f'Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}')
                     return default_model_path + model_extension
 
     return None
@@ -88,13 +91,13 @@ def is_malicious_model(file_path):
     try:
         scan_result = picklescan.scanner.scan_file_path(file_path)
         if scan_result.issues_count > 0 or scan_result.infected_files > 0:
-            rich.print(":warning: [bold red]Scan %s: %d scanned, %d issue, %d infected.[/bold red]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files))
+            log.warn(":warning: [bold red]Scan %s: %d scanned, %d issue, %d infected.[/bold red]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files))
             return True
         else:
-            rich.print("Scan %s: [green]%d scanned, %d issue, %d infected.[/green]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files))
+            log.debug("Scan %s: [green]%d scanned, %d issue, %d infected.[/green]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files))
             return False
     except Exception as e:
-        print('error while scanning', file_path, 'error:', e)
+        log.error(f'error while scanning: {file_path}, error: {e}')
     return False
 
 def getModels():
@@ -111,7 +114,10 @@ def getModels():
         },
     }
 
+    models_scanned = 0
     def listModels(model_type):
+        nonlocal models_scanned
+
         model_extensions = MODEL_EXTENSIONS.get(model_type, [])
         models_dir = os.path.join(app.MODELS_DIR, model_type)
         if not os.path.exists(models_dir):
@@ -126,6 +132,7 @@ def getModels():
                 mtime = os.path.getmtime(model_path)
                 mod_time = known_models[model_path] if model_path in known_models else -1
                 if mod_time != mtime:
+                    models_scanned += 1
                     if is_malicious_model(model_path):
                         models['scan-error'] = file
                         return
@@ -142,6 +149,8 @@ def getModels():
     listModels(model_type='vae')
     listModels(model_type='hypernetwork')
 
+    if models_scanned > 0: log.info(f'[green]Scanned {models_scanned} models. 0 infected[/]')
+
     # legacy
     custom_weight_path = os.path.join(app.SD_DIR, 'custom-model.ckpt')
     if os.path.exists(custom_weight_path):
diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index f74acc12..c7845079 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -6,12 +6,15 @@ import os
 import base64
 import re
 import traceback
+import logging
 
 from sd_internal import device_manager, model_manager
 from sd_internal import Request, Response, Image as ResponseImage, UserInitiatedStop
 
 from modules import model_loader, image_generator, image_utils, filters as image_filters
 
+log = logging.getLogger()
+
 thread_data = threading.local()
 '''
 runtime data (bound locally to this thread), for e.g. device, references to loaded models, optimization flags etc
@@ -69,7 +72,7 @@ def make_images(req: Request, data_queue: queue.Queue, task_temp_images: list, s
     try:
         return _make_images_internal(req, data_queue, task_temp_images, step_callback)
     except Exception as e:
-        print(traceback.format_exc())
+        log.error(traceback.format_exc())
 
         data_queue.put(json.dumps({
             "status": 'failed',
@@ -91,7 +94,7 @@ def _make_images_internal(req: Request, data_queue: queue.Queue, task_temp_image
     res = Response(req, images=construct_response(req, images))
     res = res.json()
     data_queue.put(json.dumps(res))
-    print('Task completed')
+    log.info('Task completed')
 
     return res
 
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 6b0a1d8c..852631c6 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -6,6 +6,7 @@ Notes:
 """
 import json
 import traceback
+import logging
 
 TASK_TTL = 15 * 60 # seconds, Discard last session's task timeout
 
@@ -16,6 +17,8 @@ from typing import Any, Hashable
 from pydantic import BaseModel
 from sd_internal import Request, device_manager
 
+log = logging.getLogger()
+
 THREAD_NAME_PREFIX = 'Runtime-Render/'
 ERR_LOCK_FAILED = ' failed to acquire lock within timeout.'
 LOCK_TIMEOUT = 15 # Maximum locking time in seconds before failing a task.
@@ -140,11 +143,11 @@ class DataCache():
             for key in to_delete:
                 (_, val) = self._base[key]
                 if isinstance(val, RenderTask):
-                    print(f'RenderTask {key} expired. Data removed.')
+                    log.debug(f'RenderTask {key} expired. Data removed.')
                 elif isinstance(val, SessionState):
-                    print(f'Session {key} expired. Data removed.')
+                    log.debug(f'Session {key} expired. Data removed.')
                 else:
-                    print(f'Key {key} expired. Data removed.')
+                    log.debug(f'Key {key} expired. Data removed.')
                 del self._base[key]
         finally:
             self._lock.release()
@@ -178,8 +181,7 @@ class DataCache():
                 self._get_ttl_time(ttl), value
             )
         except Exception as e:
-            print(str(e))
-            print(traceback.format_exc())
+            log.error(traceback.format_exc())
             return False
         else:
             return True
@@ -190,7 +192,7 @@ class DataCache():
         try:
             ttl, value = self._base.get(key, (None, None))
             if ttl is not None and self._is_expired(ttl):
-                print(f'Session {key} expired. Discarding data.')
+                log.debug(f'Session {key} expired. Discarding data.')
                 del self._base[key]
                 return None
             return value
@@ -234,7 +236,7 @@ class SessionState():
 def thread_get_next_task():
     from sd_internal import runtime2
     if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
-        print('Render thread on device', runtime2.thread_data.device, 'failed to acquire manager lock.')
+        log.warn(f'Render thread on device: {runtime2.thread_data.device} failed to acquire manager lock.')
         return None
     if len(tasks_queue) <= 0:
         manager_lock.release()
@@ -269,7 +271,7 @@ def thread_render(device):
     try:
         runtime2.init(device)
     except Exception as e:
-        print(traceback.format_exc())
+        log.error(traceback.format_exc())
         weak_thread_data[threading.current_thread()] = {
             'error': e
         }
@@ -287,7 +289,7 @@ def thread_render(device):
         session_cache.clean()
         task_cache.clean()
         if not weak_thread_data[threading.current_thread()]['alive']:
-            print(f'Shutting down thread for device {runtime2.thread_data.device}')
+            log.info(f'Shutting down thread for device {runtime2.thread_data.device}')
             runtime2.destroy()
             return
         if isinstance(current_state_error, SystemExit):
@@ -299,7 +301,7 @@ def thread_render(device):
             idle_event.wait(timeout=1)
             continue
         if task.error is not None:
-            print(task.error)
+            log.error(task.error)
             task.response = {"status": 'failed', "detail": str(task.error)}
             task.buffer_queue.put(json.dumps(task.response))
             continue
@@ -308,7 +310,7 @@ def thread_render(device):
             task.response = {"status": 'failed', "detail": str(task.error)}
             task.buffer_queue.put(json.dumps(task.response))
             continue
-        print(f'Session {task.request.session_id} starting task {id(task)} on {runtime2.thread_data.device_name}')
+        log.info(f'Session {task.request.session_id} starting task {id(task)} on {runtime2.thread_data.device_name}')
         if not task.lock.acquire(blocking=False): raise Exception('Got locked task from queue.')
         try:
             def step_callback():
@@ -319,7 +321,7 @@ def thread_render(device):
                     if isinstance(current_state_error, StopAsyncIteration):
                         task.error = current_state_error
                         current_state_error = None
-                        print(f'Session {task.request.session_id} sent cancel signal for task {id(task)}')
+                        log.info(f'Session {task.request.session_id} sent cancel signal for task {id(task)}')
 
             current_state = ServerStates.LoadingModel
             runtime2.reload_models_if_necessary(task.request)
@@ -331,7 +333,7 @@ def thread_render(device):
             session_cache.keep(task.request.session_id, TASK_TTL)
         except Exception as e:
             task.error = e
-            print(traceback.format_exc())
+            log.error(traceback.format_exc())
             continue
         finally:
             # Task completed
@@ -339,11 +341,11 @@ def thread_render(device):
         task_cache.keep(id(task), TASK_TTL)
         session_cache.keep(task.request.session_id, TASK_TTL)
         if isinstance(task.error, StopAsyncIteration):
-            print(f'Session {task.request.session_id} task {id(task)} cancelled!')
+            log.info(f'Session {task.request.session_id} task {id(task)} cancelled!')
         elif task.error is not None:
-            print(f'Session {task.request.session_id} task {id(task)} failed!')
+            log.info(f'Session {task.request.session_id} task {id(task)} failed!')
         else:
-            print(f'Session {task.request.session_id} task {id(task)} completed by {runtime2.thread_data.device_name}.')
+            log.info(f'Session {task.request.session_id} task {id(task)} completed by {runtime2.thread_data.device_name}.')
         current_state = ServerStates.Online
 
 def get_cached_task(task_id:str, update_ttl:bool=False):
@@ -429,7 +431,7 @@ def is_alive(device=None):
 
 def start_render_thread(device):
     if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('start_render_thread' + ERR_LOCK_FAILED)
-    print('Start new Rendering Thread on device', device)
+    log.info(f'Start new Rendering Thread on device: {device}')
     try:
         rthread = threading.Thread(target=thread_render, kwargs={'device': device})
         rthread.daemon = True
@@ -441,7 +443,7 @@ def start_render_thread(device):
     timeout = DEVICE_START_TIMEOUT
     while not rthread.is_alive() or not rthread in weak_thread_data or not 'device' in weak_thread_data[rthread]:
         if rthread in weak_thread_data and 'error' in weak_thread_data[rthread]:
-            print(rthread, device, 'error:', weak_thread_data[rthread]['error'])
+            log.error(f"{rthread}, {device}, error: {weak_thread_data[rthread]['error']}")
             return False
         if timeout <= 0:
             return False
@@ -453,11 +455,11 @@ def stop_render_thread(device):
     try:
         device_manager.validate_device_id(device, log_prefix='stop_render_thread')
     except:
-        print(traceback.format_exc())
+        log.error(traceback.format_exc())
         return False
 
     if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('stop_render_thread' + ERR_LOCK_FAILED)
-    print('Stopping Rendering Thread on device', device)
+    log.info(f'Stopping Rendering Thread on device: {device}')
 
     try:
         thread_to_remove = None
@@ -480,27 +482,27 @@ def stop_render_thread(device):
 
 def update_render_threads(render_devices, active_devices):
     devices_to_start, devices_to_stop = device_manager.get_device_delta(render_devices, active_devices)
-    print('devices_to_start', devices_to_start)
-    print('devices_to_stop', devices_to_stop)
+    log.debug(f'devices_to_start: {devices_to_start}')
+    log.debug(f'devices_to_stop: {devices_to_stop}')
 
     for device in devices_to_stop:
         if is_alive(device) <= 0:
-            print(device, 'is not alive')
+            log.debug(f'{device} is not alive')
             continue
         if not stop_render_thread(device):
-            print(device, 'could not stop render thread')
+            log.warn(f'{device} could not stop render thread')
 
     for device in devices_to_start:
         if is_alive(device) >= 1:
-            print(device, 'already registered.')
+            log.debug(f'{device} already registered.')
             continue
         if not start_render_thread(device):
-            print(device, 'failed to start.')
+            log.warn(f'{device} failed to start.')
 
     if is_alive() <= 0: # No running devices, probably invalid user config.
         raise EnvironmentError('ERROR: No active render devices! Please verify the "render_devices" value in config.json')
 
-    print('active devices', get_devices()['active'])
+    log.debug(f"active devices: {get_devices()['active']}")
 
 def shutdown_event(): # Signal render thread to close on shutdown
     global current_state_error
diff --git a/ui/server.py b/ui/server.py
index 458bc1aa..aaa16ce0 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -14,7 +14,9 @@ from pydantic import BaseModel
 
 from sd_internal import app, model_manager, task_manager
 
-print('started in ', app.SD_DIR)
+log = logging.getLogger()
+
+log.info(f'started in {app.SD_DIR}')
 
 server_api = FastAPI()
 
@@ -84,7 +86,7 @@ async def setAppConfig(req : SetAppConfigRequest):
 
         return JSONResponse({'status': 'OK'}, headers=NOCACHE_HEADERS)
     except Exception as e:
-        print(traceback.format_exc())
+        log.error(traceback.format_exc())
         raise HTTPException(status_code=500, detail=str(e))
 
 def update_render_devices_in_config(config, render_devices):
@@ -153,8 +155,7 @@ def render(req : task_manager.ImageRequest):
     except ConnectionRefusedError as e: # Unstarted task pending limit reached, deny queueing too many.
         raise HTTPException(status_code=503, detail=str(e)) # HTTP503 Service Unavailable
     except Exception as e:
-        print(e)
-        print(traceback.format_exc())
+        log.error(traceback.format_exc())
         raise HTTPException(status_code=500, detail=str(e))
 
 @server_api.get('/image/stream/{task_id:int}')
@@ -165,10 +166,10 @@ def stream(task_id:int):
     #if (id(task) != task_id): raise HTTPException(status_code=409, detail=f'Wrong task id received. Expected:{id(task)}, Received:{task_id}') # HTTP409 Conflict
     if task.buffer_queue.empty() and not task.lock.locked():
         if task.response:
-            #print(f'Session {session_id} sending cached response')
+            #log.info(f'Session {session_id} sending cached response')
             return JSONResponse(task.response, headers=NOCACHE_HEADERS)
         raise HTTPException(status_code=425, detail='Too Early, task not started yet.') # HTTP425 Too Early
-    #print(f'Session {session_id} opened live render stream {id(task.buffer_queue)}')
+    #log.info(f'Session {session_id} opened live render stream {id(task.buffer_queue)}')
     return StreamingResponse(task.read_buffer_generator(), media_type='application/json')
 
 @server_api.get('/image/stop')

From a2af811ad29ccd573d5ddbd5497b51bab8e5783a Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 9 Dec 2022 22:47:34 +0530
Subject: [PATCH 16/74] Disable uvicorn access logging in favor of cleaner
 server-side logging, we already get all that info; Print the request metadata

---
 scripts/on_sd_start.bat        | 2 +-
 scripts/on_sd_start.sh         | 2 +-
 ui/sd_internal/app.py          | 6 +++---
 ui/sd_internal/runtime2.py     | 1 +
 ui/sd_internal/task_manager.py | 2 +-
 5 files changed, 7 insertions(+), 6 deletions(-)

diff --git a/scripts/on_sd_start.bat b/scripts/on_sd_start.bat
index 9bac3757..5f1bfcb1 100644
--- a/scripts/on_sd_start.bat
+++ b/scripts/on_sd_start.bat
@@ -393,7 +393,7 @@ call python --version
 
 @if NOT DEFINED SD_UI_BIND_PORT set SD_UI_BIND_PORT=9000
 @if NOT DEFINED SD_UI_BIND_IP set SD_UI_BIND_IP=0.0.0.0
-@uvicorn server:server_api --app-dir "%SD_UI_PATH%" --port %SD_UI_BIND_PORT% --host %SD_UI_BIND_IP%
+@uvicorn server:server_api --app-dir "%SD_UI_PATH%" --port %SD_UI_BIND_PORT% --host %SD_UI_BIND_IP% --log-level critical
 
 
 @pause
diff --git a/scripts/on_sd_start.sh b/scripts/on_sd_start.sh
index afb95295..f4f540e7 100755
--- a/scripts/on_sd_start.sh
+++ b/scripts/on_sd_start.sh
@@ -322,6 +322,6 @@ cd ..
 export SD_UI_PATH=`pwd`/ui
 cd stable-diffusion
 
-uvicorn server:server_api --app-dir "$SD_UI_PATH" --port ${SD_UI_BIND_PORT:-9000} --host ${SD_UI_BIND_IP:-0.0.0.0}
+uvicorn server:server_api --app-dir "$SD_UI_PATH" --port ${SD_UI_BIND_PORT:-9000} --host ${SD_UI_BIND_IP:-0.0.0.0} --log-level critical
 
 read -p "Press any key to continue"
diff --git a/ui/sd_internal/app.py b/ui/sd_internal/app.py
index c34f2ea6..bfb90399 100644
--- a/ui/sd_internal/app.py
+++ b/ui/sd_internal/app.py
@@ -8,12 +8,12 @@ from rich.logging import RichHandler
 
 from sd_internal import task_manager
 
-LOG_FORMAT = '[%(threadName)s] %(message)s'
+LOG_FORMAT = '%(levelname)s %(threadName)s %(message)s'
 logging.basicConfig(
         level=logging.INFO,
         format=LOG_FORMAT,
-        datefmt="[%X.%f]",
-        handlers=[RichHandler(markup=True)]
+        datefmt="%X.%f",
+        handlers=[RichHandler(markup=True, rich_tracebacks=True, show_level=False)]
 )
 
 log = logging.getLogger()
diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index c7845079..cdffa574 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -70,6 +70,7 @@ def reload_models_if_necessary(req: Request):
 
 def make_images(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
     try:
+        log.info(req)
         return _make_images_internal(req, data_queue, task_temp_images, step_callback)
     except Exception as e:
         log.error(traceback.format_exc())
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 852631c6..4eb45ce6 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -19,7 +19,7 @@ from sd_internal import Request, device_manager
 
 log = logging.getLogger()
 
-THREAD_NAME_PREFIX = 'Runtime-Render/'
+THREAD_NAME_PREFIX = ''
 ERR_LOCK_FAILED = ' failed to acquire lock within timeout.'
 LOCK_TIMEOUT = 15 # Maximum locking time in seconds before failing a task.
 # It's better to get an exception than a deadlock... ALWAYS use timeout in critical paths.

From 543f13f9a345df332a4cc29911b8c9266ca55e94 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sun, 11 Dec 2022 13:19:22 +0530
Subject: [PATCH 17/74] Tweak logging to increase the space available by 3
 characters

---
 ui/sd_internal/app.py           | 6 +++---
 ui/sd_internal/model_manager.py | 2 +-
 ui/server.py                    | 2 ++
 3 files changed, 6 insertions(+), 4 deletions(-)

diff --git a/ui/sd_internal/app.py b/ui/sd_internal/app.py
index bfb90399..47a2d610 100644
--- a/ui/sd_internal/app.py
+++ b/ui/sd_internal/app.py
@@ -8,12 +8,12 @@ from rich.logging import RichHandler
 
 from sd_internal import task_manager
 
-LOG_FORMAT = '%(levelname)s %(threadName)s %(message)s'
+LOG_FORMAT = '%(asctime)s.%(msecs)03d %(levelname)s %(threadName)s %(message)s'
 logging.basicConfig(
         level=logging.INFO,
         format=LOG_FORMAT,
-        datefmt="%X.%f",
-        handlers=[RichHandler(markup=True, rich_tracebacks=True, show_level=False)]
+        datefmt="%X",
+        handlers=[RichHandler(markup=True, rich_tracebacks=True, show_time=False, show_level=False)]
 )
 
 log = logging.getLogger()
diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index 827434d7..ebeb439c 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -149,7 +149,7 @@ def getModels():
     listModels(model_type='vae')
     listModels(model_type='hypernetwork')
 
-    if models_scanned > 0: log.info(f'[green]Scanned {models_scanned} models. 0 infected[/]')
+    if models_scanned > 0: log.info(f'[green]Scanned {models_scanned} models. Nothing infected[/]')
 
     # legacy
     custom_weight_path = os.path.join(app.SD_DIR, 'custom-model.ckpt')
diff --git a/ui/server.py b/ui/server.py
index aaa16ce0..1c537dcd 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -5,6 +5,7 @@ Notes:
 import os
 import traceback
 import logging
+import datetime
 from typing import List, Union
 
 from fastapi import FastAPI, HTTPException
@@ -17,6 +18,7 @@ from sd_internal import app, model_manager, task_manager
 log = logging.getLogger()
 
 log.info(f'started in {app.SD_DIR}')
+log.info(f'started at {datetime.datetime.now():%x %X}')
 
 server_api = FastAPI()
 

From afb88616d85817470ff369890485b33a48946996 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sun, 11 Dec 2022 13:30:16 +0530
Subject: [PATCH 18/74] Load the models after the device init, to let the UI
 load before the models finish loading

---
 ui/sd_internal/runtime2.py     | 4 +---
 ui/sd_internal/task_manager.py | 1 +
 2 files changed, 2 insertions(+), 3 deletions(-)

diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index cdffa574..06c6fdb6 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -39,13 +39,11 @@ def init(device):
 
     device_manager.device_init(thread_data, device)
 
-    init_and_load_default_models()
-
 def destroy():
     for model_type in ('stable-diffusion', 'hypernetwork', 'gfpgan', 'realesrgan'):
         model_loader.unload_model(thread_data, model_type)
 
-def init_and_load_default_models():
+def load_default_models():
     # init default model paths
     for model_type in model_manager.KNOWN_MODEL_TYPES:
         thread_data.model_paths[model_type] = model_manager.resolve_model_to_use(model_type=model_type)
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 4eb45ce6..9d1d26f6 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -283,6 +283,7 @@ def thread_render(device):
         'alive': True
     }
 
+    runtime2.load_default_models()
     current_state = ServerStates.Online
 
     while True:

From d03eed385987ee7e3c80f42172142aa711b287e3 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sun, 11 Dec 2022 14:14:59 +0530
Subject: [PATCH 19/74] Simplify the logic for reloading gfpgan and realesrgan
 models (based on the request), using the code path used for the other model
 types

---
 ui/sd_internal/runtime2.py | 29 ++++++++++++++++++-----------
 ui/server.py               |  6 ++++++
 2 files changed, 24 insertions(+), 11 deletions(-)

diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index 06c6fdb6..b7ce6fe5 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -40,7 +40,7 @@ def init(device):
     device_manager.device_init(thread_data, device)
 
 def destroy():
-    for model_type in ('stable-diffusion', 'hypernetwork', 'gfpgan', 'realesrgan'):
+    for model_type in model_manager.KNOWN_MODEL_TYPES:
         model_loader.unload_model(thread_data, model_type)
 
 def load_default_models():
@@ -52,19 +52,26 @@ def load_default_models():
     model_loader.load_model(thread_data, 'stable-diffusion')
 
 def reload_models_if_necessary(req: Request):
+    model_paths_in_req = (
+        ('hypernetwork', req.use_hypernetwork_model),
+        ('gfpgan', req.use_face_correction),
+        ('realesrgan', req.use_upscale),
+    )
+
     if model_manager.is_sd_model_reload_necessary(thread_data, req):
         thread_data.model_paths['stable-diffusion'] = req.use_stable_diffusion_model
         thread_data.model_paths['vae'] = req.use_vae_model
 
         model_loader.load_model(thread_data, 'stable-diffusion')
 
-    if thread_data.model_paths.get('hypernetwork') != req.use_hypernetwork_model:
-        thread_data.model_paths['hypernetwork'] = req.use_hypernetwork_model
+    for model_type, model_path_in_req in model_paths_in_req:
+        if thread_data.model_paths.get(model_type) != model_path_in_req:
+            thread_data.model_paths[model_type] = model_path_in_req
 
-        if thread_data.model_paths['hypernetwork'] is not None:
-            model_loader.load_model(thread_data, 'hypernetwork')
-        else:
-            model_loader.unload_model(thread_data, 'hypernetwork')
+            if thread_data.model_paths[model_type] is not None:
+                model_loader.load_model(thread_data, model_type)
+            else:
+                model_loader.unload_model(thread_data, model_type)
 
 def make_images(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
     try:
@@ -137,13 +144,13 @@ def apply_filters(args: dict, images: list, user_stopped, show_only_filtered_ima
         return images
 
     filters = []
-    if args['use_face_correction'].startswith('GFPGAN'): filters.append((image_filters.apply_gfpgan, model_manager.resolve_model_to_use(args['use_face_correction'], model_type='gfpgan')))
-    if args['use_face_correction'].use_upscale.startswith('RealESRGAN'): filters.append((image_filters.apply_realesrgan, model_manager.resolve_model_to_use(args['use_upscale'], model_type='realesrgan')))
+    if 'gfpgan' in args['use_face_correction'].lower(): filters.append(image_filters.apply_gfpgan)
+    if 'realesrgan' in args['use_face_correction'].lower(): filters.append(image_filters.apply_realesrgan)
 
     filtered_images = []
     for img, seed, _ in images:
-        for filter_fn, filter_model_path in filters:
-            img = filter_fn(thread_data, img, filter_model_path)
+        for filter_fn in filters:
+            img = filter_fn(thread_data, img)
 
         filtered_images.append((img, seed, True))
 
diff --git a/ui/server.py b/ui/server.py
index 1c537dcd..258c433d 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -140,10 +140,16 @@ def ping(session_id:str=None):
 def render(req : task_manager.ImageRequest):
     try:
         app.save_model_to_config(req.use_stable_diffusion_model, req.use_vae_model, req.use_hypernetwork_model)
+
+        # resolve the model paths to use
         req.use_stable_diffusion_model = model_manager.resolve_model_to_use(req.use_stable_diffusion_model, model_type='stable-diffusion')
         req.use_vae_model = model_manager.resolve_model_to_use(req.use_vae_model, model_type='vae')
         req.use_hypernetwork_model = model_manager.resolve_model_to_use(req.use_hypernetwork_model, model_type='hypernetwork')
 
+        if req.use_face_correction: req.use_face_correction = model_manager.resolve_model_to_use(req.use_face_correction, 'gfpgan')
+        if req.use_upscale: req.use_upscale = model_manager.resolve_model_to_use(req.use_upscale, 'gfpgan')
+
+        # enqueue the task
         new_task = task_manager.render(req)
         response = {
             'status': str(task_manager.current_state), 

From 6ce6dc3ff630c5953b33c509a004a017a5edfd63 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sun, 11 Dec 2022 18:16:29 +0530
Subject: [PATCH 20/74] Get rid of the ugly copying around (and maintaining) of
 multiple request-related fields. Split into two objects: task-related fields,
 and render-related fields. Also remove the ability for request-defined
 full-precision. Full-precision can now be forced by using a
 USE_FULL_PRECISION environment variable

---
 ui/media/js/auto-save.js         |   2 -
 ui/media/js/dnd.js               |   8 --
 ui/media/js/engine.js            |   2 -
 ui/media/js/main.js              |   1 -
 ui/media/js/parameters.js        |   9 ---
 ui/sd_internal/__init__.py       |  90 +++-------------------
 ui/sd_internal/device_manager.py |  14 +++-
 ui/sd_internal/model_manager.py  |  19 +----
 ui/sd_internal/runtime2.py       | 125 ++++++++++++++++---------------
 ui/sd_internal/task_manager.py   | 119 +++++------------------------
 ui/server.py                     |  31 +++-----
 11 files changed, 115 insertions(+), 305 deletions(-)

diff --git a/ui/media/js/auto-save.js b/ui/media/js/auto-save.js
index 9025f988..df044e2b 100644
--- a/ui/media/js/auto-save.js
+++ b/ui/media/js/auto-save.js
@@ -37,7 +37,6 @@ const SETTINGS_IDS_LIST = [
     "diskPath",
     "sound_toggle",
     "turbo",
-    "use_full_precision",
     "confirm_dangerous_actions",
     "auto_save_settings",
     "apply_color_correction"
@@ -278,7 +277,6 @@ function tryLoadOldSettings() {
         "soundEnabled": "sound_toggle",
         "saveToDisk": "save_to_disk",
         "useCPU": "use_cpu",
-        "useFullPrecision": "use_full_precision",
         "useTurboMode": "turbo",
         "diskPath": "diskPath",
         "useFaceCorrection": "use_face_correction",
diff --git a/ui/media/js/dnd.js b/ui/media/js/dnd.js
index 53b55ac7..8b9819c2 100644
--- a/ui/media/js/dnd.js
+++ b/ui/media/js/dnd.js
@@ -217,13 +217,6 @@ const TASK_MAPPING = {
         readUI: () => turboField.checked,
         parse: (val) => Boolean(val)
     },
-    use_full_precision: { name: 'Use Full Precision',
-        setUI: (use_full_precision) => {
-            useFullPrecisionField.checked = use_full_precision
-        },
-        readUI: () => useFullPrecisionField.checked,
-        parse: (val) => Boolean(val)
-    },
 
     stream_image_progress: { name: 'Stream Image Progress',
         setUI: (stream_image_progress) => {
@@ -453,7 +446,6 @@ document.addEventListener("dragover", dragOverHandler)
 const TASK_REQ_NO_EXPORT = [
     "use_cpu",
     "turbo",
-    "use_full_precision",
     "save_to_disk_path"
 ]
 const resetSettings = document.getElementById('reset-image-settings')
diff --git a/ui/media/js/engine.js b/ui/media/js/engine.js
index dd34ddb1..61822c0f 100644
--- a/ui/media/js/engine.js
+++ b/ui/media/js/engine.js
@@ -728,7 +728,6 @@
         "stream_image_progress": 'boolean',
         "show_only_filtered_image": 'boolean',
         "turbo": 'boolean',
-        "use_full_precision": 'boolean',
         "output_format": 'string',
         "output_quality": 'number',
     }
@@ -744,7 +743,6 @@
         "stream_image_progress": true,
         "show_only_filtered_image": true,
         "turbo": false,
-        "use_full_precision": false,
         "output_format": "png",
         "output_quality": 75,
     }
diff --git a/ui/media/js/main.js b/ui/media/js/main.js
index 6c08aef7..e058f9e9 100644
--- a/ui/media/js/main.js
+++ b/ui/media/js/main.js
@@ -850,7 +850,6 @@ function getCurrentUserRequest() {
             // allow_nsfw: allowNSFWField.checked,
             turbo: turboField.checked,
             //render_device: undefined, // Set device affinity. Prefer this device, but wont activate.
-            use_full_precision: useFullPrecisionField.checked,
             use_stable_diffusion_model: stableDiffusionModelField.value,
             use_vae_model: vaeModelField.value,
             stream_progress_updates: true,
diff --git a/ui/media/js/parameters.js b/ui/media/js/parameters.js
index 3643d1ec..f326953b 100644
--- a/ui/media/js/parameters.js
+++ b/ui/media/js/parameters.js
@@ -105,14 +105,6 @@ var PARAMETERS = [
         note: "to process in parallel",
         default: false,
     },
-    {
-        id: "use_full_precision",
-        type: ParameterType.checkbox,
-        label: "Use Full Precision",
-        note: "for GPU-only. warning: this will consume more VRAM",
-        icon: "fa-crosshairs",
-        default: false,
-    },
     {
         id: "auto_save_settings",
         type: ParameterType.checkbox,
@@ -214,7 +206,6 @@ let turboField = document.querySelector('#turbo')
 let useCPUField = document.querySelector('#use_cpu')
 let autoPickGPUsField = document.querySelector('#auto_pick_gpus')
 let useGPUsField = document.querySelector('#use_gpus')
-let useFullPrecisionField = document.querySelector('#use_full_precision')
 let saveToDiskField = document.querySelector('#save_to_disk')
 let diskPathField = document.querySelector('#diskPath')
 let listenToNetworkField = document.querySelector("#listen_to_network")
diff --git a/ui/sd_internal/__init__.py b/ui/sd_internal/__init__.py
index 9dd4f066..a06220ca 100644
--- a/ui/sd_internal/__init__.py
+++ b/ui/sd_internal/__init__.py
@@ -1,93 +1,22 @@
-import json
+from pydantic import BaseModel
 
-class Request:
+from modules.types import GenerateImageRequest
+
+class TaskData(BaseModel):
     request_id: str = None
     session_id: str = "session"
-    prompt: str = ""
-    negative_prompt: str = ""
-    init_image: str = None # base64
-    mask: str = None # base64
-    apply_color_correction = False
-    num_outputs: int = 1
-    num_inference_steps: int = 50
-    guidance_scale: float = 7.5
-    width: int = 512
-    height: int = 512
-    seed: int = 42
-    prompt_strength: float = 0.8
-    sampler: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
-    # allow_nsfw: bool = False
-    precision: str = "autocast" # or "full"
     save_to_disk_path: str = None
     turbo: bool = True
-    use_full_precision: bool = False
     use_face_correction: str = None # or "GFPGANv1.3"
     use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
     use_stable_diffusion_model: str = "sd-v1-4"
     use_vae_model: str = None
     use_hypernetwork_model: str = None
-    hypernetwork_strength: float = 1
     show_only_filtered_image: bool = False
     output_format: str = "jpeg" # or "png"
     output_quality: int = 75
-
-    stream_progress_updates: bool = False
     stream_image_progress: bool = False
 
-    def json(self):
-        return {
-            "request_id": self.request_id,
-            "session_id": self.session_id,
-            "prompt": self.prompt,
-            "negative_prompt": self.negative_prompt,
-            "num_outputs": self.num_outputs,
-            "num_inference_steps": self.num_inference_steps,
-            "guidance_scale": self.guidance_scale,
-            "width": self.width,
-            "height": self.height,
-            "seed": self.seed,
-            "prompt_strength": self.prompt_strength,
-            "sampler": self.sampler,
-            "apply_color_correction": self.apply_color_correction,
-            "use_face_correction": self.use_face_correction,
-            "use_upscale": self.use_upscale,
-            "use_stable_diffusion_model": self.use_stable_diffusion_model,
-            "use_vae_model": self.use_vae_model,
-            "use_hypernetwork_model": self.use_hypernetwork_model,
-            "hypernetwork_strength": self.hypernetwork_strength,
-            "output_format": self.output_format,
-            "output_quality": self.output_quality,
-        }
-
-    def __str__(self):
-        return f'''
-    session_id: {self.session_id}
-    prompt: {self.prompt}
-    negative_prompt: {self.negative_prompt}
-    seed: {self.seed}
-    num_inference_steps: {self.num_inference_steps}
-    sampler: {self.sampler}
-    guidance_scale: {self.guidance_scale}
-    w: {self.width}
-    h: {self.height}
-    precision: {self.precision}
-    save_to_disk_path: {self.save_to_disk_path}
-    turbo: {self.turbo}
-    use_full_precision: {self.use_full_precision}
-    apply_color_correction: {self.apply_color_correction}
-    use_face_correction: {self.use_face_correction}
-    use_upscale: {self.use_upscale}
-    use_stable_diffusion_model: {self.use_stable_diffusion_model}
-    use_vae_model: {self.use_vae_model}
-    use_hypernetwork_model: {self.use_hypernetwork_model}
-    hypernetwork_strength: {self.hypernetwork_strength}
-    show_only_filtered_image: {self.show_only_filtered_image}
-    output_format: {self.output_format}
-    output_quality: {self.output_quality}
-
-    stream_progress_updates: {self.stream_progress_updates}
-    stream_image_progress: {self.stream_image_progress}'''
-
 class Image:
     data: str # base64
     seed: int
@@ -106,17 +35,20 @@ class Image:
         }
 
 class Response:
-    request: Request
+    render_request: GenerateImageRequest
+    task_data: TaskData
     images: list
 
-    def __init__(self, request: Request, images: list):
-        self.request = request
+    def __init__(self, render_request: GenerateImageRequest, task_data: TaskData, images: list):
+        self.render_request = render_request
+        self.task_data = task_data
         self.images = images
 
     def json(self):
         res = {
             "status": 'succeeded',
-            "request": self.request.json(),
+            "render_request": self.render_request.dict(),
+            "task_data": self.task_data.dict(),
             "output": [],
         }
 
diff --git a/ui/sd_internal/device_manager.py b/ui/sd_internal/device_manager.py
index a3f91cfb..733bab50 100644
--- a/ui/sd_internal/device_manager.py
+++ b/ui/sd_internal/device_manager.py
@@ -6,6 +6,13 @@ import logging
 
 log = logging.getLogger()
 
+'''
+Set `FORCE_FULL_PRECISION` in the environment variables, or in `config.bat`/`config.sh` to set full precision (i.e. float32).
+Otherwise the models will load at half-precision (i.e. float16).
+
+Half-precision is fine most of the time. Full precision is only needed for working around GPU bugs (like NVIDIA 16xx GPUs).
+'''
+
 COMPARABLE_GPU_PERCENTILE = 0.65 # if a GPU's free_mem is within this % of the GPU with the most free_mem, it will be picked
 
 mem_free_threshold = 0
@@ -96,7 +103,7 @@ def device_init(context, device):
     if device == 'cpu':
         context.device = 'cpu'
         context.device_name = get_processor_name()
-        context.precision = 'full'
+        context.half_precision = False
         log.debug(f'Render device CPU available as {context.device_name}')
         return
 
@@ -107,7 +114,7 @@ def device_init(context, device):
     if needs_to_force_full_precision(context):
         log.warn(f'forcing full precision on this GPU, to avoid green images. GPU detected: {context.device_name}')
         # Apply force_full_precision now before models are loaded.
-        context.precision = 'full'
+        context.half_precision = False
 
     log.info(f'Setting {device} as active')
     torch.cuda.device(device)
@@ -115,6 +122,9 @@ def device_init(context, device):
     return
 
 def needs_to_force_full_precision(context):
+    if 'FORCE_FULL_PRECISION' in os.environ:
+        return True
+
     device_name = context.device_name.lower()
     return (('nvidia' in device_name or 'geforce' in device_name) and (' 1660' in device_name or ' 1650' in device_name)) or ('Quadro T2000' in device_name)
 
diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index ebeb439c..2129af3d 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -3,8 +3,7 @@ import logging
 import picklescan.scanner
 import rich
 
-from sd_internal import app, device_manager
-from sd_internal import Request
+from sd_internal import app
 
 log = logging.getLogger()
 
@@ -157,19 +156,3 @@ def getModels():
         models['options']['stable-diffusion'].append('custom-model')
 
     return models
-
-def is_sd_model_reload_necessary(thread_data, req: Request):
-    needs_model_reload = False
-    if 'stable-diffusion' not in thread_data.models or \
-        thread_data.model_paths['stable-diffusion'] != req.use_stable_diffusion_model or \
-        thread_data.model_paths['vae'] != req.use_vae_model:
-
-        needs_model_reload = True
-
-    if thread_data.device != 'cpu':
-        if (thread_data.precision == 'autocast' and req.use_full_precision) or \
-            (thread_data.precision == 'full' and not req.use_full_precision and not device_manager.needs_to_force_full_precision(thread_data)):
-            thread_data.precision = 'full' if req.use_full_precision else 'autocast'
-            needs_model_reload = True
-
-    return needs_model_reload
diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index b7ce6fe5..434f489b 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -9,13 +9,14 @@ import traceback
 import logging
 
 from sd_internal import device_manager, model_manager
-from sd_internal import Request, Response, Image as ResponseImage, UserInitiatedStop
+from sd_internal import TaskData, Response, Image as ResponseImage, UserInitiatedStop
 
 from modules import model_loader, image_generator, image_utils, filters as image_filters
+from modules.types import Context, GenerateImageRequest
 
 log = logging.getLogger()
 
-thread_data = threading.local()
+thread_data = Context()
 '''
 runtime data (bound locally to this thread), for e.g. device, references to loaded models, optimization flags etc
 '''
@@ -28,14 +29,7 @@ def init(device):
     '''
     thread_data.stop_processing = False
     thread_data.temp_images = {}
-
-    thread_data.models = {}
-    thread_data.model_paths = {}
-
-    thread_data.device = None
-    thread_data.device_name = None
-    thread_data.precision = 'autocast'
-    thread_data.vram_optimizations = ('TURBO', 'MOVE_MODELS')
+    thread_data.partial_x_samples = None
 
     device_manager.device_init(thread_data, device)
 
@@ -51,16 +45,16 @@ def load_default_models():
     # load mandatory models
     model_loader.load_model(thread_data, 'stable-diffusion')
 
-def reload_models_if_necessary(req: Request):
+def reload_models_if_necessary(task_data: TaskData):
     model_paths_in_req = (
-        ('hypernetwork', req.use_hypernetwork_model),
-        ('gfpgan', req.use_face_correction),
-        ('realesrgan', req.use_upscale),
+        ('hypernetwork', task_data.use_hypernetwork_model),
+        ('gfpgan', task_data.use_face_correction),
+        ('realesrgan', task_data.use_upscale),
     )
 
-    if model_manager.is_sd_model_reload_necessary(thread_data, req):
-        thread_data.model_paths['stable-diffusion'] = req.use_stable_diffusion_model
-        thread_data.model_paths['vae'] = req.use_vae_model
+    if thread_data.model_paths.get('stable-diffusion') != task_data.use_stable_diffusion_model or thread_data.model_paths.get('vae') != task_data.use_vae_model:
+        thread_data.model_paths['stable-diffusion'] = task_data.use_stable_diffusion_model
+        thread_data.model_paths['vae'] = task_data.use_vae_model
 
         model_loader.load_model(thread_data, 'stable-diffusion')
 
@@ -73,10 +67,17 @@ def reload_models_if_necessary(req: Request):
             else:
                 model_loader.unload_model(thread_data, model_type)
 
-def make_images(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
+def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
     try:
-        log.info(req)
-        return _make_images_internal(req, data_queue, task_temp_images, step_callback)
+        # resolve the model paths to use
+        resolve_model_paths(task_data)
+
+        # convert init image to PIL.Image
+        req.init_image = image_utils.base64_str_to_img(req.init_image) if req.init_image is not None else None
+        req.init_image_mask = image_utils.base64_str_to_img(req.init_image_mask) if req.init_image_mask is not None else None
+
+        # generate
+        return _make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
     except Exception as e:
         log.error(traceback.format_exc())
 
@@ -86,66 +87,76 @@ def make_images(req: Request, data_queue: queue.Queue, task_temp_images: list, s
         }))
         raise e
 
-def _make_images_internal(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
-    args = req_to_args(req)
+def _make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
+    metadata = req.dict()
+    del metadata['init_image']
+    del metadata['init_image_mask']
+    print(metadata)
 
-    images, user_stopped = generate_images(args, data_queue, task_temp_images, step_callback, req.stream_image_progress)
-    images = apply_color_correction(args, images, user_stopped)
-    images = apply_filters(args, images, user_stopped, req.show_only_filtered_image)
+    images, user_stopped = generate_images(req, data_queue, task_temp_images, step_callback, task_data.stream_image_progress)
+    images = apply_color_correction(req, images, user_stopped)
+    images = apply_filters(task_data, images, user_stopped, task_data.show_only_filtered_image)
 
-    if req.save_to_disk_path is not None:
-        out_path = os.path.join(req.save_to_disk_path, filename_regex.sub('_', req.session_id))
-        save_images(images, out_path, metadata=req.json(), show_only_filtered_image=req.show_only_filtered_image)
+    if task_data.save_to_disk_path is not None:
+        out_path = os.path.join(task_data.save_to_disk_path, filename_regex.sub('_', task_data.session_id))
+        save_images(images, out_path, metadata=metadata, show_only_filtered_image=task_data.show_only_filtered_image)
 
-    res = Response(req, images=construct_response(req, images))
+    res = Response(req, task_data, images=construct_response(images))
     res = res.json()
     data_queue.put(json.dumps(res))
     log.info('Task completed')
 
     return res
 
-def generate_images(args: dict, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
+def resolve_model_paths(task_data: TaskData):
+    task_data.use_stable_diffusion_model = model_manager.resolve_model_to_use(task_data.use_stable_diffusion_model, model_type='stable-diffusion')
+    task_data.use_vae_model = model_manager.resolve_model_to_use(task_data.use_vae_model, model_type='vae')
+    task_data.use_hypernetwork_model = model_manager.resolve_model_to_use(task_data.use_hypernetwork_model, model_type='hypernetwork')
+
+    if task_data.use_face_correction: task_data.use_face_correction = model_manager.resolve_model_to_use(task_data.use_face_correction, 'gfpgan')
+    if task_data.use_upscale: task_data.use_upscale = model_manager.resolve_model_to_use(task_data.use_upscale, 'gfpgan')
+
+def generate_images(req: GenerateImageRequest, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
     thread_data.temp_images.clear()
 
-    image_generator.on_image_step = make_step_callback(args, data_queue, task_temp_images, step_callback, stream_image_progress)
+    image_generator.on_image_step = make_step_callback(req, data_queue, task_temp_images, step_callback, stream_image_progress)
 
     try:
-        images = image_generator.make_images(context=thread_data, args=args)
+        images = image_generator.make_images(context=thread_data, req=req)
         user_stopped = False
     except UserInitiatedStop:
         images = []
         user_stopped = True
-        if not hasattr(thread_data, 'partial_x_samples') or thread_data.partial_x_samples is None:
-            return images
-        for i in range(args['num_outputs']):
-            images[i] = image_utils.latent_to_img(thread_data, thread_data.partial_x_samples[i].unsqueeze(0))
-        
-        del thread_data.partial_x_samples
+        if thread_data.partial_x_samples is not None:
+            for i in range(req.num_outputs):
+                images[i] = image_utils.latent_to_img(thread_data, thread_data.partial_x_samples[i].unsqueeze(0))
+
+        thread_data.partial_x_samples = None
     finally:
         model_loader.gc(thread_data)
     
-    images = [(image, args['seed'] + i, False) for i, image in enumerate(images)]
+    images = [(image, req.seed + i, False) for i, image in enumerate(images)]
 
     return images, user_stopped
 
-def apply_color_correction(args: dict, images: list, user_stopped):
-    if user_stopped or args['init_image'] is None or not args['apply_color_correction']:
+def apply_color_correction(req: GenerateImageRequest, images: list, user_stopped):
+    if user_stopped or req.init_image is None or not req.apply_color_correction:
         return images
 
     for i, img_info in enumerate(images):
         img, seed, filtered = img_info
-        img = image_utils.apply_color_correction(orig_image=args['init_image'], image_to_correct=img)
+        img = image_utils.apply_color_correction(orig_image=req.init_image, image_to_correct=img)
         images[i] = (img, seed, filtered)
 
     return images
 
-def apply_filters(args: dict, images: list, user_stopped, show_only_filtered_image):
-    if user_stopped or (args['use_face_correction'] is None and args['use_upscale'] is None):
+def apply_filters(task_data: TaskData, images: list, user_stopped, show_only_filtered_image):
+    if user_stopped or (task_data.use_face_correction is None and task_data.use_upscale is None):
         return images
 
     filters = []
-    if 'gfpgan' in args['use_face_correction'].lower(): filters.append(image_filters.apply_gfpgan)
-    if 'realesrgan' in args['use_face_correction'].lower(): filters.append(image_filters.apply_realesrgan)
+    if 'gfpgan' in task_data.use_face_correction.lower(): filters.append(image_filters.apply_gfpgan)
+    if 'realesrgan' in task_data.use_face_correction.lower(): filters.append(image_filters.apply_realesrgan)
 
     filtered_images = []
     for img, seed, _ in images:
@@ -188,37 +199,29 @@ def save_images(images: list, save_to_disk_path, metadata: dict, show_only_filte
         img_path += '.' + metadata['output_format']
         img.save(img_path, quality=metadata['output_quality'])
 
-def construct_response(req: Request, images: list):
+def construct_response(task_data: TaskData, images: list):
     return [
         ResponseImage(
-            data=image_utils.img_to_base64_str(img, req.output_format, req.output_quality),
+            data=image_utils.img_to_base64_str(img, task_data.output_format, task_data.output_quality),
             seed=seed
         ) for img, seed, _ in images
     ]
 
-def req_to_args(req: Request):
-    args = req.json()
-
-    args['init_image'] = image_utils.base64_str_to_img(req.init_image) if req.init_image is not None else None
-    args['mask'] = image_utils.base64_str_to_img(req.mask) if req.mask is not None else None
-
-    return args
-
-def make_step_callback(args: dict, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
-    n_steps = args['num_inference_steps'] if args['init_image'] is None else int(args['num_inference_steps'] * args['prompt_strength'])
+def make_step_callback(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
+    n_steps = req.num_inference_steps if req.init_image is None else int(req.num_inference_steps * req.prompt_strength)
     last_callback_time = -1
 
     def update_temp_img(x_samples, task_temp_images: list):
         partial_images = []
-        for i in range(args['num_outputs']):
+        for i in range(req.num_outputs):
             img = image_utils.latent_to_img(thread_data, x_samples[i].unsqueeze(0))
             buf = image_utils.img_to_buffer(img, output_format='JPEG')
 
             del img
 
-            thread_data.temp_images[f"{args['request_id']}/{i}"] = buf
+            thread_data.temp_images[f"{task_data.request_id}/{i}"] = buf
             task_temp_images[i] = buf
-            partial_images.append({'path': f"/image/tmp/{args['request_id']}/{i}"})
+            partial_images.append({'path': f"/image/tmp/{task_data.request_id}/{i}"})
         return partial_images
 
     def on_image_step(x_samples, i):
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 9d1d26f6..3ec1b99d 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -14,8 +14,8 @@ import torch
 import queue, threading, time, weakref
 from typing import Any, Hashable
 
-from pydantic import BaseModel
-from sd_internal import Request, device_manager
+from sd_internal import TaskData, device_manager
+from modules.types import GenerateImageRequest
 
 log = logging.getLogger()
 
@@ -39,9 +39,10 @@ class ServerStates:
     class Unavailable(Symbol): pass
 
 class RenderTask(): # Task with output queue and completion lock.
-    def __init__(self, req: Request):
+    def __init__(self, req: GenerateImageRequest, task_data: TaskData):
         req.request_id = id(self)
-        self.request: Request = req  # Initial Request
+        self.render_request: GenerateImageRequest = req  # Initial Request
+        self.task_data: TaskData = task_data
         self.response: Any = None # Copy of the last reponse
         self.render_device = None # Select the task affinity. (Not used to change active devices).
         self.temp_images:list = [None] * req.num_outputs * (1 if req.show_only_filtered_image else 2)
@@ -72,55 +73,6 @@ class RenderTask(): # Task with output queue and completion lock.
     def is_pending(self):
         return bool(not self.response and not self.error)
 
-# defaults from https://huggingface.co/blog/stable_diffusion
-class ImageRequest(BaseModel):
-    session_id: str = "session"
-    prompt: str = ""
-    negative_prompt: str = ""
-    init_image: str = None # base64
-    mask: str = None # base64
-    apply_color_correction: bool = False
-    num_outputs: int = 1
-    num_inference_steps: int = 50
-    guidance_scale: float = 7.5
-    width: int = 512
-    height: int = 512
-    seed: int = 42
-    prompt_strength: float = 0.8
-    sampler: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
-    # allow_nsfw: bool = False
-    save_to_disk_path: str = None
-    turbo: bool = True
-    use_cpu: bool = False ##TODO Remove after UI and plugins transition.
-    render_device: str = None # Select the task affinity. (Not used to change active devices).
-    use_full_precision: bool = False
-    use_face_correction: str = None # or "GFPGANv1.3"
-    use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
-    use_stable_diffusion_model: str = "sd-v1-4"
-    use_vae_model: str = None
-    use_hypernetwork_model: str = None
-    hypernetwork_strength: float = None
-    show_only_filtered_image: bool = False
-    output_format: str = "jpeg" # or "png"
-    output_quality: int = 75
-
-    stream_progress_updates: bool = False
-    stream_image_progress: bool = False
-
-class FilterRequest(BaseModel):
-    session_id: str = "session"
-    model: str = None
-    name: str = ""
-    init_image: str = None # base64
-    width: int = 512
-    height: int = 512
-    save_to_disk_path: str = None
-    turbo: bool = True
-    render_device: str = None
-    use_full_precision: bool = False
-    output_format: str = "jpeg" # or "png"
-    output_quality: int = 75
-
 # Temporary cache to allow to query tasks results for a short time after they are completed.
 class DataCache():
     def __init__(self):
@@ -311,7 +263,7 @@ def thread_render(device):
             task.response = {"status": 'failed', "detail": str(task.error)}
             task.buffer_queue.put(json.dumps(task.response))
             continue
-        log.info(f'Session {task.request.session_id} starting task {id(task)} on {runtime2.thread_data.device_name}')
+        log.info(f'Session {task.task_data.session_id} starting task {id(task)} on {runtime2.thread_data.device_name}')
         if not task.lock.acquire(blocking=False): raise Exception('Got locked task from queue.')
         try:
             def step_callback():
@@ -322,16 +274,16 @@ def thread_render(device):
                     if isinstance(current_state_error, StopAsyncIteration):
                         task.error = current_state_error
                         current_state_error = None
-                        log.info(f'Session {task.request.session_id} sent cancel signal for task {id(task)}')
+                        log.info(f'Session {task.task_data.session_id} sent cancel signal for task {id(task)}')
 
             current_state = ServerStates.LoadingModel
-            runtime2.reload_models_if_necessary(task.request)
+            runtime2.reload_models_if_necessary(task.task_data)
 
             current_state = ServerStates.Rendering
-            task.response = runtime2.make_images(task.request, task.buffer_queue, task.temp_images, step_callback)
+            task.response = runtime2.make_images(task.render_request, task.task_data, task.buffer_queue, task.temp_images, step_callback)
             # Before looping back to the generator, mark cache as still alive.
             task_cache.keep(id(task), TASK_TTL)
-            session_cache.keep(task.request.session_id, TASK_TTL)
+            session_cache.keep(task.task_data.session_id, TASK_TTL)
         except Exception as e:
             task.error = e
             log.error(traceback.format_exc())
@@ -340,13 +292,13 @@ def thread_render(device):
             # Task completed
             task.lock.release()
         task_cache.keep(id(task), TASK_TTL)
-        session_cache.keep(task.request.session_id, TASK_TTL)
+        session_cache.keep(task.task_data.session_id, TASK_TTL)
         if isinstance(task.error, StopAsyncIteration):
-            log.info(f'Session {task.request.session_id} task {id(task)} cancelled!')
+            log.info(f'Session {task.task_data.session_id} task {id(task)} cancelled!')
         elif task.error is not None:
-            log.info(f'Session {task.request.session_id} task {id(task)} failed!')
+            log.info(f'Session {task.task_data.session_id} task {id(task)} failed!')
         else:
-            log.info(f'Session {task.request.session_id} task {id(task)} completed by {runtime2.thread_data.device_name}.')
+            log.info(f'Session {task.task_data.session_id} task {id(task)} completed by {runtime2.thread_data.device_name}.')
         current_state = ServerStates.Online
 
 def get_cached_task(task_id:str, update_ttl:bool=False):
@@ -509,53 +461,18 @@ def shutdown_event(): # Signal render thread to close on shutdown
     global current_state_error
     current_state_error = SystemExit('Application shutting down.')
 
-def render(req : ImageRequest):
+def render(render_req: GenerateImageRequest, task_data: TaskData):
     current_thread_count = is_alive()
     if current_thread_count <= 0:  # Render thread is dead
         raise ChildProcessError('Rendering thread has died.')
 
     # Alive, check if task in cache
-    session = get_cached_session(req.session_id, update_ttl=True)
+    session = get_cached_session(task_data.session_id, update_ttl=True)
     pending_tasks = list(filter(lambda t: t.is_pending, session.tasks))
     if current_thread_count < len(pending_tasks):
-        raise ConnectionRefusedError(f'Session {req.session_id} already has {len(pending_tasks)} pending tasks out of {current_thread_count}.')
+        raise ConnectionRefusedError(f'Session {task_data.session_id} already has {len(pending_tasks)} pending tasks out of {current_thread_count}.')
 
-    r = Request()
-    r.session_id = req.session_id
-    r.prompt = req.prompt
-    r.negative_prompt = req.negative_prompt
-    r.init_image = req.init_image
-    r.mask = req.mask
-    r.apply_color_correction = req.apply_color_correction
-    r.num_outputs = req.num_outputs
-    r.num_inference_steps = req.num_inference_steps
-    r.guidance_scale = req.guidance_scale
-    r.width = req.width
-    r.height = req.height
-    r.seed = req.seed
-    r.prompt_strength = req.prompt_strength
-    r.sampler = req.sampler
-    # r.allow_nsfw = req.allow_nsfw
-    r.turbo = req.turbo
-    r.use_full_precision = req.use_full_precision
-    r.save_to_disk_path = req.save_to_disk_path
-    r.use_upscale: str = req.use_upscale
-    r.use_face_correction = req.use_face_correction
-    r.use_stable_diffusion_model = req.use_stable_diffusion_model
-    r.use_vae_model = req.use_vae_model
-    r.use_hypernetwork_model = req.use_hypernetwork_model
-    r.hypernetwork_strength = req.hypernetwork_strength
-    r.show_only_filtered_image = req.show_only_filtered_image
-    r.output_format = req.output_format
-    r.output_quality = req.output_quality
-
-    r.stream_progress_updates = True # the underlying implementation only supports streaming
-    r.stream_image_progress = req.stream_image_progress
-
-    if not req.stream_progress_updates:
-        r.stream_image_progress = False
-
-    new_task = RenderTask(r)
+    new_task = RenderTask(render_req, task_data)
     if session.put(new_task, TASK_TTL):
         # Use twice the normal timeout for adding user requests.
         # Tries to force session.put to fail before tasks_queue.put would.
diff --git a/ui/server.py b/ui/server.py
index 258c433d..42bdb0f4 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -14,6 +14,8 @@ from starlette.responses import FileResponse, JSONResponse, StreamingResponse
 from pydantic import BaseModel
 
 from sd_internal import app, model_manager, task_manager
+from sd_internal import TaskData
+from modules.types import GenerateImageRequest
 
 log = logging.getLogger()
 
@@ -22,8 +24,6 @@ log.info(f'started at {datetime.datetime.now():%x %X}')
 
 server_api = FastAPI()
 
-# don't show access log entries for URLs that start with the given prefix
-ACCESS_LOG_SUPPRESS_PATH_PREFIXES = ['/ping', '/image', '/modifier-thumbnails']
 NOCACHE_HEADERS={"Cache-Control": "no-cache, no-store, must-revalidate", "Pragma": "no-cache", "Expires": "0"}
 
 class NoCacheStaticFiles(StaticFiles):
@@ -43,17 +43,6 @@ class SetAppConfigRequest(BaseModel):
     listen_port: int = None
     test_sd2: bool = None
 
-class LogSuppressFilter(logging.Filter):
-    def filter(self, record: logging.LogRecord) -> bool:
-        path = record.getMessage()
-        for prefix in ACCESS_LOG_SUPPRESS_PATH_PREFIXES:
-            if path.find(prefix) != -1:
-                return False
-        return True
-
-# don't log certain requests
-logging.getLogger('uvicorn.access').addFilter(LogSuppressFilter())
-
 server_api.mount('/media', NoCacheStaticFiles(directory=os.path.join(app.SD_UI_DIR, 'media')), name="media")
 
 for plugins_dir, dir_prefix in app.UI_PLUGINS_SOURCES:
@@ -137,20 +126,18 @@ def ping(session_id:str=None):
     return JSONResponse(response, headers=NOCACHE_HEADERS)
 
 @server_api.post('/render')
-def render(req : task_manager.ImageRequest):
+def render(req: dict):
     try:
-        app.save_model_to_config(req.use_stable_diffusion_model, req.use_vae_model, req.use_hypernetwork_model)
+        # separate out the request data into rendering and task-specific data
+        render_req: GenerateImageRequest = GenerateImageRequest.parse_obj(req)
+        task_data: TaskData = TaskData.parse_obj(req)
 
-        # resolve the model paths to use
-        req.use_stable_diffusion_model = model_manager.resolve_model_to_use(req.use_stable_diffusion_model, model_type='stable-diffusion')
-        req.use_vae_model = model_manager.resolve_model_to_use(req.use_vae_model, model_type='vae')
-        req.use_hypernetwork_model = model_manager.resolve_model_to_use(req.use_hypernetwork_model, model_type='hypernetwork')
+        render_req.init_image_mask = req.get('mask') # hack: will rename this in the HTTP API in a future revision
 
-        if req.use_face_correction: req.use_face_correction = model_manager.resolve_model_to_use(req.use_face_correction, 'gfpgan')
-        if req.use_upscale: req.use_upscale = model_manager.resolve_model_to_use(req.use_upscale, 'gfpgan')
+        app.save_model_to_config(task_data.use_stable_diffusion_model, task_data.use_vae_model, task_data.use_hypernetwork_model)
 
         # enqueue the task
-        new_task = task_manager.render(req)
+        new_task = task_manager.render(render_req, task_data)
         response = {
             'status': str(task_manager.current_state), 
             'queue': len(task_manager.tasks_queue),

From 0aa79685035559e513ee54bb95febedf2a6cee39 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sun, 11 Dec 2022 19:34:07 +0530
Subject: [PATCH 21/74] Move color correction to diffusionkit; Rename color
 correction to 'Preserve color profile'

---
 ui/index.html              |  2 +-
 ui/media/js/main.js        |  6 +++---
 ui/sd_internal/runtime2.py | 18 ++----------------
 3 files changed, 6 insertions(+), 20 deletions(-)

diff --git a/ui/index.html b/ui/index.html
index 30648424..0273b574 100644
--- a/ui/index.html
+++ b/ui/index.html
@@ -213,7 +213,7 @@
                     <div><ul>
                     <li><b class="settings-subheader">Render Settings</b></li>
                     <li class="pl-5"><input id="stream_image_progress" name="stream_image_progress" type="checkbox"> <label for="stream_image_progress">Show a live preview <small>(uses more VRAM, slower images)</small></label></li>
-                    <li id="apply_color_correction_setting" class="pl-5"><input id="apply_color_correction" name="apply_color_correction" type="checkbox"> <label for="apply_color_correction">Apply color correction <small>(helps during inpainting)</small></label></li>
+                    <li id="apply_color_correction_setting" class="pl-5"><input id="apply_color_correction" name="apply_color_correction" type="checkbox"> <label for="apply_color_correction">Preserve color profile <small>(helps during inpainting)</small></label></li>
                     <li class="pl-5"><input id="use_face_correction" name="use_face_correction" type="checkbox"> <label for="use_face_correction">Fix incorrect faces and eyes <small>(uses GFPGAN)</small></label></li>
                     <li class="pl-5">
                         <input id="use_upscale" name="use_upscale" type="checkbox"> <label for="use_upscale">Upscale image by 4x with </label>
diff --git a/ui/media/js/main.js b/ui/media/js/main.js
index e058f9e9..6e00f8c0 100644
--- a/ui/media/js/main.js
+++ b/ui/media/js/main.js
@@ -761,8 +761,8 @@ function createTask(task) {
         taskConfig += `, <b>Hypernetwork:</b> ${task.reqBody.use_hypernetwork_model}`
         taskConfig += `, <b>Hypernetwork Strength:</b> ${task.reqBody.hypernetwork_strength}`
     }
-    if (task.reqBody.apply_color_correction) {
-        taskConfig += `, <b>Color Correction:</b> true`
+    if (task.reqBody.preserve_init_image_color_profile) {
+        taskConfig += `, <b>Preserve Color Profile:</b> true`
     }
 
     let taskEntry = document.createElement('div')
@@ -871,7 +871,7 @@ function getCurrentUserRequest() {
         if (maskSetting.checked) {
             newTask.reqBody.mask = imageInpainter.getImg()
         }
-        newTask.reqBody.apply_color_correction = applyColorCorrectionField.checked
+        newTask.reqBody.preserve_init_image_color_profile = applyColorCorrectionField.checked
         newTask.reqBody.sampler = 'ddim'
     } else {
         newTask.reqBody.sampler = samplerField.value
diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index 434f489b..0e1efc2c 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -62,10 +62,8 @@ def reload_models_if_necessary(task_data: TaskData):
         if thread_data.model_paths.get(model_type) != model_path_in_req:
             thread_data.model_paths[model_type] = model_path_in_req
 
-            if thread_data.model_paths[model_type] is not None:
-                model_loader.load_model(thread_data, model_type)
-            else:
-                model_loader.unload_model(thread_data, model_type)
+            action_fn = model_loader.unload_model if thread_data.model_paths[model_type] is None else model_loader.load_model
+            action_fn(thread_data, model_type)
 
 def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
     try:
@@ -94,7 +92,6 @@ def _make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_q
     print(metadata)
 
     images, user_stopped = generate_images(req, data_queue, task_temp_images, step_callback, task_data.stream_image_progress)
-    images = apply_color_correction(req, images, user_stopped)
     images = apply_filters(task_data, images, user_stopped, task_data.show_only_filtered_image)
 
     if task_data.save_to_disk_path is not None:
@@ -139,17 +136,6 @@ def generate_images(req: GenerateImageRequest, data_queue: queue.Queue, task_tem
 
     return images, user_stopped
 
-def apply_color_correction(req: GenerateImageRequest, images: list, user_stopped):
-    if user_stopped or req.init_image is None or not req.apply_color_correction:
-        return images
-
-    for i, img_info in enumerate(images):
-        img, seed, filtered = img_info
-        img = image_utils.apply_color_correction(orig_image=req.init_image, image_to_correct=img)
-        images[i] = (img, seed, filtered)
-
-    return images
-
 def apply_filters(task_data: TaskData, images: list, user_stopped, show_only_filtered_image):
     if user_stopped or (task_data.use_face_correction is None and task_data.use_upscale is None):
         return images

From 97919c7e87399b5dc017efae1a83b6f009935ef3 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sun, 11 Dec 2022 19:58:12 +0530
Subject: [PATCH 22/74] Simplify the runtime code

---
 ui/sd_internal/model_manager.py | 14 +++++++++++++
 ui/sd_internal/runtime2.py      | 36 +++++----------------------------
 ui/sd_internal/task_manager.py  |  7 ++++---
 3 files changed, 23 insertions(+), 34 deletions(-)

diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index 2129af3d..3d68494f 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -4,6 +4,8 @@ import picklescan.scanner
 import rich
 
 from sd_internal import app
+from modules import model_loader
+from modules.types import Context
 
 log = logging.getLogger()
 
@@ -30,6 +32,18 @@ def init():
     make_model_folders()
     getModels() # run this once, to cache the picklescan results
 
+def load_default_models(context: Context):
+    # init default model paths
+    for model_type in KNOWN_MODEL_TYPES:
+        context.model_paths[model_type] = resolve_model_to_use(model_type=model_type)
+
+    # load mandatory models
+    model_loader.load_model(context, 'stable-diffusion')
+
+def unload_all(context: Context):
+    for model_type in KNOWN_MODEL_TYPES:
+        model_loader.unload_model(context, model_type)
+
 def resolve_model_to_use(model_name:str=None, model_type:str=None):
     model_extensions = MODEL_EXTENSIONS.get(model_type, [])
     default_models = DEFAULT_MODELS.get(model_type, [])
diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index 0e1efc2c..399ba960 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -33,18 +33,6 @@ def init(device):
 
     device_manager.device_init(thread_data, device)
 
-def destroy():
-    for model_type in model_manager.KNOWN_MODEL_TYPES:
-        model_loader.unload_model(thread_data, model_type)
-
-def load_default_models():
-    # init default model paths
-    for model_type in model_manager.KNOWN_MODEL_TYPES:
-        thread_data.model_paths[model_type] = model_manager.resolve_model_to_use(model_type=model_type)
-
-    # load mandatory models
-    model_loader.load_model(thread_data, 'stable-diffusion')
-
 def reload_models_if_necessary(task_data: TaskData):
     model_paths_in_req = (
         ('hypernetwork', task_data.use_hypernetwork_model),
@@ -67,14 +55,6 @@ def reload_models_if_necessary(task_data: TaskData):
 
 def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
     try:
-        # resolve the model paths to use
-        resolve_model_paths(task_data)
-
-        # convert init image to PIL.Image
-        req.init_image = image_utils.base64_str_to_img(req.init_image) if req.init_image is not None else None
-        req.init_image_mask = image_utils.base64_str_to_img(req.init_image_mask) if req.init_image_mask is not None else None
-
-        # generate
         return _make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
     except Exception as e:
         log.error(traceback.format_exc())
@@ -86,17 +66,12 @@ def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queu
         raise e
 
 def _make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
-    metadata = req.dict()
-    del metadata['init_image']
-    del metadata['init_image_mask']
-    print(metadata)
-
     images, user_stopped = generate_images(req, data_queue, task_temp_images, step_callback, task_data.stream_image_progress)
     images = apply_filters(task_data, images, user_stopped, task_data.show_only_filtered_image)
 
     if task_data.save_to_disk_path is not None:
         out_path = os.path.join(task_data.save_to_disk_path, filename_regex.sub('_', task_data.session_id))
-        save_images(images, out_path, metadata=metadata, show_only_filtered_image=task_data.show_only_filtered_image)
+        save_images(images, out_path, metadata=req.to_metadata(), show_only_filtered_image=task_data.show_only_filtered_image)
 
     res = Response(req, task_data, images=construct_response(images))
     res = res.json()
@@ -114,6 +89,7 @@ def resolve_model_paths(task_data: TaskData):
     if task_data.use_upscale: task_data.use_upscale = model_manager.resolve_model_to_use(task_data.use_upscale, 'gfpgan')
 
 def generate_images(req: GenerateImageRequest, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
+    log.info(req.to_metadata())
     thread_data.temp_images.clear()
 
     image_generator.on_image_step = make_step_callback(req, data_queue, task_temp_images, step_callback, stream_image_progress)
@@ -125,13 +101,11 @@ def generate_images(req: GenerateImageRequest, data_queue: queue.Queue, task_tem
         images = []
         user_stopped = True
         if thread_data.partial_x_samples is not None:
-            for i in range(req.num_outputs):
-                images[i] = image_utils.latent_to_img(thread_data, thread_data.partial_x_samples[i].unsqueeze(0))
-
-        thread_data.partial_x_samples = None
+            images = image_utils.latent_samples_to_images(thread_data, thread_data.partial_x_samples)
+            thread_data.partial_x_samples = None
     finally:
         model_loader.gc(thread_data)
-    
+
     images = [(image, req.seed + i, False) for i, image in enumerate(images)]
 
     return images, user_stopped
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 3ec1b99d..c167a5f9 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -219,7 +219,7 @@ def thread_get_next_task():
 def thread_render(device):
     global current_state, current_state_error
 
-    from sd_internal import runtime2
+    from sd_internal import runtime2, model_manager
     try:
         runtime2.init(device)
     except Exception as e:
@@ -235,7 +235,7 @@ def thread_render(device):
         'alive': True
     }
 
-    runtime2.load_default_models()
+    model_manager.load_default_models(runtime2.thread_data)
     current_state = ServerStates.Online
 
     while True:
@@ -243,7 +243,7 @@ def thread_render(device):
         task_cache.clean()
         if not weak_thread_data[threading.current_thread()]['alive']:
             log.info(f'Shutting down thread for device {runtime2.thread_data.device}')
-            runtime2.destroy()
+            model_manager.unload_all(runtime2.thread_data)
             return
         if isinstance(current_state_error, SystemExit):
             current_state = ServerStates.Unavailable
@@ -280,6 +280,7 @@ def thread_render(device):
             runtime2.reload_models_if_necessary(task.task_data)
 
             current_state = ServerStates.Rendering
+            runtime2.resolve_model_paths(task.task_data)
             task.response = runtime2.make_images(task.render_request, task.task_data, task.buffer_queue, task.temp_images, step_callback)
             # Before looping back to the generator, mark cache as still alive.
             task_cache.keep(id(task), TASK_TTL)

From 096556d8c93615f5a346735cde5ba5ed8d3be733 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sun, 11 Dec 2022 20:13:44 +0530
Subject: [PATCH 23/74] Move away the remaining model-related code to the
 model_manager

---
 ui/sd_internal/model_manager.py | 30 +++++++++++++++++++++++++++++-
 ui/sd_internal/runtime2.py      | 31 +------------------------------
 ui/sd_internal/task_manager.py  |  4 ++--
 3 files changed, 32 insertions(+), 33 deletions(-)

diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index 3d68494f..ea624322 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -3,7 +3,7 @@ import logging
 import picklescan.scanner
 import rich
 
-from sd_internal import app
+from sd_internal import app, TaskData
 from modules import model_loader
 from modules.types import Context
 
@@ -88,6 +88,34 @@ def resolve_model_to_use(model_name:str=None, model_type:str=None):
 
     return None
 
+def reload_models_if_necessary(context: Context, task_data: TaskData):
+    model_paths_in_req = (
+        ('hypernetwork', task_data.use_hypernetwork_model),
+        ('gfpgan', task_data.use_face_correction),
+        ('realesrgan', task_data.use_upscale),
+    )
+
+    if context.model_paths.get('stable-diffusion') != task_data.use_stable_diffusion_model or context.model_paths.get('vae') != task_data.use_vae_model:
+        context.model_paths['stable-diffusion'] = task_data.use_stable_diffusion_model
+        context.model_paths['vae'] = task_data.use_vae_model
+
+        model_loader.load_model(context, 'stable-diffusion')
+
+    for model_type, model_path_in_req in model_paths_in_req:
+        if context.model_paths.get(model_type) != model_path_in_req:
+            context.model_paths[model_type] = model_path_in_req
+
+            action_fn = model_loader.unload_model if context.model_paths[model_type] is None else model_loader.load_model
+            action_fn(context, model_type)
+
+def resolve_model_paths(task_data: TaskData):
+    task_data.use_stable_diffusion_model = resolve_model_to_use(task_data.use_stable_diffusion_model, model_type='stable-diffusion')
+    task_data.use_vae_model = resolve_model_to_use(task_data.use_vae_model, model_type='vae')
+    task_data.use_hypernetwork_model = resolve_model_to_use(task_data.use_hypernetwork_model, model_type='hypernetwork')
+
+    if task_data.use_face_correction: task_data.use_face_correction = resolve_model_to_use(task_data.use_face_correction, 'gfpgan')
+    if task_data.use_upscale: task_data.use_upscale = resolve_model_to_use(task_data.use_upscale, 'gfpgan')
+
 def make_model_folders():
     for model_type in KNOWN_MODEL_TYPES:
         model_dir_path = os.path.join(app.MODELS_DIR, model_type)
diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/runtime2.py
index 399ba960..1f2e9d27 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/runtime2.py
@@ -1,4 +1,3 @@
-import threading
 import queue
 import time
 import json
@@ -8,7 +7,7 @@ import re
 import traceback
 import logging
 
-from sd_internal import device_manager, model_manager
+from sd_internal import device_manager
 from sd_internal import TaskData, Response, Image as ResponseImage, UserInitiatedStop
 
 from modules import model_loader, image_generator, image_utils, filters as image_filters
@@ -33,26 +32,6 @@ def init(device):
 
     device_manager.device_init(thread_data, device)
 
-def reload_models_if_necessary(task_data: TaskData):
-    model_paths_in_req = (
-        ('hypernetwork', task_data.use_hypernetwork_model),
-        ('gfpgan', task_data.use_face_correction),
-        ('realesrgan', task_data.use_upscale),
-    )
-
-    if thread_data.model_paths.get('stable-diffusion') != task_data.use_stable_diffusion_model or thread_data.model_paths.get('vae') != task_data.use_vae_model:
-        thread_data.model_paths['stable-diffusion'] = task_data.use_stable_diffusion_model
-        thread_data.model_paths['vae'] = task_data.use_vae_model
-
-        model_loader.load_model(thread_data, 'stable-diffusion')
-
-    for model_type, model_path_in_req in model_paths_in_req:
-        if thread_data.model_paths.get(model_type) != model_path_in_req:
-            thread_data.model_paths[model_type] = model_path_in_req
-
-            action_fn = model_loader.unload_model if thread_data.model_paths[model_type] is None else model_loader.load_model
-            action_fn(thread_data, model_type)
-
 def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
     try:
         return _make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
@@ -80,14 +59,6 @@ def _make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_q
 
     return res
 
-def resolve_model_paths(task_data: TaskData):
-    task_data.use_stable_diffusion_model = model_manager.resolve_model_to_use(task_data.use_stable_diffusion_model, model_type='stable-diffusion')
-    task_data.use_vae_model = model_manager.resolve_model_to_use(task_data.use_vae_model, model_type='vae')
-    task_data.use_hypernetwork_model = model_manager.resolve_model_to_use(task_data.use_hypernetwork_model, model_type='hypernetwork')
-
-    if task_data.use_face_correction: task_data.use_face_correction = model_manager.resolve_model_to_use(task_data.use_face_correction, 'gfpgan')
-    if task_data.use_upscale: task_data.use_upscale = model_manager.resolve_model_to_use(task_data.use_upscale, 'gfpgan')
-
 def generate_images(req: GenerateImageRequest, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
     log.info(req.to_metadata())
     thread_data.temp_images.clear()
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index c167a5f9..5e6abce2 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -277,10 +277,10 @@ def thread_render(device):
                         log.info(f'Session {task.task_data.session_id} sent cancel signal for task {id(task)}')
 
             current_state = ServerStates.LoadingModel
-            runtime2.reload_models_if_necessary(task.task_data)
+            model_manager.resolve_model_paths(task.task_data)
+            model_manager.reload_models_if_necessary(runtime2.thread_data, task.task_data)
 
             current_state = ServerStates.Rendering
-            runtime2.resolve_model_paths(task.task_data)
             task.response = runtime2.make_images(task.render_request, task.task_data, task.buffer_queue, task.temp_images, step_callback)
             # Before looping back to the generator, mark cache as still alive.
             task_cache.keep(id(task), TASK_TTL)

From 1a5b6ef2601f8c097c3147c08c634f7515e3c438 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sun, 11 Dec 2022 20:21:25 +0530
Subject: [PATCH 24/74] Rename runtime2.py to renderer.py; Will remove the old
 runtime soon

---
 ui/sd_internal/{runtime2.py => renderer.py} | 34 ++++++++++-----------
 ui/sd_internal/task_manager.py              | 32 +++++++++----------
 2 files changed, 33 insertions(+), 33 deletions(-)
 rename ui/sd_internal/{runtime2.py => renderer.py} (87%)

diff --git a/ui/sd_internal/runtime2.py b/ui/sd_internal/renderer.py
similarity index 87%
rename from ui/sd_internal/runtime2.py
rename to ui/sd_internal/renderer.py
index 1f2e9d27..645fdd00 100644
--- a/ui/sd_internal/runtime2.py
+++ b/ui/sd_internal/renderer.py
@@ -15,7 +15,7 @@ from modules.types import Context, GenerateImageRequest
 
 log = logging.getLogger()
 
-thread_data = Context()
+context = Context() # thread-local
 '''
 runtime data (bound locally to this thread), for e.g. device, references to loaded models, optimization flags etc
 '''
@@ -24,13 +24,13 @@ filename_regex = re.compile('[^a-zA-Z0-9]')
 
 def init(device):
     '''
-    Initializes the fields that will be bound to this runtime's thread_data, and sets the current torch device
+    Initializes the fields that will be bound to this runtime's context, and sets the current torch device
     '''
-    thread_data.stop_processing = False
-    thread_data.temp_images = {}
-    thread_data.partial_x_samples = None
+    context.stop_processing = False
+    context.temp_images = {}
+    context.partial_x_samples = None
 
-    device_manager.device_init(thread_data, device)
+    device_manager.device_init(context, device)
 
 def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
     try:
@@ -61,21 +61,21 @@ def _make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_q
 
 def generate_images(req: GenerateImageRequest, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
     log.info(req.to_metadata())
-    thread_data.temp_images.clear()
+    context.temp_images.clear()
 
     image_generator.on_image_step = make_step_callback(req, data_queue, task_temp_images, step_callback, stream_image_progress)
 
     try:
-        images = image_generator.make_images(context=thread_data, req=req)
+        images = image_generator.make_images(context=context, req=req)
         user_stopped = False
     except UserInitiatedStop:
         images = []
         user_stopped = True
-        if thread_data.partial_x_samples is not None:
-            images = image_utils.latent_samples_to_images(thread_data, thread_data.partial_x_samples)
-            thread_data.partial_x_samples = None
+        if context.partial_x_samples is not None:
+            images = image_utils.latent_samples_to_images(context, context.partial_x_samples)
+            context.partial_x_samples = None
     finally:
-        model_loader.gc(thread_data)
+        model_loader.gc(context)
 
     images = [(image, req.seed + i, False) for i, image in enumerate(images)]
 
@@ -92,7 +92,7 @@ def apply_filters(task_data: TaskData, images: list, user_stopped, show_only_fil
     filtered_images = []
     for img, seed, _ in images:
         for filter_fn in filters:
-            img = filter_fn(thread_data, img)
+            img = filter_fn(context, img)
 
         filtered_images.append((img, seed, True))
 
@@ -145,12 +145,12 @@ def make_step_callback(req: GenerateImageRequest, task_data: TaskData, data_queu
     def update_temp_img(x_samples, task_temp_images: list):
         partial_images = []
         for i in range(req.num_outputs):
-            img = image_utils.latent_to_img(thread_data, x_samples[i].unsqueeze(0))
+            img = image_utils.latent_to_img(context, x_samples[i].unsqueeze(0))
             buf = image_utils.img_to_buffer(img, output_format='JPEG')
 
             del img
 
-            thread_data.temp_images[f"{task_data.request_id}/{i}"] = buf
+            context.temp_images[f"{task_data.request_id}/{i}"] = buf
             task_temp_images[i] = buf
             partial_images.append({'path': f"/image/tmp/{task_data.request_id}/{i}"})
         return partial_images
@@ -158,7 +158,7 @@ def make_step_callback(req: GenerateImageRequest, task_data: TaskData, data_queu
     def on_image_step(x_samples, i):
         nonlocal last_callback_time
 
-        thread_data.partial_x_samples = x_samples
+        context.partial_x_samples = x_samples
         step_time = time.time() - last_callback_time if last_callback_time != -1 else -1
         last_callback_time = time.time()
 
@@ -171,7 +171,7 @@ def make_step_callback(req: GenerateImageRequest, task_data: TaskData, data_queu
 
         step_callback()
 
-        if thread_data.stop_processing:
+        if context.stop_processing:
             raise UserInitiatedStop("User requested that we stop processing")
 
     return on_image_step
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 5e6abce2..4810584b 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -186,9 +186,9 @@ class SessionState():
         return True
 
 def thread_get_next_task():
-    from sd_internal import runtime2
+    from sd_internal import renderer
     if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
-        log.warn(f'Render thread on device: {runtime2.thread_data.device} failed to acquire manager lock.')
+        log.warn(f'Render thread on device: {renderer.context.device} failed to acquire manager lock.')
         return None
     if len(tasks_queue) <= 0:
         manager_lock.release()
@@ -196,7 +196,7 @@ def thread_get_next_task():
     task = None
     try:  # Select a render task.
         for queued_task in tasks_queue:
-            if queued_task.render_device and runtime2.thread_data.device != queued_task.render_device:
+            if queued_task.render_device and renderer.context.device != queued_task.render_device:
                 # Is asking for a specific render device.
                 if is_alive(queued_task.render_device) > 0:
                     continue  # requested device alive, skip current one.
@@ -205,7 +205,7 @@ def thread_get_next_task():
                     queued_task.error = Exception(queued_task.render_device + ' is not currently active.')
                     task = queued_task
                     break
-            if not queued_task.render_device and runtime2.thread_data.device == 'cpu' and is_alive() > 1:
+            if not queued_task.render_device and renderer.context.device == 'cpu' and is_alive() > 1:
                 # not asking for any specific devices, cpu want to grab task but other render devices are alive.
                 continue  # Skip Tasks, don't run on CPU unless there is nothing else or user asked for it.
             task = queued_task
@@ -219,9 +219,9 @@ def thread_get_next_task():
 def thread_render(device):
     global current_state, current_state_error
 
-    from sd_internal import runtime2, model_manager
+    from sd_internal import renderer, model_manager
     try:
-        runtime2.init(device)
+        renderer.init(device)
     except Exception as e:
         log.error(traceback.format_exc())
         weak_thread_data[threading.current_thread()] = {
@@ -230,20 +230,20 @@ def thread_render(device):
         return
 
     weak_thread_data[threading.current_thread()] = {
-        'device': runtime2.thread_data.device,
-        'device_name': runtime2.thread_data.device_name,
+        'device': renderer.context.device,
+        'device_name': renderer.context.device_name,
         'alive': True
     }
 
-    model_manager.load_default_models(runtime2.thread_data)
+    model_manager.load_default_models(renderer.context)
     current_state = ServerStates.Online
 
     while True:
         session_cache.clean()
         task_cache.clean()
         if not weak_thread_data[threading.current_thread()]['alive']:
-            log.info(f'Shutting down thread for device {runtime2.thread_data.device}')
-            model_manager.unload_all(runtime2.thread_data)
+            log.info(f'Shutting down thread for device {renderer.context.device}')
+            model_manager.unload_all(renderer.context)
             return
         if isinstance(current_state_error, SystemExit):
             current_state = ServerStates.Unavailable
@@ -263,14 +263,14 @@ def thread_render(device):
             task.response = {"status": 'failed', "detail": str(task.error)}
             task.buffer_queue.put(json.dumps(task.response))
             continue
-        log.info(f'Session {task.task_data.session_id} starting task {id(task)} on {runtime2.thread_data.device_name}')
+        log.info(f'Session {task.task_data.session_id} starting task {id(task)} on {renderer.context.device_name}')
         if not task.lock.acquire(blocking=False): raise Exception('Got locked task from queue.')
         try:
             def step_callback():
                 global current_state_error
 
                 if isinstance(current_state_error, SystemExit) or isinstance(current_state_error, StopAsyncIteration) or isinstance(task.error, StopAsyncIteration):
-                    runtime2.thread_data.stop_processing = True
+                    renderer.context.stop_processing = True
                     if isinstance(current_state_error, StopAsyncIteration):
                         task.error = current_state_error
                         current_state_error = None
@@ -278,10 +278,10 @@ def thread_render(device):
 
             current_state = ServerStates.LoadingModel
             model_manager.resolve_model_paths(task.task_data)
-            model_manager.reload_models_if_necessary(runtime2.thread_data, task.task_data)
+            model_manager.reload_models_if_necessary(renderer.context, task.task_data)
 
             current_state = ServerStates.Rendering
-            task.response = runtime2.make_images(task.render_request, task.task_data, task.buffer_queue, task.temp_images, step_callback)
+            task.response = renderer.make_images(task.render_request, task.task_data, task.buffer_queue, task.temp_images, step_callback)
             # Before looping back to the generator, mark cache as still alive.
             task_cache.keep(id(task), TASK_TTL)
             session_cache.keep(task.task_data.session_id, TASK_TTL)
@@ -299,7 +299,7 @@ def thread_render(device):
         elif task.error is not None:
             log.info(f'Session {task.task_data.session_id} task {id(task)} failed!')
         else:
-            log.info(f'Session {task.task_data.session_id} task {id(task)} completed by {runtime2.thread_data.device_name}.')
+            log.info(f'Session {task.task_data.session_id} task {id(task)} completed by {renderer.context.device_name}.')
         current_state = ServerStates.Online
 
 def get_cached_task(task_id:str, update_ttl:bool=False):

From e45cbbf1cab201bafa4c9985b29359325c520ae1 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sun, 11 Dec 2022 20:42:31 +0530
Subject: [PATCH 25/74] Use the turbo setting if requested

---
 ui/sd_internal/model_manager.py | 9 +++++++++
 ui/sd_internal/task_manager.py  | 1 +
 2 files changed, 10 insertions(+)

diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index ea624322..0cc9414c 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -37,6 +37,9 @@ def load_default_models(context: Context):
     for model_type in KNOWN_MODEL_TYPES:
         context.model_paths[model_type] = resolve_model_to_use(model_type=model_type)
 
+    # disable TURBO initially (this should be read from the config eventually)
+    context.vram_optimizations -= {'TURBO'}
+
     # load mandatory models
     model_loader.load_model(context, 'stable-diffusion')
 
@@ -116,6 +119,12 @@ def resolve_model_paths(task_data: TaskData):
     if task_data.use_face_correction: task_data.use_face_correction = resolve_model_to_use(task_data.use_face_correction, 'gfpgan')
     if task_data.use_upscale: task_data.use_upscale = resolve_model_to_use(task_data.use_upscale, 'gfpgan')
 
+def set_vram_optimizations(context: Context, task_data: TaskData):
+    if task_data.turbo:
+        context.vram_optimizations += {'TURBO'}
+    else:
+        context.vram_optimizations -= {'TURBO'}
+
 def make_model_folders():
     for model_type in KNOWN_MODEL_TYPES:
         model_dir_path = os.path.join(app.MODELS_DIR, model_type)
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 4810584b..a6d4dadd 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -278,6 +278,7 @@ def thread_render(device):
 
             current_state = ServerStates.LoadingModel
             model_manager.resolve_model_paths(task.task_data)
+            model_manager.set_vram_optimizations(renderer.context, task.task_data)
             model_manager.reload_models_if_necessary(renderer.context, task.task_data)
 
             current_state = ServerStates.Rendering

From b57649828dddeeea14de2b4e25090d93b0673087 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Mon, 12 Dec 2022 14:01:47 +0530
Subject: [PATCH 26/74] Refactor the save-to-disk code, moving parts of it to
 diffusionkit

---
 ui/sd_internal/__init__.py |   3 +
 ui/sd_internal/renderer.py | 110 +++++++++++++++++++++----------------
 2 files changed, 67 insertions(+), 46 deletions(-)

diff --git a/ui/sd_internal/__init__.py b/ui/sd_internal/__init__.py
index a06220ca..f0710652 100644
--- a/ui/sd_internal/__init__.py
+++ b/ui/sd_internal/__init__.py
@@ -7,14 +7,17 @@ class TaskData(BaseModel):
     session_id: str = "session"
     save_to_disk_path: str = None
     turbo: bool = True
+
     use_face_correction: str = None # or "GFPGANv1.3"
     use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
     use_stable_diffusion_model: str = "sd-v1-4"
     use_vae_model: str = None
     use_hypernetwork_model: str = None
+
     show_only_filtered_image: bool = False
     output_format: str = "jpeg" # or "png"
     output_quality: int = 75
+    metadata_output_format: str = "txt" # or "json"
     stream_image_progress: bool = False
 
 class Image:
diff --git a/ui/sd_internal/renderer.py b/ui/sd_internal/renderer.py
index 645fdd00..440f2bf2 100644
--- a/ui/sd_internal/renderer.py
+++ b/ui/sd_internal/renderer.py
@@ -10,7 +10,7 @@ import logging
 from sd_internal import device_manager
 from sd_internal import TaskData, Response, Image as ResponseImage, UserInitiatedStop
 
-from modules import model_loader, image_generator, image_utils, filters as image_filters
+from modules import model_loader, image_generator, image_utils, filters as image_filters, data_utils
 from modules.types import Context, GenerateImageRequest
 
 log = logging.getLogger()
@@ -33,8 +33,18 @@ def init(device):
     device_manager.device_init(context, device)
 
 def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
+    log.info(f'request: {req.dict()}')
+    log.info(f'task data: {task_data.dict()}')
+
     try:
-        return _make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
+        images = _make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
+
+        res = Response(req, task_data, images=construct_response(images, task_data, base_seed=req.seed))
+        res = res.json()
+        data_queue.put(json.dumps(res))
+        log.info('Task completed')
+
+        return res
     except Exception as e:
         log.error(traceback.format_exc())
 
@@ -46,21 +56,15 @@ def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queu
 
 def _make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
     images, user_stopped = generate_images(req, data_queue, task_temp_images, step_callback, task_data.stream_image_progress)
-    images = apply_filters(task_data, images, user_stopped, task_data.show_only_filtered_image)
+    filtered_images = apply_filters(task_data, images, user_stopped)
 
     if task_data.save_to_disk_path is not None:
-        out_path = os.path.join(task_data.save_to_disk_path, filename_regex.sub('_', task_data.session_id))
-        save_images(images, out_path, metadata=req.to_metadata(), show_only_filtered_image=task_data.show_only_filtered_image)
+        save_folder_path = os.path.join(task_data.save_to_disk_path, filename_regex.sub('_', task_data.session_id))
+        save_to_disk(images, filtered_images, save_folder_path, req, task_data)
 
-    res = Response(req, task_data, images=construct_response(images))
-    res = res.json()
-    data_queue.put(json.dumps(res))
-    log.info('Task completed')
-
-    return res
+    return filtered_images if task_data.show_only_filtered_image else images + filtered_images
 
 def generate_images(req: GenerateImageRequest, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
-    log.info(req.to_metadata())
     context.temp_images.clear()
 
     image_generator.on_image_step = make_step_callback(req, data_queue, task_temp_images, step_callback, stream_image_progress)
@@ -77,11 +81,9 @@ def generate_images(req: GenerateImageRequest, data_queue: queue.Queue, task_tem
     finally:
         model_loader.gc(context)
 
-    images = [(image, req.seed + i, False) for i, image in enumerate(images)]
-
     return images, user_stopped
 
-def apply_filters(task_data: TaskData, images: list, user_stopped, show_only_filtered_image):
+def apply_filters(task_data: TaskData, images: list, user_stopped):
     if user_stopped or (task_data.use_face_correction is None and task_data.use_upscale is None):
         return images
 
@@ -90,52 +92,68 @@ def apply_filters(task_data: TaskData, images: list, user_stopped, show_only_fil
     if 'realesrgan' in task_data.use_face_correction.lower(): filters.append(image_filters.apply_realesrgan)
 
     filtered_images = []
-    for img, seed, _ in images:
+    for img in images:
         for filter_fn in filters:
             img = filter_fn(context, img)
 
-        filtered_images.append((img, seed, True))
-
-    if not show_only_filtered_image:
-        filtered_images = images + filtered_images
+        filtered_images.append(img)
 
     return filtered_images
 
-def save_images(images: list, save_to_disk_path, metadata: dict, show_only_filtered_image):
-    if save_to_disk_path is None:
-        return
+def save_to_disk(images: list, filtered_images: list, save_folder_path, req: GenerateImageRequest, task_data: TaskData):
+    metadata = req.dict()
+    del metadata['init_image']
+    del metadata['init_image_mask']
+    metadata.update({
+        'use_stable_diffusion_model': task_data.use_stable_diffusion_model,
+        'use_vae_model': task_data.use_vae_model,
+        'use_hypernetwork_model': task_data.use_hypernetwork_model,
+        'use_face_correction': task_data.use_face_correction,
+        'use_upscale': task_data.use_upscale,
+    })
 
-    def get_image_id(i):
+    metadata_entries = get_metadata_entries(req, task_data)
+
+    if task_data.show_only_filtered_image or filtered_images == images:
+        data_utils.save_images(filtered_images, save_folder_path, file_name=get_output_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        data_utils.save_metadata(metadata_entries, save_folder_path, file_name=get_output_filename_callback(req), output_format=task_data.metadata_output_format)
+    else:
+        data_utils.save_images(images, save_folder_path, file_name=get_output_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        data_utils.save_images(filtered_images, save_folder_path, file_name=get_output_filename_callback(req, suffix='filtered'), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        data_utils.save_metadata(metadata_entries, save_folder_path, file_name=get_output_filename_callback(req, suffix='filtered'), output_format=task_data.metadata_output_format)
+
+def get_metadata_entries(req: GenerateImageRequest, task_data: TaskData):
+    metadata = req.dict()
+    del metadata['init_image']
+    del metadata['init_image_mask']
+    metadata.update({
+        'use_stable_diffusion_model': task_data.use_stable_diffusion_model,
+        'use_vae_model': task_data.use_vae_model,
+        'use_hypernetwork_model': task_data.use_hypernetwork_model,
+        'use_face_correction': task_data.use_face_correction,
+        'use_upscale': task_data.use_upscale,
+    })
+
+    return [metadata.copy().update({'seed': req.seed + i}) for i in range(req.num_outputs)]
+
+def get_output_filename_callback(req: GenerateImageRequest, suffix=None):
+    def make_filename(i):
         img_id = base64.b64encode(int(time.time()+i).to_bytes(8, 'big')).decode() # Generate unique ID based on time.
         img_id = img_id.translate({43:None, 47:None, 61:None})[-8:] # Remove + / = and keep last 8 chars.
-        return img_id
 
-    def get_image_basepath(i):
-        os.makedirs(save_to_disk_path, exist_ok=True)
-        prompt_flattened = filename_regex.sub('_', metadata['prompt'])[:50]
-        return os.path.join(save_to_disk_path, f"{prompt_flattened}_{get_image_id(i)}")
+        prompt_flattened = filename_regex.sub('_', req.prompt)[:50]
+        name = f"{prompt_flattened}_{img_id}"
+        name = name if suffix is None else f'{name}_{suffix}'
+        return name
 
-    for i, img_data in enumerate(images):
-        img, seed, filtered = img_data
-        img_path = get_image_basepath(i)
+    return make_filename
 
-        if not filtered or show_only_filtered_image:
-            img_metadata_path = img_path + '.txt'
-            m = metadata.copy()
-            m['seed'] = seed
-            with open(img_metadata_path, 'w', encoding='utf-8') as f:
-                f.write(m)
-
-        img_path += '_filtered' if filtered else ''
-        img_path += '.' + metadata['output_format']
-        img.save(img_path, quality=metadata['output_quality'])
-
-def construct_response(task_data: TaskData, images: list):
+def construct_response(images: list, task_data: TaskData, base_seed: int):
     return [
         ResponseImage(
             data=image_utils.img_to_base64_str(img, task_data.output_format, task_data.output_quality),
-            seed=seed
-        ) for img, seed, _ in images
+            seed=base_seed + i
+        ) for i, img in enumerate(images)
     ]
 
 def make_step_callback(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):

From d0e50584ea54f37961a3ad1851f3cdf9f435ef99 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Mon, 12 Dec 2022 14:06:20 +0530
Subject: [PATCH 27/74] Expose the metadata format option in the UI

---
 ui/media/js/auto-save.js  |  1 +
 ui/media/js/parameters.js | 13 +++++++++++++
 2 files changed, 14 insertions(+)

diff --git a/ui/media/js/auto-save.js b/ui/media/js/auto-save.js
index df044e2b..44903724 100644
--- a/ui/media/js/auto-save.js
+++ b/ui/media/js/auto-save.js
@@ -38,6 +38,7 @@ const SETTINGS_IDS_LIST = [
     "sound_toggle",
     "turbo",
     "confirm_dangerous_actions",
+    "metadata_output_format",
     "auto_save_settings",
     "apply_color_correction"
 ]
diff --git a/ui/media/js/parameters.js b/ui/media/js/parameters.js
index f326953b..a4167fc3 100644
--- a/ui/media/js/parameters.js
+++ b/ui/media/js/parameters.js
@@ -53,6 +53,19 @@ var PARAMETERS = [
             return `<input id="${parameter.id}" name="${parameter.id}" size="30" disabled>`
         }
     },
+    {
+        id: "metadata_output_format",
+        type: ParameterType.select,
+        label: "Metadata format",
+        note: "the metadata will be saved to disk in this format",
+        default: "txt",
+        options: [
+            {
+                value: "txt",
+                label: "json"
+            }
+        ],
+    },
     {
         id: "sound_toggle",
         type: ParameterType.checkbox,

From 4bbf683d155489a8d757db4555726ddad2be0a89 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Mon, 12 Dec 2022 14:41:36 +0530
Subject: [PATCH 28/74] Minor refactor

---
 ui/sd_internal/renderer.py | 39 ++++++++++++++------------------------
 1 file changed, 14 insertions(+), 25 deletions(-)

diff --git a/ui/sd_internal/renderer.py b/ui/sd_internal/renderer.py
index 440f2bf2..2bf079f5 100644
--- a/ui/sd_internal/renderer.py
+++ b/ui/sd_internal/renderer.py
@@ -101,26 +101,23 @@ def apply_filters(task_data: TaskData, images: list, user_stopped):
     return filtered_images
 
 def save_to_disk(images: list, filtered_images: list, save_folder_path, req: GenerateImageRequest, task_data: TaskData):
-    metadata = req.dict()
-    del metadata['init_image']
-    del metadata['init_image_mask']
-    metadata.update({
-        'use_stable_diffusion_model': task_data.use_stable_diffusion_model,
-        'use_vae_model': task_data.use_vae_model,
-        'use_hypernetwork_model': task_data.use_hypernetwork_model,
-        'use_face_correction': task_data.use_face_correction,
-        'use_upscale': task_data.use_upscale,
-    })
-
     metadata_entries = get_metadata_entries(req, task_data)
 
     if task_data.show_only_filtered_image or filtered_images == images:
-        data_utils.save_images(filtered_images, save_folder_path, file_name=get_output_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
-        data_utils.save_metadata(metadata_entries, save_folder_path, file_name=get_output_filename_callback(req), output_format=task_data.metadata_output_format)
+        data_utils.save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        data_utils.save_metadata(metadata_entries, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.metadata_output_format)
     else:
-        data_utils.save_images(images, save_folder_path, file_name=get_output_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
-        data_utils.save_images(filtered_images, save_folder_path, file_name=get_output_filename_callback(req, suffix='filtered'), output_format=task_data.output_format, output_quality=task_data.output_quality)
-        data_utils.save_metadata(metadata_entries, save_folder_path, file_name=get_output_filename_callback(req, suffix='filtered'), output_format=task_data.metadata_output_format)
+        data_utils.save_images(images, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        data_utils.save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        data_utils.save_metadata(metadata_entries, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.metadata_output_format)
+
+def construct_response(images: list, task_data: TaskData, base_seed: int):
+    return [
+        ResponseImage(
+            data=image_utils.img_to_base64_str(img, task_data.output_format, task_data.output_quality),
+            seed=base_seed + i
+        ) for i, img in enumerate(images)
+    ]
 
 def get_metadata_entries(req: GenerateImageRequest, task_data: TaskData):
     metadata = req.dict()
@@ -136,7 +133,7 @@ def get_metadata_entries(req: GenerateImageRequest, task_data: TaskData):
 
     return [metadata.copy().update({'seed': req.seed + i}) for i in range(req.num_outputs)]
 
-def get_output_filename_callback(req: GenerateImageRequest, suffix=None):
+def make_filename_callback(req: GenerateImageRequest, suffix=None):
     def make_filename(i):
         img_id = base64.b64encode(int(time.time()+i).to_bytes(8, 'big')).decode() # Generate unique ID based on time.
         img_id = img_id.translate({43:None, 47:None, 61:None})[-8:] # Remove + / = and keep last 8 chars.
@@ -148,14 +145,6 @@ def get_output_filename_callback(req: GenerateImageRequest, suffix=None):
 
     return make_filename
 
-def construct_response(images: list, task_data: TaskData, base_seed: int):
-    return [
-        ResponseImage(
-            data=image_utils.img_to_base64_str(img, task_data.output_format, task_data.output_quality),
-            seed=base_seed + i
-        ) for i, img in enumerate(images)
-    ]
-
 def make_step_callback(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
     n_steps = req.num_inference_steps if req.init_image is None else int(req.num_inference_steps * req.prompt_strength)
     last_callback_time = -1

From 6b943f88d19d1fa99abd71bb737379aedf523523 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Mon, 12 Dec 2022 15:18:30 +0530
Subject: [PATCH 29/74] Set uvicorn log level to 'error'

---
 scripts/on_sd_start.bat | 2 +-
 scripts/on_sd_start.sh  | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/scripts/on_sd_start.bat b/scripts/on_sd_start.bat
index 5f1bfcb1..620d0909 100644
--- a/scripts/on_sd_start.bat
+++ b/scripts/on_sd_start.bat
@@ -393,7 +393,7 @@ call python --version
 
 @if NOT DEFINED SD_UI_BIND_PORT set SD_UI_BIND_PORT=9000
 @if NOT DEFINED SD_UI_BIND_IP set SD_UI_BIND_IP=0.0.0.0
-@uvicorn server:server_api --app-dir "%SD_UI_PATH%" --port %SD_UI_BIND_PORT% --host %SD_UI_BIND_IP% --log-level critical
+@uvicorn server:server_api --app-dir "%SD_UI_PATH%" --port %SD_UI_BIND_PORT% --host %SD_UI_BIND_IP% --log-level error
 
 
 @pause
diff --git a/scripts/on_sd_start.sh b/scripts/on_sd_start.sh
index f4f540e7..3e082b81 100755
--- a/scripts/on_sd_start.sh
+++ b/scripts/on_sd_start.sh
@@ -322,6 +322,6 @@ cd ..
 export SD_UI_PATH=`pwd`/ui
 cd stable-diffusion
 
-uvicorn server:server_api --app-dir "$SD_UI_PATH" --port ${SD_UI_BIND_PORT:-9000} --host ${SD_UI_BIND_IP:-0.0.0.0} --log-level critical
+uvicorn server:server_api --app-dir "$SD_UI_PATH" --port ${SD_UI_BIND_PORT:-9000} --host ${SD_UI_BIND_IP:-0.0.0.0} --log-level error
 
 read -p "Press any key to continue"

From ac0961d7d4dca73a8a90f06e91f4b283214f0402 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Mon, 12 Dec 2022 15:18:56 +0530
Subject: [PATCH 30/74] Typos from the refactor

---
 ui/sd_internal/model_manager.py | 4 ++--
 ui/sd_internal/renderer.py      | 6 +++---
 ui/sd_internal/task_manager.py  | 6 ++++--
 3 files changed, 9 insertions(+), 7 deletions(-)

diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index 0cc9414c..f5e8a5c7 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -121,9 +121,9 @@ def resolve_model_paths(task_data: TaskData):
 
 def set_vram_optimizations(context: Context, task_data: TaskData):
     if task_data.turbo:
-        context.vram_optimizations += {'TURBO'}
+        context.vram_optimizations.add('TURBO')
     else:
-        context.vram_optimizations -= {'TURBO'}
+        context.vram_optimizations.remove('TURBO')
 
 def make_model_folders():
     for model_type in KNOWN_MODEL_TYPES:
diff --git a/ui/sd_internal/renderer.py b/ui/sd_internal/renderer.py
index 2bf079f5..aa805ad9 100644
--- a/ui/sd_internal/renderer.py
+++ b/ui/sd_internal/renderer.py
@@ -55,7 +55,7 @@ def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queu
         raise e
 
 def _make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
-    images, user_stopped = generate_images(req, data_queue, task_temp_images, step_callback, task_data.stream_image_progress)
+    images, user_stopped = generate_images(req, task_data, data_queue, task_temp_images, step_callback, task_data.stream_image_progress)
     filtered_images = apply_filters(task_data, images, user_stopped)
 
     if task_data.save_to_disk_path is not None:
@@ -64,10 +64,10 @@ def _make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_q
 
     return filtered_images if task_data.show_only_filtered_image else images + filtered_images
 
-def generate_images(req: GenerateImageRequest, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
+def generate_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
     context.temp_images.clear()
 
-    image_generator.on_image_step = make_step_callback(req, data_queue, task_temp_images, step_callback, stream_image_progress)
+    image_generator.on_image_step = make_step_callback(req, task_data, data_queue, task_temp_images, step_callback, stream_image_progress)
 
     try:
         images = image_generator.make_images(context=context, req=req)
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index a6d4dadd..ef2a4a3b 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -40,12 +40,12 @@ class ServerStates:
 
 class RenderTask(): # Task with output queue and completion lock.
     def __init__(self, req: GenerateImageRequest, task_data: TaskData):
-        req.request_id = id(self)
+        task_data.request_id = id(self)
         self.render_request: GenerateImageRequest = req  # Initial Request
         self.task_data: TaskData = task_data
         self.response: Any = None # Copy of the last reponse
         self.render_device = None # Select the task affinity. (Not used to change active devices).
-        self.temp_images:list = [None] * req.num_outputs * (1 if req.show_only_filtered_image else 2)
+        self.temp_images:list = [None] * req.num_outputs * (1 if task_data.show_only_filtered_image else 2)
         self.error: Exception = None
         self.lock: threading.Lock = threading.Lock() # Locks at task start and unlocks when task is completed
         self.buffer_queue: queue.Queue = queue.Queue() # Queue of JSON string segments
@@ -235,7 +235,9 @@ def thread_render(device):
         'alive': True
     }
 
+    current_state = ServerStates.LoadingModel
     model_manager.load_default_models(renderer.context)
+
     current_state = ServerStates.Online
 
     while True:

From fb32a38d9638fc0bf8868b2849e4c19de36408eb Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Mon, 12 Dec 2022 15:21:02 +0530
Subject: [PATCH 31/74] Rename sampler to sampler_name in the API

---
 ui/index.html            | 4 ++--
 ui/media/js/auto-save.js | 2 +-
 ui/media/js/main.js      | 8 ++++----
 3 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/ui/index.html b/ui/index.html
index 0273b574..612759c0 100644
--- a/ui/index.html
+++ b/ui/index.html
@@ -137,8 +137,8 @@
                         </select>
                     </td></tr>
                     <tr id="hypernetwork_strength_container" class="pl-5"><td><label for="hypernetwork_strength_slider">Hypernetwork Strength:</label></td><td> <input id="hypernetwork_strength_slider" name="hypernetwork_strength_slider" class="editor-slider" value="100" type="range" min="0" max="100"> <input id="hypernetwork_strength" name="hypernetwork_strength" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"><br/></td></tr></span>
-                    <tr id="samplerSelection" class="pl-5"><td><label for="sampler">Sampler:</label></td><td>
-                        <select id="sampler" name="sampler">
+                    <tr id="samplerSelection" class="pl-5"><td><label for="sampler_name">Sampler:</label></td><td>
+                        <select id="sampler_name" name="sampler_name">
                             <option value="plms">plms</option>
                             <option value="ddim">ddim</option>
                             <option value="heun">heun</option>
diff --git a/ui/media/js/auto-save.js b/ui/media/js/auto-save.js
index 44903724..c5826087 100644
--- a/ui/media/js/auto-save.js
+++ b/ui/media/js/auto-save.js
@@ -15,7 +15,7 @@ const SETTINGS_IDS_LIST = [
     "stable_diffusion_model",
     "vae_model",
     "hypernetwork_model",
-    "sampler",
+    "sampler_name",
     "width",
     "height",
     "num_inference_steps",
diff --git a/ui/media/js/main.js b/ui/media/js/main.js
index 6e00f8c0..8d7d9ce3 100644
--- a/ui/media/js/main.js
+++ b/ui/media/js/main.js
@@ -30,7 +30,7 @@ let applyColorCorrectionField = document.querySelector('#apply_color_correction'
 let colorCorrectionSetting = document.querySelector('#apply_color_correction_setting')
 let promptStrengthSlider = document.querySelector('#prompt_strength_slider')
 let promptStrengthField = document.querySelector('#prompt_strength')
-let samplerField = document.querySelector('#sampler')
+let samplerField = document.querySelector('#sampler_name')
 let samplerSelectionContainer = document.querySelector("#samplerSelection")
 let useFaceCorrectionField = document.querySelector("#use_face_correction")
 let useUpscalingField = document.querySelector("#use_upscale")
@@ -741,7 +741,7 @@ function onTaskStart(task) {
 }
 
 function createTask(task) {
-    let taskConfig = `<b>Seed:</b> ${task.seed}, <b>Sampler:</b> ${task.reqBody.sampler}, <b>Inference Steps:</b> ${task.reqBody.num_inference_steps}, <b>Guidance Scale:</b> ${task.reqBody.guidance_scale}, <b>Model:</b> ${task.reqBody.use_stable_diffusion_model}`
+    let taskConfig = `<b>Seed:</b> ${task.seed}, <b>Sampler:</b> ${task.reqBody.sampler_name}, <b>Inference Steps:</b> ${task.reqBody.num_inference_steps}, <b>Guidance Scale:</b> ${task.reqBody.guidance_scale}, <b>Model:</b> ${task.reqBody.use_stable_diffusion_model}`
     if (task.reqBody.use_vae_model.trim() !== '') {
         taskConfig += `, <b>VAE:</b> ${task.reqBody.use_vae_model}`
     }
@@ -872,9 +872,9 @@ function getCurrentUserRequest() {
             newTask.reqBody.mask = imageInpainter.getImg()
         }
         newTask.reqBody.preserve_init_image_color_profile = applyColorCorrectionField.checked
-        newTask.reqBody.sampler = 'ddim'
+        newTask.reqBody.sampler_name = 'ddim'
     } else {
-        newTask.reqBody.sampler = samplerField.value
+        newTask.reqBody.sampler_name = samplerField.value
     }
     if (saveToDiskField.checked && diskPathField.value.trim() !== '') {
         newTask.reqBody.save_to_disk_path = diskPathField.value.trim()

From 07bd580050b9113e061a5c473f14613cc810dc52 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Mon, 12 Dec 2022 15:44:22 +0530
Subject: [PATCH 32/74] Typos

---
 ui/sd_internal/__init__.py |  3 +++
 ui/sd_internal/renderer.py | 12 ++++++++----
 2 files changed, 11 insertions(+), 4 deletions(-)

diff --git a/ui/sd_internal/__init__.py b/ui/sd_internal/__init__.py
index f0710652..7093562a 100644
--- a/ui/sd_internal/__init__.py
+++ b/ui/sd_internal/__init__.py
@@ -48,6 +48,9 @@ class Response:
         self.images = images
 
     def json(self):
+        del self.render_request.init_image
+        del self.render_request.init_image_mask
+
         res = {
             "status": 'succeeded',
             "render_request": self.render_request.dict(),
diff --git a/ui/sd_internal/renderer.py b/ui/sd_internal/renderer.py
index aa805ad9..162b7da0 100644
--- a/ui/sd_internal/renderer.py
+++ b/ui/sd_internal/renderer.py
@@ -33,7 +33,7 @@ def init(device):
     device_manager.device_init(context, device)
 
 def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
-    log.info(f'request: {req.dict()}')
+    log.info(f'request: {get_printable_request(req)}')
     log.info(f'task data: {task_data.dict()}')
 
     try:
@@ -120,9 +120,7 @@ def construct_response(images: list, task_data: TaskData, base_seed: int):
     ]
 
 def get_metadata_entries(req: GenerateImageRequest, task_data: TaskData):
-    metadata = req.dict()
-    del metadata['init_image']
-    del metadata['init_image_mask']
+    metadata = get_printable_request(req)
     metadata.update({
         'use_stable_diffusion_model': task_data.use_stable_diffusion_model,
         'use_vae_model': task_data.use_vae_model,
@@ -133,6 +131,12 @@ def get_metadata_entries(req: GenerateImageRequest, task_data: TaskData):
 
     return [metadata.copy().update({'seed': req.seed + i}) for i in range(req.num_outputs)]
 
+def get_printable_request(req: GenerateImageRequest):
+    metadata = req.dict()
+    del metadata['init_image']
+    del metadata['init_image_mask']
+    return metadata
+
 def make_filename_callback(req: GenerateImageRequest, suffix=None):
     def make_filename(i):
         img_id = base64.b64encode(int(time.time()+i).to_bytes(8, 'big')).decode() # Generate unique ID based on time.

From 27963decc9c609b56d5d6babdc646753cf5b434c Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Mon, 12 Dec 2022 18:12:55 +0530
Subject: [PATCH 33/74] Use the multi-filters API

---
 ui/sd_internal/renderer.py | 13 +++++++------
 1 file changed, 7 insertions(+), 6 deletions(-)

diff --git a/ui/sd_internal/renderer.py b/ui/sd_internal/renderer.py
index 162b7da0..11a38da8 100644
--- a/ui/sd_internal/renderer.py
+++ b/ui/sd_internal/renderer.py
@@ -11,7 +11,7 @@ from sd_internal import device_manager
 from sd_internal import TaskData, Response, Image as ResponseImage, UserInitiatedStop
 
 from modules import model_loader, image_generator, image_utils, filters as image_filters, data_utils
-from modules.types import Context, GenerateImageRequest
+from modules.types import Context, GenerateImageRequest, FilterImageRequest
 
 log = logging.getLogger()
 
@@ -88,15 +88,16 @@ def apply_filters(task_data: TaskData, images: list, user_stopped):
         return images
 
     filters = []
-    if 'gfpgan' in task_data.use_face_correction.lower(): filters.append(image_filters.apply_gfpgan)
-    if 'realesrgan' in task_data.use_face_correction.lower(): filters.append(image_filters.apply_realesrgan)
+    if 'gfpgan' in task_data.use_face_correction.lower(): filters.append('gfpgan')
+    if 'realesrgan' in task_data.use_face_correction.lower(): filters.append('realesrgan')
 
     filtered_images = []
     for img in images:
-        for filter_fn in filters:
-            img = filter_fn(context, img)
+        filter_req = FilterImageRequest()
+        filter_req.init_image = img
 
-        filtered_images.append(img)
+        filtered_image = image_filters.apply(context, filters, filter_req)
+        filtered_images.append(filtered_image)
 
     return filtered_images
 

From a244a6873a6026d2157cda2298f196edbe2c8565 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Mon, 12 Dec 2022 20:46:11 +0530
Subject: [PATCH 34/74] Use the new 'diffusionkit' package name

---
 ui/sd_internal/__init__.py      | 2 +-
 ui/sd_internal/model_manager.py | 4 ++--
 ui/sd_internal/renderer.py      | 4 ++--
 ui/sd_internal/task_manager.py  | 2 +-
 ui/server.py                    | 2 +-
 5 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/ui/sd_internal/__init__.py b/ui/sd_internal/__init__.py
index 7093562a..71073216 100644
--- a/ui/sd_internal/__init__.py
+++ b/ui/sd_internal/__init__.py
@@ -1,6 +1,6 @@
 from pydantic import BaseModel
 
-from modules.types import GenerateImageRequest
+from diffusionkit.types import GenerateImageRequest
 
 class TaskData(BaseModel):
     request_id: str = None
diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index f5e8a5c7..18418624 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -4,8 +4,8 @@ import picklescan.scanner
 import rich
 
 from sd_internal import app, TaskData
-from modules import model_loader
-from modules.types import Context
+from diffusionkit import model_loader
+from diffusionkit.types import Context
 
 log = logging.getLogger()
 
diff --git a/ui/sd_internal/renderer.py b/ui/sd_internal/renderer.py
index 11a38da8..1fff48e1 100644
--- a/ui/sd_internal/renderer.py
+++ b/ui/sd_internal/renderer.py
@@ -10,8 +10,8 @@ import logging
 from sd_internal import device_manager
 from sd_internal import TaskData, Response, Image as ResponseImage, UserInitiatedStop
 
-from modules import model_loader, image_generator, image_utils, filters as image_filters, data_utils
-from modules.types import Context, GenerateImageRequest, FilterImageRequest
+from diffusionkit import model_loader, image_generator, image_utils, filters as image_filters, data_utils
+from diffusionkit.types import Context, GenerateImageRequest, FilterImageRequest
 
 log = logging.getLogger()
 
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index ef2a4a3b..f4576372 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -15,7 +15,7 @@ import queue, threading, time, weakref
 from typing import Any, Hashable
 
 from sd_internal import TaskData, device_manager
-from modules.types import GenerateImageRequest
+from diffusionkit.types import GenerateImageRequest
 
 log = logging.getLogger()
 
diff --git a/ui/server.py b/ui/server.py
index 42bdb0f4..7308dfc8 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -15,7 +15,7 @@ from pydantic import BaseModel
 
 from sd_internal import app, model_manager, task_manager
 from sd_internal import TaskData
-from modules.types import GenerateImageRequest
+from diffusionkit.types import GenerateImageRequest
 
 log = logging.getLogger()
 

From a483bd0800e7887892895c2c43f4a022e6b03691 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Tue, 13 Dec 2022 11:46:13 +0530
Subject: [PATCH 35/74] No need to catch and report exceptions separately in
 the renderer now

---
 ui/sd_internal/renderer.py | 21 ++++++---------------
 1 file changed, 6 insertions(+), 15 deletions(-)

diff --git a/ui/sd_internal/renderer.py b/ui/sd_internal/renderer.py
index 1fff48e1..0697c908 100644
--- a/ui/sd_internal/renderer.py
+++ b/ui/sd_internal/renderer.py
@@ -36,23 +36,14 @@ def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queu
     log.info(f'request: {get_printable_request(req)}')
     log.info(f'task data: {task_data.dict()}')
 
-    try:
-        images = _make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
+    images = _make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
 
-        res = Response(req, task_data, images=construct_response(images, task_data, base_seed=req.seed))
-        res = res.json()
-        data_queue.put(json.dumps(res))
-        log.info('Task completed')
+    res = Response(req, task_data, images=construct_response(images, task_data, base_seed=req.seed))
+    res = res.json()
+    data_queue.put(json.dumps(res))
+    log.info('Task completed')
 
-        return res
-    except Exception as e:
-        log.error(traceback.format_exc())
-
-        data_queue.put(json.dumps({
-            "status": 'failed',
-            "detail": str(e)
-        }))
-        raise e
+    return res
 
 def _make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
     images, user_stopped = generate_images(req, task_data, data_queue, task_temp_images, step_callback, task_data.stream_image_progress)

From 6cd0b530c5a791ff33968ae15b66b55fd1415dee Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Tue, 13 Dec 2022 15:45:44 +0530
Subject: [PATCH 36/74] Simplify the code for VAE loading, and make it faster
 to load VAEs (because we don't reload the entire SD model each time a VAE
 changes); Record the error and end the thread if the SD model fails to load
 during startup

---
 ui/sd_internal/model_manager.py | 10 ++++------
 ui/sd_internal/task_manager.py  | 25 +++++++++++++------------
 2 files changed, 17 insertions(+), 18 deletions(-)

diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index 18418624..b6c4c92d 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -42,6 +42,8 @@ def load_default_models(context: Context):
 
     # load mandatory models
     model_loader.load_model(context, 'stable-diffusion')
+    model_loader.load_model(context, 'vae')
+    model_loader.load_model(context, 'hypernetwork')
 
 def unload_all(context: Context):
     for model_type in KNOWN_MODEL_TYPES:
@@ -93,17 +95,13 @@ def resolve_model_to_use(model_name:str=None, model_type:str=None):
 
 def reload_models_if_necessary(context: Context, task_data: TaskData):
     model_paths_in_req = (
+        ('stable-diffusion', task_data.use_stable_diffusion_model),
+        ('vae', task_data.use_vae_model),
         ('hypernetwork', task_data.use_hypernetwork_model),
         ('gfpgan', task_data.use_face_correction),
         ('realesrgan', task_data.use_upscale),
     )
 
-    if context.model_paths.get('stable-diffusion') != task_data.use_stable_diffusion_model or context.model_paths.get('vae') != task_data.use_vae_model:
-        context.model_paths['stable-diffusion'] = task_data.use_stable_diffusion_model
-        context.model_paths['vae'] = task_data.use_vae_model
-
-        model_loader.load_model(context, 'stable-diffusion')
-
     for model_type, model_path_in_req in model_paths_in_req:
         if context.model_paths.get(model_type) != model_path_in_req:
             context.model_paths[model_type] = model_path_in_req
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 0db48d9d..3b8f6082 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -222,24 +222,25 @@ def thread_render(device):
     from sd_internal import renderer, model_manager
     try:
         renderer.init(device)
+
+        weak_thread_data[threading.current_thread()] = {
+            'device': renderer.context.device,
+            'device_name': renderer.context.device_name,
+            'alive': True
+        }
+
+        current_state = ServerStates.LoadingModel
+        model_manager.load_default_models(renderer.context)
+
+        current_state = ServerStates.Online
     except Exception as e:
         log.error(traceback.format_exc())
         weak_thread_data[threading.current_thread()] = {
-            'error': e
+            'error': e,
+            'alive': False
         }
         return
 
-    weak_thread_data[threading.current_thread()] = {
-        'device': renderer.context.device,
-        'device_name': renderer.context.device_name,
-        'alive': True
-    }
-
-    current_state = ServerStates.LoadingModel
-    model_manager.load_default_models(renderer.context)
-
-    current_state = ServerStates.Online
-
     while True:
         session_cache.clean()
         task_cache.clean()

From cb81e2aacd5e47e64b0915b76b6ba6bbcf8e9033 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Wed, 14 Dec 2022 10:18:01 +0530
Subject: [PATCH 37/74] Fix a bug where the metadata output format wouldn't get
 sent to the backend

---
 ui/media/js/main.js       | 1 +
 ui/media/js/parameters.js | 6 +++++-
 2 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/ui/media/js/main.js b/ui/media/js/main.js
index b26f363a..26303420 100644
--- a/ui/media/js/main.js
+++ b/ui/media/js/main.js
@@ -894,6 +894,7 @@ function getCurrentUserRequest() {
             show_only_filtered_image: showOnlyFilteredImageField.checked,
             output_format: outputFormatField.value,
             output_quality: parseInt(outputQualityField.value),
+            metadata_output_format: document.querySelector('#metadata_output_format').value,
             original_prompt: promptField.value,
             active_tags: (activeTags.map(x => x.name))
         }
diff --git a/ui/media/js/parameters.js b/ui/media/js/parameters.js
index a4167fc3..52a4b67c 100644
--- a/ui/media/js/parameters.js
+++ b/ui/media/js/parameters.js
@@ -57,11 +57,15 @@ var PARAMETERS = [
         id: "metadata_output_format",
         type: ParameterType.select,
         label: "Metadata format",
-        note: "the metadata will be saved to disk in this format",
+        note: "will be saved to disk in this format",
         default: "txt",
         options: [
             {
                 value: "txt",
+                label: "txt"
+            },
+            {
+                value: "json",
                 label: "json"
             }
         ],

From 0dbce101acec4f621dde37d0a2dc84826fd56088 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Wed, 14 Dec 2022 10:21:44 +0530
Subject: [PATCH 38/74] sampler -> sampler_name

---
 ui/media/js/dnd.js | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/ui/media/js/dnd.js b/ui/media/js/dnd.js
index 1887aeaf..fa4a2d43 100644
--- a/ui/media/js/dnd.js
+++ b/ui/media/js/dnd.js
@@ -160,9 +160,9 @@ const TASK_MAPPING = {
         readUI: () => (useUpscalingField.checked ? upscaleModelField.value : undefined),
         parse: (val) => val
     },
-    sampler: { name: 'Sampler',
-        setUI: (sampler) => {
-            samplerField.value = sampler
+    sampler_name: { name: 'Sampler',
+        setUI: (sampler_name) => {
+            samplerField.value = sampler_name
         },
         readUI: () => samplerField.value,
         parse: (val) => val
@@ -351,7 +351,7 @@ const TASK_TEXT_MAPPING = {
     prompt_strength: 'Prompt Strength',
     use_face_correction: 'Use Face Correction',
     use_upscale: 'Use Upscaling',
-    sampler: 'Sampler',
+    sampler_name: 'Sampler',
     negative_prompt: 'Negative Prompt',
     use_stable_diffusion_model: 'Stable Diffusion model',
     use_hypernetwork_model: 'Hypernetwork model',

From d103693811388ad8edd33d70de53139f22dd0150 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Wed, 14 Dec 2022 10:22:24 +0530
Subject: [PATCH 39/74] Bug in the metadata generation - made an array of None

---
 ui/sd_internal/renderer.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/ui/sd_internal/renderer.py b/ui/sd_internal/renderer.py
index 0697c908..0420d51d 100644
--- a/ui/sd_internal/renderer.py
+++ b/ui/sd_internal/renderer.py
@@ -121,7 +121,10 @@ def get_metadata_entries(req: GenerateImageRequest, task_data: TaskData):
         'use_upscale': task_data.use_upscale,
     })
 
-    return [metadata.copy().update({'seed': req.seed + i}) for i in range(req.num_outputs)]
+    entries = [metadata.copy() for _ in range(req.num_outputs)]
+    for i, entry in enumerate(entries):
+        entry['seed'] = req.seed + i
+    return entries
 
 def get_printable_request(req: GenerateImageRequest):
     metadata = req.dict()

From 84d606408ae103bf1a6c45981b3288993e6451ff Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Wed, 14 Dec 2022 10:31:19 +0530
Subject: [PATCH 40/74] Prompt is now a keyword in the new metadata format
 generated from diffusionkit

---
 ui/media/js/dnd.js | 1 +
 1 file changed, 1 insertion(+)

diff --git a/ui/media/js/dnd.js b/ui/media/js/dnd.js
index fa4a2d43..6e733286 100644
--- a/ui/media/js/dnd.js
+++ b/ui/media/js/dnd.js
@@ -343,6 +343,7 @@ function getModelPath(filename, extensions)
 }
 
 const TASK_TEXT_MAPPING = {
+    prompt: 'Prompt',
     width: 'Width',
     height: 'Height',
     seed: 'Seed',

From 7dc7f70582c2bd085b1e54f62659998367c4e90f Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Wed, 14 Dec 2022 10:34:36 +0530
Subject: [PATCH 41/74] Allow parsing .safetensors stable diffusion model path
 in the metadata parser

---
 ui/media/js/dnd.js | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ui/media/js/dnd.js b/ui/media/js/dnd.js
index 6e733286..d09fe32f 100644
--- a/ui/media/js/dnd.js
+++ b/ui/media/js/dnd.js
@@ -171,7 +171,7 @@ const TASK_MAPPING = {
         setUI: (use_stable_diffusion_model) => {
             const oldVal = stableDiffusionModelField.value
 
-            use_stable_diffusion_model = getModelPath(use_stable_diffusion_model, ['.ckpt'])
+            use_stable_diffusion_model = getModelPath(use_stable_diffusion_model, ['.ckpt', '.safetensors'])
             stableDiffusionModelField.value = use_stable_diffusion_model
 
             if (!stableDiffusionModelField.value) {

From d1ac90e16d9e5d2d396d21148fc7e4849de6c32a Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Wed, 14 Dec 2022 15:43:24 +0530
Subject: [PATCH 42/74] [metadata parsing] Support loading the flat JSON format
 saved by the next backend; Set the dropdown to None if the value is undefined
 or null in the metadata

---
 ui/media/js/dnd.js | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/ui/media/js/dnd.js b/ui/media/js/dnd.js
index d09fe32f..0f204326 100644
--- a/ui/media/js/dnd.js
+++ b/ui/media/js/dnd.js
@@ -184,6 +184,7 @@ const TASK_MAPPING = {
     use_vae_model: { name: 'VAE model',
         setUI: (use_vae_model) => {
             const oldVal = vaeModelField.value
+            use_vae_model = (use_vae_model === undefined || use_vae_model === null ? '' : use_vae_model)
 
             if (use_vae_model !== '') {
                 use_vae_model = getModelPath(use_vae_model, ['.vae.pt', '.ckpt'])
@@ -197,6 +198,7 @@ const TASK_MAPPING = {
     use_hypernetwork_model: { name: 'Hypernetwork model',
         setUI: (use_hypernetwork_model) => {
             const oldVal = hypernetworkModelField.value
+            use_hypernetwork_model = (use_hypernetwork_model === undefined || use_hypernetwork_model === null ? '' : use_hypernetwork_model)
 
             if (use_hypernetwork_model !== '') {
                 use_hypernetwork_model = getModelPath(use_hypernetwork_model, ['.pt'])
@@ -404,6 +406,9 @@ async function parseContent(text) {
     if (text.startsWith('{') && text.endsWith('}')) {
         try {
             const task = JSON.parse(text)
+            if (!('reqBody' in task)) { // support the format saved to the disk, by the UI
+                task.reqBody = Object.assign({}, task)
+            }
             restoreTaskToUI(task)
             return true
         } catch (e) {

From 12e0194c7f5f189c2f9d2429465452bdfc5ef4ec Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Wed, 14 Dec 2022 16:30:08 +0530
Subject: [PATCH 43/74] Allow None as the value type in dnd parsing

---
 ui/media/js/dnd.js | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/ui/media/js/dnd.js b/ui/media/js/dnd.js
index 0f204326..37d99d44 100644
--- a/ui/media/js/dnd.js
+++ b/ui/media/js/dnd.js
@@ -184,7 +184,7 @@ const TASK_MAPPING = {
     use_vae_model: { name: 'VAE model',
         setUI: (use_vae_model) => {
             const oldVal = vaeModelField.value
-            use_vae_model = (use_vae_model === undefined || use_vae_model === null ? '' : use_vae_model)
+            use_vae_model = (use_vae_model === undefined || use_vae_model === null || use_vae_model === 'None' ? '' : use_vae_model)
 
             if (use_vae_model !== '') {
                 use_vae_model = getModelPath(use_vae_model, ['.vae.pt', '.ckpt'])
@@ -198,7 +198,7 @@ const TASK_MAPPING = {
     use_hypernetwork_model: { name: 'Hypernetwork model',
         setUI: (use_hypernetwork_model) => {
             const oldVal = hypernetworkModelField.value
-            use_hypernetwork_model = (use_hypernetwork_model === undefined || use_hypernetwork_model === null ? '' : use_hypernetwork_model)
+            use_hypernetwork_model = (use_hypernetwork_model === undefined || use_hypernetwork_model === null || use_hypernetwork_model === 'None' ? '' : use_hypernetwork_model)
 
             if (use_hypernetwork_model !== '') {
                 use_hypernetwork_model = getModelPath(use_hypernetwork_model, ['.pt'])

From 35ff4f439ef4cb30ed4d0aa201f355914bd7a27d Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Wed, 14 Dec 2022 16:30:19 +0530
Subject: [PATCH 44/74] Refactor save_to_disk

---
 ui/sd_internal/renderer.py   | 57 ++-----------------------
 ui/sd_internal/save_utils.py | 80 ++++++++++++++++++++++++++++++++++++
 2 files changed, 83 insertions(+), 54 deletions(-)
 create mode 100644 ui/sd_internal/save_utils.py

diff --git a/ui/sd_internal/renderer.py b/ui/sd_internal/renderer.py
index 0420d51d..55b2c4a7 100644
--- a/ui/sd_internal/renderer.py
+++ b/ui/sd_internal/renderer.py
@@ -1,13 +1,9 @@
 import queue
 import time
 import json
-import os
-import base64
-import re
-import traceback
 import logging
 
-from sd_internal import device_manager
+from sd_internal import device_manager, save_utils
 from sd_internal import TaskData, Response, Image as ResponseImage, UserInitiatedStop
 
 from diffusionkit import model_loader, image_generator, image_utils, filters as image_filters, data_utils
@@ -20,8 +16,6 @@ context = Context() # thread-local
 runtime data (bound locally to this thread), for e.g. device, references to loaded models, optimization flags etc
 '''
 
-filename_regex = re.compile('[^a-zA-Z0-9]')
-
 def init(device):
     '''
     Initializes the fields that will be bound to this runtime's context, and sets the current torch device
@@ -33,7 +27,7 @@ def init(device):
     device_manager.device_init(context, device)
 
 def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
-    log.info(f'request: {get_printable_request(req)}')
+    log.info(f'request: {save_utils.get_printable_request(req)}')
     log.info(f'task data: {task_data.dict()}')
 
     images = _make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
@@ -50,8 +44,7 @@ def _make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_q
     filtered_images = apply_filters(task_data, images, user_stopped)
 
     if task_data.save_to_disk_path is not None:
-        save_folder_path = os.path.join(task_data.save_to_disk_path, filename_regex.sub('_', task_data.session_id))
-        save_to_disk(images, filtered_images, save_folder_path, req, task_data)
+        save_utils.save_to_disk(images, filtered_images, req, task_data)
 
     return filtered_images if task_data.show_only_filtered_image else images + filtered_images
 
@@ -92,17 +85,6 @@ def apply_filters(task_data: TaskData, images: list, user_stopped):
 
     return filtered_images
 
-def save_to_disk(images: list, filtered_images: list, save_folder_path, req: GenerateImageRequest, task_data: TaskData):
-    metadata_entries = get_metadata_entries(req, task_data)
-
-    if task_data.show_only_filtered_image or filtered_images == images:
-        data_utils.save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
-        data_utils.save_metadata(metadata_entries, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.metadata_output_format)
-    else:
-        data_utils.save_images(images, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
-        data_utils.save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.output_format, output_quality=task_data.output_quality)
-        data_utils.save_metadata(metadata_entries, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.metadata_output_format)
-
 def construct_response(images: list, task_data: TaskData, base_seed: int):
     return [
         ResponseImage(
@@ -111,39 +93,6 @@ def construct_response(images: list, task_data: TaskData, base_seed: int):
         ) for i, img in enumerate(images)
     ]
 
-def get_metadata_entries(req: GenerateImageRequest, task_data: TaskData):
-    metadata = get_printable_request(req)
-    metadata.update({
-        'use_stable_diffusion_model': task_data.use_stable_diffusion_model,
-        'use_vae_model': task_data.use_vae_model,
-        'use_hypernetwork_model': task_data.use_hypernetwork_model,
-        'use_face_correction': task_data.use_face_correction,
-        'use_upscale': task_data.use_upscale,
-    })
-
-    entries = [metadata.copy() for _ in range(req.num_outputs)]
-    for i, entry in enumerate(entries):
-        entry['seed'] = req.seed + i
-    return entries
-
-def get_printable_request(req: GenerateImageRequest):
-    metadata = req.dict()
-    del metadata['init_image']
-    del metadata['init_image_mask']
-    return metadata
-
-def make_filename_callback(req: GenerateImageRequest, suffix=None):
-    def make_filename(i):
-        img_id = base64.b64encode(int(time.time()+i).to_bytes(8, 'big')).decode() # Generate unique ID based on time.
-        img_id = img_id.translate({43:None, 47:None, 61:None})[-8:] # Remove + / = and keep last 8 chars.
-
-        prompt_flattened = filename_regex.sub('_', req.prompt)[:50]
-        name = f"{prompt_flattened}_{img_id}"
-        name = name if suffix is None else f'{name}_{suffix}'
-        return name
-
-    return make_filename
-
 def make_step_callback(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
     n_steps = req.num_inference_steps if req.init_image is None else int(req.num_inference_steps * req.prompt_strength)
     last_callback_time = -1
diff --git a/ui/sd_internal/save_utils.py b/ui/sd_internal/save_utils.py
new file mode 100644
index 00000000..29c4a29c
--- /dev/null
+++ b/ui/sd_internal/save_utils.py
@@ -0,0 +1,80 @@
+import os
+import time
+import base64
+import re
+
+from diffusionkit import data_utils
+from diffusionkit.types import GenerateImageRequest
+
+from sd_internal import TaskData
+
+filename_regex = re.compile('[^a-zA-Z0-9]')
+
+# keep in sync with `ui/media/js/dnd.js`
+TASK_TEXT_MAPPING = {
+    'prompt': 'Prompt',
+    'width': 'Width',
+    'height': 'Height',
+    'seed': 'Seed',
+    'num_inference_steps': 'Steps',
+    'guidance_scale': 'Guidance Scale',
+    'prompt_strength': 'Prompt Strength',
+    'use_face_correction': 'Use Face Correction',
+    'use_upscale': 'Use Upscaling',
+    'sampler_name': 'Sampler',
+    'negative_prompt': 'Negative Prompt',
+    'use_stable_diffusion_model': 'Stable Diffusion model',
+    'use_hypernetwork_model': 'Hypernetwork model',
+    'hypernetwork_strength': 'Hypernetwork Strength'
+}
+
+def save_to_disk(images: list, filtered_images: list, req: GenerateImageRequest, task_data: TaskData):
+    save_folder_path = os.path.join(task_data.save_to_disk_path, filename_regex.sub('_', task_data.session_id))
+    metadata_entries = get_metadata_entries(req, task_data)
+
+    if task_data.show_only_filtered_image or filtered_images == images:
+        data_utils.save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        data_utils.save_metadata(metadata_entries, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.metadata_output_format)
+    else:
+        data_utils.save_images(images, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        data_utils.save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        data_utils.save_metadata(metadata_entries, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.metadata_output_format)
+
+def get_metadata_entries(req: GenerateImageRequest, task_data: TaskData):
+    metadata = get_printable_request(req)
+    metadata.update({
+        'use_stable_diffusion_model': task_data.use_stable_diffusion_model,
+        'use_vae_model': task_data.use_vae_model,
+        'use_hypernetwork_model': task_data.use_hypernetwork_model,
+        'use_face_correction': task_data.use_face_correction,
+        'use_upscale': task_data.use_upscale,
+    })
+
+    # if text, format it in the text format expected by the UI
+    is_txt_format = (task_data.metadata_output_format.lower() == 'txt')
+    if is_txt_format:
+        metadata = {TASK_TEXT_MAPPING[key]: val for key, val in metadata.items() if key in TASK_TEXT_MAPPING}
+
+    entries = [metadata.copy() for _ in range(req.num_outputs)]
+    for i, entry in enumerate(entries):
+        entry['Seed' if is_txt_format else 'seed'] = req.seed + i
+
+    return entries
+
+def get_printable_request(req: GenerateImageRequest):
+    metadata = req.dict()
+    del metadata['init_image']
+    del metadata['init_image_mask']
+    return metadata
+
+def make_filename_callback(req: GenerateImageRequest, suffix=None):
+    def make_filename(i):
+        img_id = base64.b64encode(int(time.time()+i).to_bytes(8, 'big')).decode() # Generate unique ID based on time.
+        img_id = img_id.translate({43:None, 47:None, 61:None})[-8:] # Remove + / = and keep last 8 chars.
+
+        prompt_flattened = filename_regex.sub('_', req.prompt)[:50]
+        name = f"{prompt_flattened}_{img_id}"
+        name = name if suffix is None else f'{name}_{suffix}'
+        return name
+
+    return make_filename
\ No newline at end of file

From fb075a0013d476120ce79f4eb2d9ed19132f75d0 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Wed, 14 Dec 2022 16:53:50 +0530
Subject: [PATCH 45/74] Fix whitespace

---
 ui/media/js/main.js | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/ui/media/js/main.js b/ui/media/js/main.js
index d309ad0a..c2dc32f3 100644
--- a/ui/media/js/main.js
+++ b/ui/media/js/main.js
@@ -629,9 +629,9 @@ function onTaskCompleted(task, reqBody, instance, outputContainer, stepUpdate) {
     time /= 1000
 
     if (task.batchesDone == task.batchCount) {
-	if (!task.outputMsg.innerText.toLowerCase().includes('error')) {
+        if (!task.outputMsg.innerText.toLowerCase().includes('error')) {
             task.outputMsg.innerText = `Processed ${task.numOutputsTotal} images in ${time} seconds`
-	}
+        }
         task.progressBar.style.height = "0px"
         task.progressBar.style.border = "0px solid var(--background-color3)"
         task.progressBar.classList.remove("active")

From aa01fd058ea44bd38526869c9dc0e04a31d6900f Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Thu, 15 Dec 2022 23:30:06 +0530
Subject: [PATCH 46/74] Set performance level (low, medium, high) instead of a
 Turbo field. The previous Turbo field is equivalent to 'Medium' performance
 now

---
 ui/media/js/auto-save.js         |  2 +-
 ui/media/js/main.js              |  4 +--
 ui/media/js/parameters.js        | 20 ++++++++----
 ui/sd_internal/__init__.py       |  2 +-
 ui/sd_internal/app.py            |  4 ++-
 ui/sd_internal/device_manager.py | 12 ++++++++
 ui/sd_internal/model_manager.py  | 52 ++++++++++++++++++++------------
 ui/sd_internal/task_manager.py   |  2 +-
 ui/server.py                     |  2 +-
 9 files changed, 67 insertions(+), 33 deletions(-)

diff --git a/ui/media/js/auto-save.js b/ui/media/js/auto-save.js
index 1677c6c1..91a2d267 100644
--- a/ui/media/js/auto-save.js
+++ b/ui/media/js/auto-save.js
@@ -36,7 +36,7 @@ const SETTINGS_IDS_LIST = [
     "save_to_disk",
     "diskPath",
     "sound_toggle",
-    "turbo",
+    "performance_level",
     "confirm_dangerous_actions",
     "metadata_output_format",
     "auto_save_settings",
diff --git a/ui/media/js/main.js b/ui/media/js/main.js
index c2dc32f3..3a669b67 100644
--- a/ui/media/js/main.js
+++ b/ui/media/js/main.js
@@ -602,7 +602,7 @@ function onTaskCompleted(task, reqBody, instance, outputContainer, stepUpdate) {
                             <b>Suggestions</b>:
                             <br/>
                             1. If you have set an initial image, please try reducing its dimension to ${MAX_INIT_IMAGE_DIMENSION}x${MAX_INIT_IMAGE_DIMENSION} or smaller.<br/>
-                            2. Try disabling the '<em>Turbo mode</em>' under '<em>Advanced Settings</em>'.<br/>
+                            2. Try picking a lower performance level in the '<em>Performance Level</em>' setting (in the '<em>Settings</em>' tab).<br/>
                             3. Try generating a smaller image.<br/>`
                 }
             } else {
@@ -887,7 +887,7 @@ function getCurrentUserRequest() {
             width: parseInt(widthField.value),
             height: parseInt(heightField.value),
             // allow_nsfw: allowNSFWField.checked,
-            turbo: turboField.checked,
+            performance_level: perfLevelField.value,
             //render_device: undefined, // Set device affinity. Prefer this device, but wont activate.
             use_stable_diffusion_model: stableDiffusionModelField.value,
             use_vae_model: vaeModelField.value,
diff --git a/ui/media/js/parameters.js b/ui/media/js/parameters.js
index 52a4b67c..865f7bb5 100644
--- a/ui/media/js/parameters.js
+++ b/ui/media/js/parameters.js
@@ -94,12 +94,20 @@ var PARAMETERS = [
         default: true,
     },
     {
-        id: "turbo",
-        type: ParameterType.checkbox,
-        label: "Turbo Mode",
-        note: "generates images faster, but uses an additional 1 GB of GPU memory",
+        id: "performance_level",
+        type: ParameterType.select,
+        label: "Performance Level",
+        note: "Faster performance requires more GPU memory<br/><br/>" +
+              "<b>High:</b> fastest, maximum GPU memory usage</br>" +
+              "<b>Medium:</b> decent speed, uses 1 GB more memory than Low<br/>" +
+              "<b>Low:</b> slowest, for GPUs with 4 GB (or less) memory",
         icon: "fa-forward",
-        default: true,
+        default: "high",
+        options: [
+            {value: "high", label: "High"},
+            {value: "medium", label: "Medium"},
+            {value: "low", label: "Low"}
+        ],
     },
     {
         id: "use_cpu",
@@ -219,7 +227,7 @@ function initParameters() {
 
 initParameters()
 
-let turboField = document.querySelector('#turbo')
+let perfLevelField = document.querySelector('#performance_level')
 let useCPUField = document.querySelector('#use_cpu')
 let autoPickGPUsField = document.querySelector('#auto_pick_gpus')
 let useGPUsField = document.querySelector('#use_gpus')
diff --git a/ui/sd_internal/__init__.py b/ui/sd_internal/__init__.py
index 71073216..5475c3a6 100644
--- a/ui/sd_internal/__init__.py
+++ b/ui/sd_internal/__init__.py
@@ -6,7 +6,7 @@ class TaskData(BaseModel):
     request_id: str = None
     session_id: str = "session"
     save_to_disk_path: str = None
-    turbo: bool = True
+    performance_level: str = "high" # or "low" or "medium"
 
     use_face_correction: str = None # or "GFPGANv1.3"
     use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
diff --git a/ui/sd_internal/app.py b/ui/sd_internal/app.py
index 47a2d610..7171e6c1 100644
--- a/ui/sd_internal/app.py
+++ b/ui/sd_internal/app.py
@@ -110,7 +110,7 @@ def setConfig(config):
     except:
         log.error(traceback.format_exc())
 
-def save_model_to_config(ckpt_model_name, vae_model_name, hypernetwork_model_name):
+def save_to_config(ckpt_model_name, vae_model_name, hypernetwork_model_name, performance_level):
     config = getConfig()
     if 'model' not in config:
         config['model'] = {}
@@ -124,6 +124,8 @@ def save_model_to_config(ckpt_model_name, vae_model_name, hypernetwork_model_nam
     if hypernetwork_model_name is None or hypernetwork_model_name == "":
         del config['model']['hypernetwork']
 
+    config['performance_level'] = performance_level
+
     setConfig(config)
 
 def update_render_threads():
diff --git a/ui/sd_internal/device_manager.py b/ui/sd_internal/device_manager.py
index 733bab50..8b5c49be 100644
--- a/ui/sd_internal/device_manager.py
+++ b/ui/sd_internal/device_manager.py
@@ -128,6 +128,18 @@ def needs_to_force_full_precision(context):
     device_name = context.device_name.lower()
     return (('nvidia' in device_name or 'geforce' in device_name) and (' 1660' in device_name or ' 1650' in device_name)) or ('Quadro T2000' in device_name)
 
+def get_max_perf_level(device):
+    if device != 'cpu':
+        _, mem_total = torch.cuda.mem_get_info(device)
+        mem_total /= float(10**9)
+
+        if mem_total < 4.5:
+            return 'low'
+        elif mem_total < 6.5:
+            return 'medium'
+
+    return 'high'
+
 def validate_device_id(device, log_prefix=''):
     def is_valid():
         if not isinstance(device, str):
diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index b6c4c92d..9c3320ea 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -3,7 +3,7 @@ import logging
 import picklescan.scanner
 import rich
 
-from sd_internal import app, TaskData
+from sd_internal import app, TaskData, device_manager
 from diffusionkit import model_loader
 from diffusionkit.types import Context
 
@@ -25,6 +25,11 @@ DEFAULT_MODELS = {
     'gfpgan': ['GFPGANv1.3'],
     'realesrgan': ['RealESRGAN_x4plus'],
 }
+PERF_LEVEL_TO_VRAM_OPTIMIZATIONS = {
+    'low': {'KEEP_ENTIRE_MODEL_IN_CPU'},
+    'medium': {'KEEP_FS_AND_CS_IN_CPU', 'SET_ATTENTION_STEP_TO_4'},
+    'high': {},
+}
 
 known_models = {}
 
@@ -37,8 +42,7 @@ def load_default_models(context: Context):
     for model_type in KNOWN_MODEL_TYPES:
         context.model_paths[model_type] = resolve_model_to_use(model_type=model_type)
 
-    # disable TURBO initially (this should be read from the config eventually)
-    context.vram_optimizations -= {'TURBO'}
+    set_vram_optimizations(context)
 
     # load mandatory models
     model_loader.load_model(context, 'stable-diffusion')
@@ -94,20 +98,23 @@ def resolve_model_to_use(model_name:str=None, model_type:str=None):
     return None
 
 def reload_models_if_necessary(context: Context, task_data: TaskData):
-    model_paths_in_req = (
-        ('stable-diffusion', task_data.use_stable_diffusion_model),
-        ('vae', task_data.use_vae_model),
-        ('hypernetwork', task_data.use_hypernetwork_model),
-        ('gfpgan', task_data.use_face_correction),
-        ('realesrgan', task_data.use_upscale),
-    )
+    model_paths_in_req = {
+        'stable-diffusion': task_data.use_stable_diffusion_model,
+        'vae': task_data.use_vae_model,
+        'hypernetwork': task_data.use_hypernetwork_model,
+        'gfpgan': task_data.use_face_correction,
+        'realesrgan': task_data.use_upscale,
+    }
+    models_to_reload = {model_type: path for model_type, path in model_paths_in_req.items() if context.model_paths.get(model_type) != path}
 
-    for model_type, model_path_in_req in model_paths_in_req:
-        if context.model_paths.get(model_type) != model_path_in_req:
-            context.model_paths[model_type] = model_path_in_req
+    if set_vram_optimizations(context): # reload SD
+        models_to_reload['stable-diffusion'] = model_paths_in_req['stable-diffusion']
 
-            action_fn = model_loader.unload_model if context.model_paths[model_type] is None else model_loader.load_model
-            action_fn(context, model_type)
+    for model_type, model_path_in_req in models_to_reload.items():
+        context.model_paths[model_type] = model_path_in_req
+
+        action_fn = model_loader.unload_model if context.model_paths[model_type] is None else model_loader.load_model
+        action_fn(context, model_type)
 
 def resolve_model_paths(task_data: TaskData):
     task_data.use_stable_diffusion_model = resolve_model_to_use(task_data.use_stable_diffusion_model, model_type='stable-diffusion')
@@ -117,11 +124,16 @@ def resolve_model_paths(task_data: TaskData):
     if task_data.use_face_correction: task_data.use_face_correction = resolve_model_to_use(task_data.use_face_correction, 'gfpgan')
     if task_data.use_upscale: task_data.use_upscale = resolve_model_to_use(task_data.use_upscale, 'gfpgan')
 
-def set_vram_optimizations(context: Context, task_data: TaskData):
-    if task_data.turbo:
-        context.vram_optimizations.add('TURBO')
-    else:
-        context.vram_optimizations.remove('TURBO')
+def set_vram_optimizations(context: Context):
+    config = app.getConfig()
+    perf_level = config.get('performance_level', device_manager.get_max_perf_level(context.device))
+    vram_optimizations = PERF_LEVEL_TO_VRAM_OPTIMIZATIONS[perf_level]
+
+    if vram_optimizations != context.vram_optimizations:
+        context.vram_optimizations = vram_optimizations
+        return True
+
+    return False
 
 def make_model_folders():
     for model_type in KNOWN_MODEL_TYPES:
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 3b8f6082..0780283d 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -281,7 +281,6 @@ def thread_render(device):
 
             current_state = ServerStates.LoadingModel
             model_manager.resolve_model_paths(task.task_data)
-            model_manager.set_vram_optimizations(renderer.context, task.task_data)
             model_manager.reload_models_if_necessary(renderer.context, task.task_data)
 
             current_state = ServerStates.Rendering
@@ -342,6 +341,7 @@ def get_devices():
             'name': torch.cuda.get_device_name(device),
             'mem_free': mem_free,
             'mem_total': mem_total,
+            'max_perf_level': device_manager.get_max_perf_level(device),
         }
 
     # list the compatible devices
diff --git a/ui/server.py b/ui/server.py
index 7308dfc8..11d3731a 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -134,7 +134,7 @@ def render(req: dict):
 
         render_req.init_image_mask = req.get('mask') # hack: will rename this in the HTTP API in a future revision
 
-        app.save_model_to_config(task_data.use_stable_diffusion_model, task_data.use_vae_model, task_data.use_hypernetwork_model)
+        app.save_to_config(task_data.use_stable_diffusion_model, task_data.use_vae_model, task_data.use_hypernetwork_model, task_data.performance_level)
 
         # enqueue the task
         new_task = task_manager.render(render_req, task_data)

From 7982a9ae257366653a1b9a305fde00de65d9b511 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 16 Dec 2022 11:34:49 +0530
Subject: [PATCH 47/74] Change the performance field to GPU Memory Usage
 instead, and use the 'balanced' profile by default, since it's just 5% slower
 than 'high', and uses nearly 50% less VRAM

---
 ui/media/js/auto-save.js         |  2 +-
 ui/media/js/main.js              |  4 ++--
 ui/media/js/parameters.js        | 14 +++++++-------
 ui/sd_internal/__init__.py       |  2 +-
 ui/sd_internal/app.py            |  4 ++--
 ui/sd_internal/device_manager.py |  4 ++--
 ui/sd_internal/model_manager.py  | 23 +++++++++++++++++++----
 ui/sd_internal/task_manager.py   |  2 +-
 ui/server.py                     |  2 +-
 9 files changed, 36 insertions(+), 21 deletions(-)

diff --git a/ui/media/js/auto-save.js b/ui/media/js/auto-save.js
index 91a2d267..934b3f32 100644
--- a/ui/media/js/auto-save.js
+++ b/ui/media/js/auto-save.js
@@ -36,7 +36,7 @@ const SETTINGS_IDS_LIST = [
     "save_to_disk",
     "diskPath",
     "sound_toggle",
-    "performance_level",
+    "vram_usage_level",
     "confirm_dangerous_actions",
     "metadata_output_format",
     "auto_save_settings",
diff --git a/ui/media/js/main.js b/ui/media/js/main.js
index 3a669b67..1e7269b4 100644
--- a/ui/media/js/main.js
+++ b/ui/media/js/main.js
@@ -602,7 +602,7 @@ function onTaskCompleted(task, reqBody, instance, outputContainer, stepUpdate) {
                             <b>Suggestions</b>:
                             <br/>
                             1. If you have set an initial image, please try reducing its dimension to ${MAX_INIT_IMAGE_DIMENSION}x${MAX_INIT_IMAGE_DIMENSION} or smaller.<br/>
-                            2. Try picking a lower performance level in the '<em>Performance Level</em>' setting (in the '<em>Settings</em>' tab).<br/>
+                            2. Try picking a lower level in the '<em>GPU Memory Usage</em>' setting (in the '<em>Settings</em>' tab).<br/>
                             3. Try generating a smaller image.<br/>`
                 }
             } else {
@@ -887,7 +887,7 @@ function getCurrentUserRequest() {
             width: parseInt(widthField.value),
             height: parseInt(heightField.value),
             // allow_nsfw: allowNSFWField.checked,
-            performance_level: perfLevelField.value,
+            vram_usage_level: vramUsageLevelField.value,
             //render_device: undefined, // Set device affinity. Prefer this device, but wont activate.
             use_stable_diffusion_model: stableDiffusionModelField.value,
             use_vae_model: vaeModelField.value,
diff --git a/ui/media/js/parameters.js b/ui/media/js/parameters.js
index 865f7bb5..93f1a266 100644
--- a/ui/media/js/parameters.js
+++ b/ui/media/js/parameters.js
@@ -94,18 +94,18 @@ var PARAMETERS = [
         default: true,
     },
     {
-        id: "performance_level",
+        id: "vram_usage_level",
         type: ParameterType.select,
-        label: "Performance Level",
+        label: "GPU Memory Usage",
         note: "Faster performance requires more GPU memory<br/><br/>" +
+              "<b>Balanced:</b> almost as fast as High, significantly lower GPU memory usage<br/>" +
               "<b>High:</b> fastest, maximum GPU memory usage</br>" +
-              "<b>Medium:</b> decent speed, uses 1 GB more memory than Low<br/>" +
-              "<b>Low:</b> slowest, for GPUs with 4 GB (or less) memory",
+              "<b>Low:</b> slowest, force-used for GPUs with 4 GB (or less) memory",
         icon: "fa-forward",
-        default: "high",
+        default: "balanced",
         options: [
+            {value: "balanced", label: "Balanced"},
             {value: "high", label: "High"},
-            {value: "medium", label: "Medium"},
             {value: "low", label: "Low"}
         ],
     },
@@ -227,7 +227,7 @@ function initParameters() {
 
 initParameters()
 
-let perfLevelField = document.querySelector('#performance_level')
+let vramUsageLevelField = document.querySelector('#vram_usage_level')
 let useCPUField = document.querySelector('#use_cpu')
 let autoPickGPUsField = document.querySelector('#auto_pick_gpus')
 let useGPUsField = document.querySelector('#use_gpus')
diff --git a/ui/sd_internal/__init__.py b/ui/sd_internal/__init__.py
index 5475c3a6..6f702749 100644
--- a/ui/sd_internal/__init__.py
+++ b/ui/sd_internal/__init__.py
@@ -6,7 +6,7 @@ class TaskData(BaseModel):
     request_id: str = None
     session_id: str = "session"
     save_to_disk_path: str = None
-    performance_level: str = "high" # or "low" or "medium"
+    vram_usage_level: str = "balanced" # or "low" or "medium"
 
     use_face_correction: str = None # or "GFPGANv1.3"
     use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
diff --git a/ui/sd_internal/app.py b/ui/sd_internal/app.py
index 7171e6c1..063069d2 100644
--- a/ui/sd_internal/app.py
+++ b/ui/sd_internal/app.py
@@ -110,7 +110,7 @@ def setConfig(config):
     except:
         log.error(traceback.format_exc())
 
-def save_to_config(ckpt_model_name, vae_model_name, hypernetwork_model_name, performance_level):
+def save_to_config(ckpt_model_name, vae_model_name, hypernetwork_model_name, vram_usage_level):
     config = getConfig()
     if 'model' not in config:
         config['model'] = {}
@@ -124,7 +124,7 @@ def save_to_config(ckpt_model_name, vae_model_name, hypernetwork_model_name, per
     if hypernetwork_model_name is None or hypernetwork_model_name == "":
         del config['model']['hypernetwork']
 
-    config['performance_level'] = performance_level
+    config['vram_usage_level'] = vram_usage_level
 
     setConfig(config)
 
diff --git a/ui/sd_internal/device_manager.py b/ui/sd_internal/device_manager.py
index 8b5c49be..56508fad 100644
--- a/ui/sd_internal/device_manager.py
+++ b/ui/sd_internal/device_manager.py
@@ -128,7 +128,7 @@ def needs_to_force_full_precision(context):
     device_name = context.device_name.lower()
     return (('nvidia' in device_name or 'geforce' in device_name) and (' 1660' in device_name or ' 1650' in device_name)) or ('Quadro T2000' in device_name)
 
-def get_max_perf_level(device):
+def get_max_vram_usage_level(device):
     if device != 'cpu':
         _, mem_total = torch.cuda.mem_get_info(device)
         mem_total /= float(10**9)
@@ -136,7 +136,7 @@ def get_max_perf_level(device):
         if mem_total < 4.5:
             return 'low'
         elif mem_total < 6.5:
-            return 'medium'
+            return 'balanced'
 
     return 'high'
 
diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index 9c3320ea..56f1d9c0 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -25,9 +25,9 @@ DEFAULT_MODELS = {
     'gfpgan': ['GFPGANv1.3'],
     'realesrgan': ['RealESRGAN_x4plus'],
 }
-PERF_LEVEL_TO_VRAM_OPTIMIZATIONS = {
+VRAM_USAGE_LEVEL_TO_OPTIMIZATIONS = {
+    'balanced': {'KEEP_FS_AND_CS_IN_CPU', 'SET_ATTENTION_STEP_TO_4'},
     'low': {'KEEP_ENTIRE_MODEL_IN_CPU'},
-    'medium': {'KEEP_FS_AND_CS_IN_CPU', 'SET_ATTENTION_STEP_TO_4'},
     'high': {},
 }
 
@@ -125,9 +125,24 @@ def resolve_model_paths(task_data: TaskData):
     if task_data.use_upscale: task_data.use_upscale = resolve_model_to_use(task_data.use_upscale, 'gfpgan')
 
 def set_vram_optimizations(context: Context):
+    def is_greater(a, b): # is a > b?
+        if a == "low": # b will be "low", "balanced" or "high"
+            return False
+        elif a == "balanced" and b != "low": # b will be "balanced" or "high"
+            return False
+        return True
+
     config = app.getConfig()
-    perf_level = config.get('performance_level', device_manager.get_max_perf_level(context.device))
-    vram_optimizations = PERF_LEVEL_TO_VRAM_OPTIMIZATIONS[perf_level]
+
+    max_usage_level = device_manager.get_max_vram_usage_level(context.device)
+    vram_usage_level = config.get('vram_usage_level', 'balanced')
+
+    if is_greater(vram_usage_level, max_usage_level):
+        log.error(f'Requested GPU Memory Usage level ({vram_usage_level}) is higher than what is ' + \
+                  f'possible ({max_usage_level}) on this device ({context.device}). Using "{max_usage_level}" instead')
+        vram_usage_level = max_usage_level
+
+    vram_optimizations = VRAM_USAGE_LEVEL_TO_OPTIMIZATIONS[vram_usage_level]
 
     if vram_optimizations != context.vram_optimizations:
         context.vram_optimizations = vram_optimizations
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 0780283d..094d853c 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -341,7 +341,7 @@ def get_devices():
             'name': torch.cuda.get_device_name(device),
             'mem_free': mem_free,
             'mem_total': mem_total,
-            'max_perf_level': device_manager.get_max_perf_level(device),
+            'max_vram_usage_level': device_manager.get_max_vram_usage_level(device),
         }
 
     # list the compatible devices
diff --git a/ui/server.py b/ui/server.py
index 11d3731a..59881975 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -134,7 +134,7 @@ def render(req: dict):
 
         render_req.init_image_mask = req.get('mask') # hack: will rename this in the HTTP API in a future revision
 
-        app.save_to_config(task_data.use_stable_diffusion_model, task_data.use_vae_model, task_data.use_hypernetwork_model, task_data.performance_level)
+        app.save_to_config(task_data.use_stable_diffusion_model, task_data.use_vae_model, task_data.use_hypernetwork_model, task_data.vram_usage_level)
 
         # enqueue the task
         new_task = task_manager.render(render_req, task_data)

From 25639cc3f80f56486308117ab26adee4d15cf19f Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 16 Dec 2022 14:11:55 +0530
Subject: [PATCH 48/74] Tweak Memory Usage setting text; Fix a bug with the
 memory usage setting comparison

---
 ui/media/js/parameters.js       |  4 ++--
 ui/sd_internal/model_manager.py | 10 ++--------
 2 files changed, 4 insertions(+), 10 deletions(-)

diff --git a/ui/media/js/parameters.js b/ui/media/js/parameters.js
index 93f1a266..a8bd3b86 100644
--- a/ui/media/js/parameters.js
+++ b/ui/media/js/parameters.js
@@ -97,8 +97,8 @@ var PARAMETERS = [
         id: "vram_usage_level",
         type: ParameterType.select,
         label: "GPU Memory Usage",
-        note: "Faster performance requires more GPU memory<br/><br/>" +
-              "<b>Balanced:</b> almost as fast as High, significantly lower GPU memory usage<br/>" +
+        note: "Faster performance requires more GPU memory (VRAM)<br/><br/>" +
+              "<b>Balanced:</b> nearly as fast as High, much lower VRAM usage<br/>" +
               "<b>High:</b> fastest, maximum GPU memory usage</br>" +
               "<b>Low:</b> slowest, force-used for GPUs with 4 GB (or less) memory",
         icon: "fa-forward",
diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index 56f1d9c0..e7729b81 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -125,19 +125,13 @@ def resolve_model_paths(task_data: TaskData):
     if task_data.use_upscale: task_data.use_upscale = resolve_model_to_use(task_data.use_upscale, 'gfpgan')
 
 def set_vram_optimizations(context: Context):
-    def is_greater(a, b): # is a > b?
-        if a == "low": # b will be "low", "balanced" or "high"
-            return False
-        elif a == "balanced" and b != "low": # b will be "balanced" or "high"
-            return False
-        return True
-
     config = app.getConfig()
 
     max_usage_level = device_manager.get_max_vram_usage_level(context.device)
     vram_usage_level = config.get('vram_usage_level', 'balanced')
 
-    if is_greater(vram_usage_level, max_usage_level):
+    v = {'low': 0, 'balanced': 1, 'high': 2}
+    if v[vram_usage_level] > v[max_usage_level]:
         log.error(f'Requested GPU Memory Usage level ({vram_usage_level}) is higher than what is ' + \
                   f'possible ({max_usage_level}) on this device ({context.device}). Using "{max_usage_level}" instead')
         vram_usage_level = max_usage_level

From aa8b50280b66cc69ecb449a37068af9bab2e2a43 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Fri, 16 Dec 2022 15:31:55 +0530
Subject: [PATCH 49/74] Remove the test_sd2 flag, the code now works with SD
 2.0

---
 ui/media/js/parameters.js       | 18 +-----------------
 ui/sd_internal/app.py           |  4 ----
 ui/sd_internal/model_manager.py |  5 -----
 ui/server.py                    |  3 ---
 4 files changed, 1 insertion(+), 29 deletions(-)

diff --git a/ui/media/js/parameters.js b/ui/media/js/parameters.js
index a8bd3b86..4e7db4f5 100644
--- a/ui/media/js/parameters.js
+++ b/ui/media/js/parameters.js
@@ -164,14 +164,6 @@ var PARAMETERS = [
             return `<input id="${parameter.id}" name="${parameter.id}" size="6" value="9000" onkeypress="preventNonNumericalInput(event)">`
         }
     },
-    {
-        id: "test_sd2",
-        type: ParameterType.checkbox,
-        label: "Test SD 2.0",
-        note: "Experimental! High memory usage! GPU-only! Not the final version! Please restart the program after changing this.",
-        icon: "fa-fire",
-        default: false,
-    },
     {
         id: "use_beta_channel",
         type: ParameterType.checkbox,
@@ -235,7 +227,6 @@ let saveToDiskField = document.querySelector('#save_to_disk')
 let diskPathField = document.querySelector('#diskPath')
 let listenToNetworkField = document.querySelector("#listen_to_network")
 let listenPortField = document.querySelector("#listen_port")
-let testSD2Field = document.querySelector("#test_sd2")
 let useBetaChannelField = document.querySelector("#use_beta_channel")
 let uiOpenBrowserOnStartField = document.querySelector("#ui_open_browser_on_start")
 let confirmDangerousActionsField = document.querySelector("#confirm_dangerous_actions")
@@ -272,12 +263,6 @@ async function getAppConfig() {
         if (config.ui && config.ui.open_browser_on_start === false) {
             uiOpenBrowserOnStartField.checked = false
         }
-        if ('test_sd2' in config) {
-            testSD2Field.checked = config['test_sd2']
-        }
-
-        let testSD2SettingEntry = getParameterSettingsEntry('test_sd2')
-        testSD2SettingEntry.style.display = (config.update_branch === 'beta' ? '' : 'none')
         if (config.net && config.net.listen_to_network === false) {
             listenToNetworkField.checked = false
         }
@@ -442,8 +427,7 @@ saveSettingsBtn.addEventListener('click', function() {
         'update_branch': updateBranch,
         'ui_open_browser_on_start': uiOpenBrowserOnStartField.checked,
         'listen_to_network': listenToNetworkField.checked,
-        'listen_port': listenPortField.value,
-        'test_sd2': testSD2Field.checked
+        'listen_port': listenPortField.value
     })
     saveSettingsBtn.classList.add('active')
     asyncDelay(300).then(() => saveSettingsBtn.classList.remove('active'))
diff --git a/ui/sd_internal/app.py b/ui/sd_internal/app.py
index 063069d2..471ee074 100644
--- a/ui/sd_internal/app.py
+++ b/ui/sd_internal/app.py
@@ -83,8 +83,6 @@ def setConfig(config):
         bind_ip = '0.0.0.0' if config['net']['listen_to_network'] else '127.0.0.1'
         config_bat.append(f"@set SD_UI_BIND_IP={bind_ip}")
 
-        config_bat.append(f"@set test_sd2={'Y' if config.get('test_sd2', False) else 'N'}")
-
         if len(config_bat) > 0:
             with open(config_bat_path, 'w', encoding='utf-8') as f:
                 f.write('\r\n'.join(config_bat))
@@ -102,8 +100,6 @@ def setConfig(config):
         bind_ip = '0.0.0.0' if config['net']['listen_to_network'] else '127.0.0.1'
         config_sh.append(f"export SD_UI_BIND_IP={bind_ip}")
 
-        config_sh.append(f"export test_sd2=\"{'Y' if config.get('test_sd2', False) else 'N'}\"")
-
         if len(config_sh) > 1:
             with open(config_sh_path, 'w', encoding='utf-8') as f:
                 f.write('\n'.join(config_sh))
diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index e7729b81..30e97053 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -65,11 +65,6 @@ def resolve_model_to_use(model_name:str=None, model_type:str=None):
             model_name = config['model'][model_type]
 
     if model_name:
-        is_sd2 = config.get('test_sd2', False)
-        if model_name.startswith('sd2_') and not is_sd2: # temp hack, until SD2 is unified with 1.4
-            log.error('ERROR: Cannot use SD 2.0 models with SD 1.0 code. Using the sd-v1-4 model instead!')
-            model_name = 'sd-v1-4'
-
         # Check models directory
         models_dir_path = os.path.join(app.MODELS_DIR, model_type, model_name)
         for model_extension in model_extensions:
diff --git a/ui/server.py b/ui/server.py
index 59881975..284fed1b 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -41,7 +41,6 @@ class SetAppConfigRequest(BaseModel):
     ui_open_browser_on_start: bool = None
     listen_to_network: bool = None
     listen_port: int = None
-    test_sd2: bool = None
 
 server_api.mount('/media', NoCacheStaticFiles(directory=os.path.join(app.SD_UI_DIR, 'media')), name="media")
 
@@ -67,8 +66,6 @@ async def setAppConfig(req : SetAppConfigRequest):
        if 'net' not in config:
            config['net'] = {}
        config['net']['listen_port'] = int(req.listen_port)
-    if req.test_sd2 is not None:
-        config['test_sd2'] = req.test_sd2
     try:
         app.setConfig(config)
 

From 8189b38e6eec2f749c8a049991586bbb06f1185c Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 17 Dec 2022 15:59:09 +0530
Subject: [PATCH 50/74] Typo in decoding live preview images

---
 ui/sd_internal/renderer.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/ui/sd_internal/renderer.py b/ui/sd_internal/renderer.py
index 55b2c4a7..ce6032bc 100644
--- a/ui/sd_internal/renderer.py
+++ b/ui/sd_internal/renderer.py
@@ -99,15 +99,14 @@ def make_step_callback(req: GenerateImageRequest, task_data: TaskData, data_queu
 
     def update_temp_img(x_samples, task_temp_images: list):
         partial_images = []
-        for i in range(req.num_outputs):
-            img = image_utils.latent_to_img(context, x_samples[i].unsqueeze(0))
+        images = image_utils.latent_samples_to_images(context, x_samples)
+        for i, img in enumerate(images):
             buf = image_utils.img_to_buffer(img, output_format='JPEG')
 
-            del img
-
             context.temp_images[f"{task_data.request_id}/{i}"] = buf
             task_temp_images[i] = buf
             partial_images.append({'path': f"/image/tmp/{task_data.request_id}/{i}"})
+        del images
         return partial_images
 
     def on_image_step(x_samples, i):

From 1595f1ed05d3e03c58a55da3d7f2d3f9f2e27650 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 17 Dec 2022 16:45:43 +0530
Subject: [PATCH 51/74] Add 6 new samplers; Fix a bug where new tasks wouldn't
 started if a previous task was stopped

---
 ui/index.html              | 22 ++++++++++++++--------
 ui/sd_internal/renderer.py |  1 +
 2 files changed, 15 insertions(+), 8 deletions(-)

diff --git a/ui/index.html b/ui/index.html
index c746f6ea..9f36033f 100644
--- a/ui/index.html
+++ b/ui/index.html
@@ -133,14 +133,20 @@
                     </td></tr>
                     <tr id="samplerSelection" class="pl-5"><td><label for="sampler_name">Sampler:</label></td><td>
                         <select id="sampler_name" name="sampler_name">
-                            <option value="plms">plms</option>
-                            <option value="ddim">ddim</option>
-                            <option value="heun">heun</option>
-                            <option value="euler">euler</option>
-                            <option value="euler_a" selected>euler_a</option>
-                            <option value="dpm2">dpm2</option>
-                            <option value="dpm2_a">dpm2_a</option>
-                            <option value="lms">lms</option>
+                            <option value="plms">PLMS</option>
+                            <option value="ddim">DDIM</option>
+                            <option value="heun">Heun</option>
+                            <option value="euler">Euler</option>
+                            <option value="euler_a" selected>Euler Ancestral</option>
+                            <option value="dpm2">DPM2</option>
+                            <option value="dpm2_a">DPM2 Ancestral</option>
+                            <option value="lms">LMS</option>
+                            <option value="dpm_solver_stability">DPM Solver (Stability AI)</option>
+                            <option value="dpmpp_2s_a" selected>DPM++ 2s Ancestral</option>
+                            <option value="dpmpp_2m">DPM++ 2m</option>
+                            <option value="dpmpp_sde">DPM++ SDE</option>
+                            <option value="dpm_fast">DPM Fast</option>
+                            <option value="dpm_adaptive">DPM Adaptive</option>
                         </select>
                         <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/How-to-Use#samplers" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about samplers</span></i></a>
                     </td></tr>
diff --git a/ui/sd_internal/renderer.py b/ui/sd_internal/renderer.py
index ce6032bc..d9ab3f0d 100644
--- a/ui/sd_internal/renderer.py
+++ b/ui/sd_internal/renderer.py
@@ -27,6 +27,7 @@ def init(device):
     device_manager.device_init(context, device)
 
 def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
+    context.stop_processing = False
     log.info(f'request: {save_utils.get_printable_request(req)}')
     log.info(f'task data: {task_data.dict()}')
 

From e483071894a9fb6827b4eb7f07fdbfe031dfdffe Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Mon, 19 Dec 2022 19:27:28 +0530
Subject: [PATCH 52/74] Rename diffusionkit to sdkit; Delete runtime.py
 (historic moment)

---
 ui/sd_internal/__init__.py      |    2 +-
 ui/sd_internal/model_manager.py |    5 +-
 ui/sd_internal/renderer.py      |    4 +-
 ui/sd_internal/runtime.py       | 1078 -------------------------------
 ui/sd_internal/save_utils.py    |   14 +-
 ui/sd_internal/task_manager.py  |    2 +-
 ui/server.py                    |    2 +-
 7 files changed, 14 insertions(+), 1093 deletions(-)
 delete mode 100644 ui/sd_internal/runtime.py

diff --git a/ui/sd_internal/__init__.py b/ui/sd_internal/__init__.py
index 6f702749..3a748431 100644
--- a/ui/sd_internal/__init__.py
+++ b/ui/sd_internal/__init__.py
@@ -1,6 +1,6 @@
 from pydantic import BaseModel
 
-from diffusionkit.types import GenerateImageRequest
+from sdkit.types import GenerateImageRequest
 
 class TaskData(BaseModel):
     request_id: str = None
diff --git a/ui/sd_internal/model_manager.py b/ui/sd_internal/model_manager.py
index 30e97053..ec72e6fa 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/sd_internal/model_manager.py
@@ -1,11 +1,10 @@
 import os
 import logging
 import picklescan.scanner
-import rich
 
 from sd_internal import app, TaskData, device_manager
-from diffusionkit import model_loader
-from diffusionkit.types import Context
+from sdkit.models import model_loader
+from sdkit.types import Context
 
 log = logging.getLogger()
 
diff --git a/ui/sd_internal/renderer.py b/ui/sd_internal/renderer.py
index d9ab3f0d..1d289c99 100644
--- a/ui/sd_internal/renderer.py
+++ b/ui/sd_internal/renderer.py
@@ -6,8 +6,8 @@ import logging
 from sd_internal import device_manager, save_utils
 from sd_internal import TaskData, Response, Image as ResponseImage, UserInitiatedStop
 
-from diffusionkit import model_loader, image_generator, image_utils, filters as image_filters, data_utils
-from diffusionkit.types import Context, GenerateImageRequest, FilterImageRequest
+from sdkit import model_loader, image_generator, image_utils, filters as image_filters
+from sdkit.types import Context, GenerateImageRequest, FilterImageRequest
 
 log = logging.getLogger()
 
diff --git a/ui/sd_internal/runtime.py b/ui/sd_internal/runtime.py
deleted file mode 100644
index 2bf53d0c..00000000
--- a/ui/sd_internal/runtime.py
+++ /dev/null
@@ -1,1078 +0,0 @@
-"""runtime.py: torch device owned by a thread.
-Notes:
-    Avoid device switching, transfering all models will get too complex.
-    To use a diffrent device signal the current render device to exit
-    And then start a new clean thread for the new device.
-"""
-import json
-import os, re
-import traceback
-import queue
-import torch
-import numpy as np
-from gc import collect as gc_collect
-from omegaconf import OmegaConf
-from PIL import Image, ImageOps
-from tqdm import tqdm, trange
-from itertools import islice
-from einops import rearrange
-import time
-from pytorch_lightning import seed_everything
-from torch import autocast
-from contextlib import nullcontext
-from einops import rearrange, repeat
-from ldm.util import instantiate_from_config
-from transformers import logging
-
-from gfpgan import GFPGANer
-from basicsr.archs.rrdbnet_arch import RRDBNet
-from realesrgan import RealESRGANer
-
-from server import HYPERNETWORK_MODEL_EXTENSIONS# , STABLE_DIFFUSION_MODEL_EXTENSIONS, VAE_MODEL_EXTENSIONS
-
-from threading import Lock
-from safetensors.torch import load_file
-
-import uuid
-
-logging.set_verbosity_error()
-
-# consts
-config_yaml = "optimizedSD/v1-inference.yaml"
-filename_regex = re.compile('[^a-zA-Z0-9]')
-gfpgan_temp_device_lock = Lock() # workaround: gfpgan currently can only start on one device at a time.
-
-# api stuff
-from sd_internal import device_manager
-from . import Request, Response, Image as ResponseImage
-import base64
-from io import BytesIO
-#from colorama import Fore
-
-from threading import local as LocalThreadVars
-thread_data = LocalThreadVars()
-
-def thread_init(device):
-    # Thread bound properties
-    thread_data.stop_processing = False
-    thread_data.temp_images = {}
-
-    thread_data.ckpt_file = None
-    thread_data.vae_file = None
-    thread_data.hypernetwork_file = None
-    thread_data.gfpgan_file = None
-    thread_data.real_esrgan_file = None
-
-    thread_data.model = None
-    thread_data.modelCS = None
-    thread_data.modelFS = None
-    thread_data.hypernetwork = None
-    thread_data.hypernetwork_strength = 1
-    thread_data.model_gfpgan = None
-    thread_data.model_real_esrgan = None
-
-    thread_data.model_is_half = False
-    thread_data.model_fs_is_half = False
-    thread_data.device = None
-    thread_data.device_name = None
-    thread_data.unet_bs = 1
-    thread_data.precision = 'autocast'
-    thread_data.sampler_plms = None
-    thread_data.sampler_ddim = None
-
-    thread_data.turbo = False
-    thread_data.force_full_precision = False
-    thread_data.reduced_memory = True
-
-    thread_data.test_sd2 = isSD2()
-
-    device_manager.device_init(thread_data, device)
-
-# temp hack, will remove soon
-def isSD2():
-    try:
-        SD_UI_DIR = os.getenv('SD_UI_PATH', None)
-        CONFIG_DIR = os.path.abspath(os.path.join(SD_UI_DIR, '..', 'scripts'))
-        config_json_path = os.path.join(CONFIG_DIR, 'config.json')
-        if not os.path.exists(config_json_path):
-            return False
-        with open(config_json_path, 'r', encoding='utf-8') as f:
-            config = json.load(f)
-            return config.get('test_sd2', False)
-    except Exception as e:
-        return False
-
-def load_model_ckpt():
-    if not thread_data.ckpt_file: raise ValueError(f'Thread ckpt_file is undefined.')
-    if os.path.exists(thread_data.ckpt_file + '.ckpt'):
-        thread_data.ckpt_file += '.ckpt'
-    elif os.path.exists(thread_data.ckpt_file + '.safetensors'):
-        thread_data.ckpt_file += '.safetensors'
-    elif not os.path.exists(thread_data.ckpt_file):
-        raise FileNotFoundError(f'Cannot find {thread_data.ckpt_file}.ckpt or .safetensors')
-
-    if not thread_data.precision:
-        thread_data.precision = 'full' if thread_data.force_full_precision else 'autocast'
-
-    if not thread_data.unet_bs:
-        thread_data.unet_bs = 1
-
-    if thread_data.device == 'cpu':
-        thread_data.precision = 'full'
-
-    print('loading', thread_data.ckpt_file, 'to device', thread_data.device, 'using precision', thread_data.precision)
-
-    if thread_data.test_sd2:
-        load_model_ckpt_sd2()
-    else:
-        load_model_ckpt_sd1()
-
-def load_model_ckpt_sd1():
-    sd, model_ver = load_model_from_config(thread_data.ckpt_file)
-    li, lo = [], []
-    for key, value in sd.items():
-        sp = key.split(".")
-        if (sp[0]) == "model":
-            if "input_blocks" in sp:
-                li.append(key)
-            elif "middle_block" in sp:
-                li.append(key)
-            elif "time_embed" in sp:
-                li.append(key)
-            else:
-                lo.append(key)
-    for key in li:
-        sd["model1." + key[6:]] = sd.pop(key)
-    for key in lo:
-        sd["model2." + key[6:]] = sd.pop(key)
-
-    config = OmegaConf.load(f"{config_yaml}")
-
-    model = instantiate_from_config(config.modelUNet)
-    _, _ = model.load_state_dict(sd, strict=False)
-    model.eval()
-    model.cdevice = torch.device(thread_data.device)
-    model.unet_bs = thread_data.unet_bs
-    model.turbo = thread_data.turbo
-    # if thread_data.device != 'cpu':
-    #     model.to(thread_data.device)
-    #if thread_data.reduced_memory:
-        #model.model1.to("cpu")
-        #model.model2.to("cpu")
-    thread_data.model = model
-
-    modelCS = instantiate_from_config(config.modelCondStage)
-    _, _ = modelCS.load_state_dict(sd, strict=False)
-    modelCS.eval()
-    modelCS.cond_stage_model.device = torch.device(thread_data.device)
-    # if thread_data.device != 'cpu':
-    #     if thread_data.reduced_memory:
-    #         modelCS.to('cpu')
-    #     else:
-    #         modelCS.to(thread_data.device) # Preload on device if not already there.
-    thread_data.modelCS = modelCS
-
-    modelFS = instantiate_from_config(config.modelFirstStage)
-    _, _ = modelFS.load_state_dict(sd, strict=False)
-
-    if thread_data.vae_file is not None:
-        try:
-            loaded = False
-            for model_extension in ['.ckpt', '.vae.pt']:
-                if os.path.exists(thread_data.vae_file + model_extension):
-                    print(f"Loading VAE weights from: {thread_data.vae_file}{model_extension}")
-                    vae_ckpt = torch.load(thread_data.vae_file + model_extension, map_location="cpu")
-                    vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
-                    modelFS.first_stage_model.load_state_dict(vae_dict, strict=False)
-                    loaded = True
-                    break
-
-            if not loaded:
-                print(f'Cannot find VAE: {thread_data.vae_file}')
-                thread_data.vae_file = None
-        except:
-            print(traceback.format_exc())
-            print(f'Could not load VAE: {thread_data.vae_file}')
-            thread_data.vae_file = None
-
-    modelFS.eval()
-    # if thread_data.device != 'cpu':
-    #     if thread_data.reduced_memory:
-    #         modelFS.to('cpu')
-    #     else:
-    #         modelFS.to(thread_data.device) # Preload on device if not already there.
-    thread_data.modelFS = modelFS
-    del sd
-
-    if thread_data.device != "cpu" and thread_data.precision == "autocast":
-        thread_data.model.half()
-        thread_data.modelCS.half()
-        thread_data.modelFS.half()
-        thread_data.model_is_half = True
-        thread_data.model_fs_is_half = True
-    else:
-        thread_data.model_is_half = False
-        thread_data.model_fs_is_half = False
-
-    print(f'''loaded model
- model file: {thread_data.ckpt_file}
- model.device: {model.device}
- modelCS.device: {modelCS.cond_stage_model.device}
- modelFS.device: {thread_data.modelFS.device}
- using precision: {thread_data.precision}''')
-
-def load_model_ckpt_sd2():
-    sd, model_ver = load_model_from_config(thread_data.ckpt_file)
-
-    config_file = 'configs/stable-diffusion/v2-inference-v.yaml' if model_ver == 'sd2' else "configs/stable-diffusion/v1-inference.yaml"
-    config = OmegaConf.load(config_file)
-    verbose = False
-
-    thread_data.model = instantiate_from_config(config.model)
-    m, u = thread_data.model.load_state_dict(sd, strict=False)
-    if len(m) > 0 and verbose:
-        print("missing keys:")
-        print(m)
-    if len(u) > 0 and verbose:
-        print("unexpected keys:")
-        print(u)
-
-    thread_data.model.to(thread_data.device)
-    thread_data.model.eval()
-    del sd
-
-    thread_data.model.cond_stage_model.device = torch.device(thread_data.device)
-
-    if thread_data.device != "cpu" and thread_data.precision == "autocast":
-        thread_data.model.half()
-        thread_data.model_is_half = True
-        thread_data.model_fs_is_half = True
-    else:
-        thread_data.model_is_half = False
-        thread_data.model_fs_is_half = False
-
-    print(f'''loaded model
- model file: {thread_data.ckpt_file}
- using precision: {thread_data.precision}''')
-
-def unload_filters():
-    if thread_data.model_gfpgan is not None:
-        if thread_data.device != 'cpu': thread_data.model_gfpgan.gfpgan.to('cpu')
-
-        del thread_data.model_gfpgan
-    thread_data.model_gfpgan = None
-
-    if thread_data.model_real_esrgan is not None:
-        if thread_data.device != 'cpu': thread_data.model_real_esrgan.model.to('cpu')
-
-        del thread_data.model_real_esrgan
-    thread_data.model_real_esrgan = None
-
-    gc()
-
-def unload_models():
-    if thread_data.model is not None:
-        print('Unloading models...')
-        if thread_data.device != 'cpu':
-            if not thread_data.test_sd2:
-                thread_data.modelFS.to('cpu')
-                thread_data.modelCS.to('cpu')
-                thread_data.model.model1.to("cpu")
-                thread_data.model.model2.to("cpu")
-
-        del thread_data.model
-        del thread_data.modelCS
-        del thread_data.modelFS
-
-    thread_data.model = None
-    thread_data.modelCS = None
-    thread_data.modelFS = None
-
-    gc()
-
-# def wait_model_move_to(model, target_device): # Send to target_device and wait until complete.
-#     if thread_data.device == target_device: return
-#     start_mem = torch.cuda.memory_allocated(thread_data.device) / 1e6
-#     if start_mem <= 0: return
-#     model_name = model.__class__.__name__
-#     print(f'Device {thread_data.device} - Sending model {model_name} to {target_device} | Memory transfer starting. Memory Used: {round(start_mem)}Mb')
-#     start_time = time.time()
-#     model.to(target_device)
-#     time_step = start_time
-#     WARNING_TIMEOUT = 1.5 # seconds - Show activity in console after timeout.
-#     last_mem = start_mem
-#     is_transfering = True
-#     while is_transfering:
-#         time.sleep(0.5) # 500ms
-#         mem = torch.cuda.memory_allocated(thread_data.device) / 1e6
-#         is_transfering = bool(mem > 0 and mem < last_mem) # still stuff loaded, but less than last time.
-#         last_mem = mem
-#         if not is_transfering:
-#             break;
-#         if time.time() - time_step > WARNING_TIMEOUT: # Long delay, print to console to show activity.
-#             print(f'Device {thread_data.device} - Waiting for Memory transfer. Memory Used: {round(mem)}Mb, Transfered: {round(start_mem - mem)}Mb')
-#             time_step = time.time()
-#     print(f'Device {thread_data.device} - {model_name} Moved: {round(start_mem - last_mem)}Mb in {round(time.time() - start_time, 3)} seconds to {target_device}')
-
-def move_to_cpu(model):
-    if thread_data.device != "cpu":
-        d = torch.device(thread_data.device)
-        mem = torch.cuda.memory_allocated(d) / 1e6
-        model.to("cpu")
-        while torch.cuda.memory_allocated(d) / 1e6 >= mem:
-            time.sleep(1)
-
-def load_model_gfpgan():
-    if thread_data.gfpgan_file is None: raise ValueError(f'Thread gfpgan_file is undefined.')
-    model_path = thread_data.gfpgan_file + ".pth"
-    thread_data.model_gfpgan = GFPGANer(device=torch.device(thread_data.device), model_path=model_path, upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None)
-    print('loaded', thread_data.gfpgan_file, 'to', thread_data.model_gfpgan.device, 'precision', thread_data.precision)
-
-def load_model_real_esrgan():
-    if thread_data.real_esrgan_file is None: raise ValueError(f'Thread real_esrgan_file is undefined.')
-    model_path = thread_data.real_esrgan_file + ".pth"
-
-    RealESRGAN_models = {
-        'RealESRGAN_x4plus': RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4),
-        'RealESRGAN_x4plus_anime_6B': RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=6, num_grow_ch=32, scale=4)
-    }
-
-    model_to_use = RealESRGAN_models[thread_data.real_esrgan_file]
-
-    if thread_data.device == 'cpu':
-        thread_data.model_real_esrgan = RealESRGANer(device=torch.device(thread_data.device), scale=2, model_path=model_path, model=model_to_use, pre_pad=0, half=False) # cpu does not support half
-        #thread_data.model_real_esrgan.device = torch.device(thread_data.device)
-        thread_data.model_real_esrgan.model.to('cpu')
-    else:
-        thread_data.model_real_esrgan = RealESRGANer(device=torch.device(thread_data.device), scale=2, model_path=model_path, model=model_to_use, pre_pad=0, half=thread_data.model_is_half)
-
-    thread_data.model_real_esrgan.model.name = thread_data.real_esrgan_file
-    print('loaded ', thread_data.real_esrgan_file, 'to', thread_data.model_real_esrgan.device, 'precision', thread_data.precision)
-
-
-def get_session_out_path(disk_path, session_id):
-    if disk_path is None: return None
-    if session_id is None: return None
-
-    session_out_path = os.path.join(disk_path, filename_regex.sub('_',session_id))
-    os.makedirs(session_out_path, exist_ok=True)
-    return session_out_path
-
-def get_base_path(disk_path, session_id, prompt, img_id, ext, suffix=None):
-    if disk_path is None: return None
-    if session_id is None: return None
-    if ext is None: raise Exception('Missing ext')
-
-    session_out_path = get_session_out_path(disk_path, session_id)
-
-    prompt_flattened = filename_regex.sub('_', prompt)[:50]
-
-    if suffix is not None:
-        return os.path.join(session_out_path, f"{prompt_flattened}_{img_id}_{suffix}.{ext}")
-    return os.path.join(session_out_path, f"{prompt_flattened}_{img_id}.{ext}")
-
-def apply_filters(filter_name, image_data, model_path=None):
-    print(f'Applying filter {filter_name}...')
-    gc() # Free space before loading new data.
-
-    if isinstance(image_data, torch.Tensor):
-        image_data.to(thread_data.device)
-
-    if filter_name == 'gfpgan':
-        # This lock is only ever used here. No need to use timeout for the request. Should never deadlock.
-        with gfpgan_temp_device_lock: # Wait for any other devices to complete before starting.
-            # hack for a bug in facexlib: https://github.com/xinntao/facexlib/pull/19/files
-            from facexlib.detection import retinaface
-            retinaface.device = torch.device(thread_data.device)
-            print('forced retinaface.device to', thread_data.device)
-
-            if model_path is not None and model_path != thread_data.gfpgan_file:
-                thread_data.gfpgan_file = model_path
-                load_model_gfpgan()
-            elif not thread_data.model_gfpgan:
-                load_model_gfpgan()
-            if thread_data.model_gfpgan is None: raise Exception('Model "gfpgan" not loaded.')
-
-            print('enhance with', thread_data.gfpgan_file, 'on', thread_data.model_gfpgan.device, 'precision', thread_data.precision)
-            _, _, output = thread_data.model_gfpgan.enhance(image_data[:,:,::-1], has_aligned=False, only_center_face=False, paste_back=True)
-            image_data = output[:,:,::-1]
-
-    if filter_name == 'real_esrgan':
-        if model_path is not None and model_path != thread_data.real_esrgan_file:
-            thread_data.real_esrgan_file = model_path
-            load_model_real_esrgan()
-        elif not thread_data.model_real_esrgan:
-            load_model_real_esrgan()
-        if thread_data.model_real_esrgan is None: raise Exception('Model "gfpgan" not loaded.')
-        print('enhance with', thread_data.real_esrgan_file, 'on', thread_data.model_real_esrgan.device, 'precision', thread_data.precision)
-        output, _ = thread_data.model_real_esrgan.enhance(image_data[:,:,::-1])
-        image_data = output[:,:,::-1]
-
-    return image_data
-
-def is_model_reload_necessary(req: Request):
-    # custom model support:
-    #  the req.use_stable_diffusion_model needs to be a valid path
-    #  to the ckpt file (without the extension).
-    if os.path.exists(req.use_stable_diffusion_model + '.ckpt'):
-        req.use_stable_diffusion_model += '.ckpt'
-    elif os.path.exists(req.use_stable_diffusion_model + '.safetensors'):
-        req.use_stable_diffusion_model += '.safetensors'
-    elif not os.path.exists(req.use_stable_diffusion_model): 
-        raise FileNotFoundError(f'Cannot find {req.use_stable_diffusion_model}.ckpt or .safetensors')
-
-    needs_model_reload = False
-    if not thread_data.model or thread_data.ckpt_file != req.use_stable_diffusion_model or thread_data.vae_file != req.use_vae_model:
-        thread_data.ckpt_file = req.use_stable_diffusion_model
-        thread_data.vae_file = req.use_vae_model
-        needs_model_reload = True
-
-    if thread_data.device != 'cpu':
-        if (thread_data.precision == 'autocast' and (req.use_full_precision or not thread_data.model_is_half)) or \
-            (thread_data.precision == 'full' and not req.use_full_precision and not thread_data.force_full_precision):
-            thread_data.precision = 'full' if req.use_full_precision else 'autocast'
-            needs_model_reload = True
-
-    return needs_model_reload
-
-def reload_model():
-    unload_models()
-    unload_filters()
-    load_model_ckpt()
-
-def is_hypernetwork_reload_necessary(req: Request):
-    needs_model_reload = False
-    if thread_data.hypernetwork_file != req.use_hypernetwork_model:
-        thread_data.hypernetwork_file = req.use_hypernetwork_model
-        needs_model_reload = True
-
-    return needs_model_reload
-
-def load_hypernetwork():
-    if thread_data.test_sd2:
-        # Not yet supported in SD2
-        return
-
-    from . import hypernetwork
-    if thread_data.hypernetwork_file is not None:
-        try:
-            loaded = False
-            for model_extension in HYPERNETWORK_MODEL_EXTENSIONS:
-                if os.path.exists(thread_data.hypernetwork_file + model_extension):
-                    print(f"Loading hypernetwork weights from: {thread_data.hypernetwork_file}{model_extension}")
-                    thread_data.hypernetwork = hypernetwork.load_hypernetwork(thread_data.hypernetwork_file + model_extension)
-                    loaded = True
-                    break
-
-            if not loaded:
-                print(f'Cannot find hypernetwork: {thread_data.hypernetwork_file}')
-                thread_data.hypernetwork_file = None
-        except:
-            print(traceback.format_exc())
-            print(f'Could not load hypernetwork: {thread_data.hypernetwork_file}')
-            thread_data.hypernetwork_file = None
-
-def unload_hypernetwork():
-    if thread_data.hypernetwork is not None:
-        print('Unloading hypernetwork...')
-        if thread_data.device != 'cpu':
-            for i in thread_data.hypernetwork:
-                thread_data.hypernetwork[i][0].to('cpu')
-                thread_data.hypernetwork[i][1].to('cpu')
-        del thread_data.hypernetwork
-    thread_data.hypernetwork = None
-
-    gc()
-
-def reload_hypernetwork():
-    unload_hypernetwork()
-    load_hypernetwork()
-
-def mk_img(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
-    try:
-        return do_mk_img(req, data_queue, task_temp_images, step_callback)
-    except Exception as e:
-        print(traceback.format_exc())
-
-        if thread_data.device != 'cpu' and not thread_data.test_sd2:
-            thread_data.modelFS.to('cpu')
-            thread_data.modelCS.to('cpu')
-            thread_data.model.model1.to("cpu")
-            thread_data.model.model2.to("cpu")
-
-        gc() # Release from memory.
-        data_queue.put(json.dumps({
-            "status": 'failed',
-            "detail": str(e)
-        }))
-        raise e
-
-def update_temp_img(req, x_samples, task_temp_images: list):
-    partial_images = []
-    for i in range(req.num_outputs):
-        if thread_data.test_sd2:
-            x_sample_ddim = thread_data.model.decode_first_stage(x_samples[i].unsqueeze(0))
-        else:
-            x_sample_ddim = thread_data.modelFS.decode_first_stage(x_samples[i].unsqueeze(0))
-        x_sample = torch.clamp((x_sample_ddim + 1.0) / 2.0, min=0.0, max=1.0)
-        x_sample = 255.0 * rearrange(x_sample[0].cpu().numpy(), "c h w -> h w c")
-        x_sample = x_sample.astype(np.uint8)
-        img = Image.fromarray(x_sample)
-        buf = img_to_buffer(img, output_format='JPEG')
-
-        del img, x_sample, x_sample_ddim
-        # don't delete x_samples, it is used in the code that called this callback
-
-        thread_data.temp_images[f'{req.request_id}/{i}'] = buf
-        task_temp_images[i] = buf
-        partial_images.append({'path': f'/image/tmp/{req.request_id}/{i}'})
-    return partial_images
-
-# Build and return the apropriate generator for do_mk_img
-def get_image_progress_generator(req, data_queue: queue.Queue, task_temp_images: list, step_callback, extra_props=None):
-    if not req.stream_progress_updates:
-        def empty_callback(x_samples, i):
-            step_callback()
-        return empty_callback
-
-    thread_data.partial_x_samples = None
-    last_callback_time = -1
-    def img_callback(x_samples, i):
-        nonlocal last_callback_time
-
-        thread_data.partial_x_samples = x_samples
-        step_time = time.time() - last_callback_time if last_callback_time != -1 else -1
-        last_callback_time = time.time()
-
-        progress = {"step": i, "step_time": step_time}
-        if extra_props is not None:
-            progress.update(extra_props)
-
-        if req.stream_image_progress and i % 5 == 0:
-            progress['output'] = update_temp_img(req, x_samples, task_temp_images)
-
-        data_queue.put(json.dumps(progress))
-
-        step_callback()
-
-        if thread_data.stop_processing:
-            raise UserInitiatedStop("User requested that we stop processing")
-    return img_callback
-
-def do_mk_img(req: Request, data_queue: queue.Queue, task_temp_images: list, step_callback):
-    thread_data.stop_processing = False
-
-    res = Response()
-    res.request = req
-    res.images = []
-    thread_data.hypernetwork_strength = req.hypernetwork_strength
-
-    thread_data.temp_images.clear()
-
-    if thread_data.turbo != req.turbo and not thread_data.test_sd2:
-        thread_data.turbo = req.turbo
-        thread_data.model.turbo = req.turbo
-
-    # Start by cleaning memory, loading and unloading things can leave memory allocated.
-    gc()
-
-    opt_prompt = req.prompt
-    opt_seed = req.seed
-    opt_n_iter = 1
-    opt_C = 4
-    opt_f = 8
-    opt_ddim_eta = 0.0
-
-    print(req, '\n    device', torch.device(thread_data.device), "as", thread_data.device_name)
-    print('\n\n    Using precision:', thread_data.precision)
-
-    seed_everything(opt_seed)
-
-    batch_size = req.num_outputs
-    prompt = opt_prompt
-    assert prompt is not None
-    data = [batch_size * [prompt]]
-
-    if thread_data.precision == "autocast" and thread_data.device != "cpu":
-        precision_scope = autocast
-    else:
-        precision_scope = nullcontext
-
-    mask = None
-
-    if req.init_image is None:
-        handler = _txt2img
-
-        init_latent = None
-        t_enc = None
-    else:
-        handler = _img2img
-
-        init_image = load_img(req.init_image, req.width, req.height)
-        init_image = init_image.to(thread_data.device)
-
-        if thread_data.device != "cpu" and thread_data.precision == "autocast":
-            init_image = init_image.half()
-
-        if not thread_data.test_sd2:
-            thread_data.modelFS.to(thread_data.device)
-
-        init_image = repeat(init_image, '1 ... -> b ...', b=batch_size)
-        if thread_data.test_sd2:
-            init_latent = thread_data.model.get_first_stage_encoding(thread_data.model.encode_first_stage(init_image))  # move to latent space
-        else:
-            init_latent = thread_data.modelFS.get_first_stage_encoding(thread_data.modelFS.encode_first_stage(init_image))  # move to latent space
-
-        if req.mask is not None:
-            mask = load_mask(req.mask, req.width, req.height, init_latent.shape[2], init_latent.shape[3], True).to(thread_data.device)
-            mask = mask[0][0].unsqueeze(0).repeat(4, 1, 1).unsqueeze(0)
-            mask = repeat(mask, '1 ... -> b ...', b=batch_size)
-
-            if thread_data.device != "cpu" and thread_data.precision == "autocast":
-                mask = mask.half()
-
-        # Send to CPU and wait until complete.
-        # wait_model_move_to(thread_data.modelFS, 'cpu')
-        if not thread_data.test_sd2:
-            move_to_cpu(thread_data.modelFS)
-
-        assert 0. <= req.prompt_strength <= 1., 'can only work with strength in [0.0, 1.0]'
-        t_enc = int(req.prompt_strength * req.num_inference_steps)
-        print(f"target t_enc is {t_enc} steps")
-
-    with torch.no_grad():
-        for n in trange(opt_n_iter, desc="Sampling"):
-            for prompts in tqdm(data, desc="data"):
-
-                with precision_scope("cuda"):
-                    if thread_data.reduced_memory and not thread_data.test_sd2:
-                        thread_data.modelCS.to(thread_data.device)
-                    uc = None
-                    if req.guidance_scale != 1.0:
-                        if thread_data.test_sd2:
-                            uc = thread_data.model.get_learned_conditioning(batch_size * [req.negative_prompt])
-                        else:
-                            uc = thread_data.modelCS.get_learned_conditioning(batch_size * [req.negative_prompt])
-                    if isinstance(prompts, tuple):
-                        prompts = list(prompts)
-
-                    subprompts, weights = split_weighted_subprompts(prompts[0])
-                    if len(subprompts) > 1:
-                        c = torch.zeros_like(uc)
-                        totalWeight = sum(weights)
-                        # normalize each "sub prompt" and add it
-                        for i in range(len(subprompts)):
-                            weight = weights[i]
-                            # if not skip_normalize:
-                            weight = weight / totalWeight
-                            if thread_data.test_sd2:
-                                c = torch.add(c, thread_data.model.get_learned_conditioning(subprompts[i]), alpha=weight)
-                            else:
-                                c = torch.add(c, thread_data.modelCS.get_learned_conditioning(subprompts[i]), alpha=weight)
-                    else:
-                        if thread_data.test_sd2:
-                            c = thread_data.model.get_learned_conditioning(prompts)
-                        else:
-                            c = thread_data.modelCS.get_learned_conditioning(prompts)
-
-                    if thread_data.reduced_memory and not thread_data.test_sd2:
-                        thread_data.modelFS.to(thread_data.device)
-
-                    n_steps = req.num_inference_steps if req.init_image is None else t_enc
-                    img_callback = get_image_progress_generator(req, data_queue, task_temp_images, step_callback, {"total_steps": n_steps})
-
-                    # run the handler
-                    try:
-                        print('Running handler...')
-                        if handler == _txt2img:
-                            x_samples = _txt2img(req.width, req.height, req.num_outputs, req.num_inference_steps, req.guidance_scale, None, opt_C, opt_f, opt_ddim_eta, c, uc, opt_seed, img_callback, mask, req.sampler)
-                        else:
-                            x_samples = _img2img(init_latent, t_enc, batch_size, req.guidance_scale, c, uc, req.num_inference_steps, opt_ddim_eta, opt_seed, img_callback, mask, opt_C, req.height, req.width, opt_f)
-                    except UserInitiatedStop:
-                        if not hasattr(thread_data, 'partial_x_samples'):
-                            continue
-                        if thread_data.partial_x_samples is None:
-                            del thread_data.partial_x_samples
-                            continue
-                        x_samples = thread_data.partial_x_samples
-                        del thread_data.partial_x_samples
-
-                    print("decoding images")
-                    img_data = [None] * batch_size
-                    for i in range(batch_size):
-                        if thread_data.test_sd2:
-                            x_samples_ddim = thread_data.model.decode_first_stage(x_samples[i].unsqueeze(0))
-                        else:
-                            x_samples_ddim = thread_data.modelFS.decode_first_stage(x_samples[i].unsqueeze(0))
-                        x_sample = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0)
-                        x_sample = 255.0 * rearrange(x_sample[0].cpu().numpy(), "c h w -> h w c")
-                        x_sample = x_sample.astype(np.uint8)
-                        img_data[i] = x_sample
-                    del x_samples, x_samples_ddim, x_sample
-
-                    print("saving images")
-                    for i in range(batch_size):
-                        img = Image.fromarray(img_data[i])
-                        img_id = base64.b64encode(int(time.time()+i).to_bytes(8, 'big')).decode() # Generate unique ID based on time.
-                        img_id = img_id.translate({43:None, 47:None, 61:None})[-8:] # Remove + / = and keep last 8 chars.
-
-                        has_filters =   (req.use_face_correction is not None and req.use_face_correction.startswith('GFPGAN')) or \
-                                        (req.use_upscale is not None and req.use_upscale.startswith('RealESRGAN'))
-
-                        return_orig_img = not has_filters or not req.show_only_filtered_image
-
-                        if thread_data.stop_processing:
-                            return_orig_img = True
-
-                        if req.save_to_disk_path is not None:
-                            if return_orig_img:
-                                img_out_path = get_base_path(req.save_to_disk_path, req.session_id, prompts[0], img_id, req.output_format)
-                                save_image(img, img_out_path, req.output_format, req.output_quality)
-                            meta_out_path = get_base_path(req.save_to_disk_path, req.session_id, prompts[0], img_id, 'txt')
-                            save_metadata(meta_out_path, req, prompts[0], opt_seed)
-
-                        if return_orig_img:
-                            img_buffer = img_to_buffer(img, req.output_format, req.output_quality)
-                            img_str = buffer_to_base64_str(img_buffer, req.output_format)
-                            res_image_orig = ResponseImage(data=img_str, seed=opt_seed)
-                            res.images.append(res_image_orig)
-                            task_temp_images[i] = img_buffer
-
-                            if req.save_to_disk_path is not None:
-                                res_image_orig.path_abs = img_out_path
-                        del img
-
-                        if has_filters and not thread_data.stop_processing:
-                            filters_applied = []
-                            if req.use_face_correction:
-                                img_data[i] = apply_filters('gfpgan', img_data[i], req.use_face_correction)
-                                filters_applied.append(req.use_face_correction)
-                            if req.use_upscale:
-                                img_data[i] = apply_filters('real_esrgan', img_data[i], req.use_upscale)
-                                filters_applied.append(req.use_upscale)
-                            if (len(filters_applied) > 0):
-                                filtered_image = Image.fromarray(img_data[i])
-                                filtered_buffer = img_to_buffer(filtered_image, req.output_format, req.output_quality)
-                                filtered_img_data = buffer_to_base64_str(filtered_buffer, req.output_format)
-                                response_image = ResponseImage(data=filtered_img_data, seed=opt_seed)
-                                res.images.append(response_image)
-                                task_temp_images[i] = filtered_buffer
-                                if req.save_to_disk_path is not None:
-                                    filtered_img_out_path = get_base_path(req.save_to_disk_path, req.session_id, prompts[0], img_id, req.output_format, "_".join(filters_applied))
-                                    save_image(filtered_image, filtered_img_out_path, req.output_format, req.output_quality)
-                                    response_image.path_abs = filtered_img_out_path
-                                del filtered_image
-                        # Filter Applied, move to next seed
-                        opt_seed += 1
-
-                    # if thread_data.reduced_memory:
-                    #     unload_filters()
-                    if not thread_data.test_sd2:
-                        move_to_cpu(thread_data.modelFS)
-                    del img_data
-                    gc()
-                    if thread_data.device != 'cpu':
-                        print(f'memory_final = {round(torch.cuda.memory_allocated(thread_data.device) / 1e6, 2)}Mb')
-
-    print('Task completed')
-    res = res.json()
-    data_queue.put(json.dumps(res))
-
-    return res
-
-def save_image(img, img_out_path, output_format="", output_quality=75):
-    try:
-        if output_format.upper() == "JPEG":
-            img.save(img_out_path, quality=output_quality)
-        else:
-            img.save(img_out_path)
-    except:
-        print('could not save the file', traceback.format_exc())
-
-def save_metadata(meta_out_path, req, prompt, opt_seed):
-    metadata = f'''{prompt}
-Width: {req.width}
-Height: {req.height}
-Seed: {opt_seed}
-Steps: {req.num_inference_steps}
-Guidance Scale: {req.guidance_scale}
-Prompt Strength: {req.prompt_strength}
-Use Face Correction: {req.use_face_correction}
-Use Upscaling: {req.use_upscale}
-Sampler: {req.sampler}
-Negative Prompt: {req.negative_prompt}
-Stable Diffusion model: {req.use_stable_diffusion_model + '.ckpt'}
-VAE model: {req.use_vae_model}
-Hypernetwork Model: {req.use_hypernetwork_model}
-Hypernetwork Strength: {req.hypernetwork_strength}
-'''
-    try:
-        with open(meta_out_path, 'w', encoding='utf-8') as f:
-            f.write(metadata)
-    except:
-        print('could not save the file', traceback.format_exc())
-
-def _txt2img(opt_W, opt_H, opt_n_samples, opt_ddim_steps, opt_scale, start_code, opt_C, opt_f, opt_ddim_eta, c, uc, opt_seed, img_callback, mask, sampler_name):
-    shape = [opt_n_samples, opt_C, opt_H // opt_f, opt_W // opt_f]
-
-    # Send to CPU and wait until complete.
-    # wait_model_move_to(thread_data.modelCS, 'cpu')
-
-    if not thread_data.test_sd2:
-        move_to_cpu(thread_data.modelCS)
-
-    if thread_data.test_sd2 and sampler_name not in ('plms', 'ddim', 'dpm2'):
-        raise Exception('Only plms, ddim and dpm2 samplers are supported right now, in SD 2.0')
-
-
-    # samples, _ = sampler.sample(S=opt.steps,
-    #                                                  conditioning=c,
-    #                                                  batch_size=opt.n_samples,
-    #                                                  shape=shape,
-    #                                                  verbose=False,
-    #                                                  unconditional_guidance_scale=opt.scale,
-    #                                                  unconditional_conditioning=uc,
-    #                                                  eta=opt.ddim_eta,
-    #                                                  x_T=start_code)
-
-    if thread_data.test_sd2:
-        if sampler_name == 'plms':
-            from ldm.models.diffusion.plms import PLMSSampler
-            sampler = PLMSSampler(thread_data.model)
-        elif sampler_name == 'ddim':
-            from ldm.models.diffusion.ddim import DDIMSampler
-            sampler = DDIMSampler(thread_data.model)
-            sampler.make_schedule(ddim_num_steps=opt_ddim_steps, ddim_eta=opt_ddim_eta, verbose=False)
-        elif sampler_name == 'dpm2':
-            from ldm.models.diffusion.dpm_solver import DPMSolverSampler
-            sampler = DPMSolverSampler(thread_data.model)
-
-        shape = [opt_C, opt_H // opt_f, opt_W // opt_f]
-
-        samples_ddim, intermediates = sampler.sample(
-            S=opt_ddim_steps,
-            conditioning=c,
-            batch_size=opt_n_samples,
-            seed=opt_seed,
-            shape=shape,
-            verbose=False,
-            unconditional_guidance_scale=opt_scale,
-            unconditional_conditioning=uc,
-            eta=opt_ddim_eta,
-            x_T=start_code,
-            img_callback=img_callback,
-            mask=mask,
-            sampler = sampler_name,
-        )
-    else:
-        if sampler_name == 'ddim':
-            thread_data.model.make_schedule(ddim_num_steps=opt_ddim_steps, ddim_eta=opt_ddim_eta, verbose=False)
-
-        samples_ddim = thread_data.model.sample(
-            S=opt_ddim_steps,
-            conditioning=c,
-            seed=opt_seed,
-            shape=shape,
-            verbose=False,
-            unconditional_guidance_scale=opt_scale,
-            unconditional_conditioning=uc,
-            eta=opt_ddim_eta,
-            x_T=start_code,
-            img_callback=img_callback,
-            mask=mask,
-            sampler = sampler_name,
-        )
-    return samples_ddim
-
-def _img2img(init_latent, t_enc, batch_size, opt_scale, c, uc, opt_ddim_steps, opt_ddim_eta, opt_seed, img_callback, mask, opt_C=1, opt_H=1, opt_W=1, opt_f=1):
-    # encode (scaled latent)
-    x_T = None if mask is None else init_latent
-
-    if thread_data.test_sd2:
-        from ldm.models.diffusion.ddim import DDIMSampler
-
-        sampler = DDIMSampler(thread_data.model)
-
-        sampler.make_schedule(ddim_num_steps=opt_ddim_steps, ddim_eta=opt_ddim_eta, verbose=False)
-
-        z_enc = sampler.stochastic_encode(init_latent, torch.tensor([t_enc] * batch_size).to(thread_data.device))
-
-        samples_ddim = sampler.decode(z_enc, c, t_enc, unconditional_guidance_scale=opt_scale,unconditional_conditioning=uc, img_callback=img_callback)
-
-    else:
-        z_enc = thread_data.model.stochastic_encode(
-            init_latent,
-            torch.tensor([t_enc] * batch_size).to(thread_data.device),
-            opt_seed,
-            opt_ddim_eta,
-            opt_ddim_steps,
-        )
-
-        # decode it
-        samples_ddim = thread_data.model.sample(
-            t_enc,
-            c,
-            z_enc,
-            unconditional_guidance_scale=opt_scale,
-            unconditional_conditioning=uc,
-            img_callback=img_callback,
-            mask=mask,
-            x_T=x_T,
-            sampler = 'ddim'
-        )
-    return samples_ddim
-
-def gc():
-    gc_collect()
-    if thread_data.device == 'cpu':
-        return
-    torch.cuda.empty_cache()
-    torch.cuda.ipc_collect()
-
-# internal
-
-def chunk(it, size):
-    it = iter(it)
-    return iter(lambda: tuple(islice(it, size)), ())
-
-def load_model_from_config(ckpt, verbose=False):
-    print(f"Loading model from {ckpt}")
-    model_ver = 'sd1'
-
-    if ckpt.endswith(".safetensors"):
-        print("Loading from safetensors")
-        pl_sd = load_file(ckpt, device="cpu")
-    else:
-        pl_sd = torch.load(ckpt, map_location="cpu")
-
-    if "global_step" in pl_sd:
-        print(f"Global Step: {pl_sd['global_step']}")
-
-    if "state_dict" in pl_sd:
-        # check for a key that only seems to be present in SD2 models
-        if 'cond_stage_model.model.ln_final.bias' in pl_sd['state_dict'].keys():
-            model_ver = 'sd2'
-
-        return pl_sd["state_dict"], model_ver
-    else:
-        return pl_sd, model_ver
-
-class UserInitiatedStop(Exception):
-    pass
-
-def load_img(img_str, w0, h0):
-    image = base64_str_to_img(img_str).convert("RGB")
-    w, h = image.size
-    print(f"loaded input image of size ({w}, {h}) from base64")
-    if h0 is not None and w0 is not None:
-        h, w = h0, w0
-
-    w, h = map(lambda x: x - x % 64, (w, h))  # resize to integer multiple of 64
-    image = image.resize((w, h), resample=Image.Resampling.LANCZOS)
-    image = np.array(image).astype(np.float32) / 255.0
-    image = image[None].transpose(0, 3, 1, 2)
-    image = torch.from_numpy(image)
-    return 2.*image - 1.
-
-def load_mask(mask_str, h0, w0, newH, newW, invert=False):
-    image = base64_str_to_img(mask_str).convert("RGB")
-    w, h = image.size
-    print(f"loaded input mask of size ({w}, {h})")
-
-    if invert:
-        print("inverted")
-        image = ImageOps.invert(image)
-        # where_0, where_1 = np.where(image == 0), np.where(image == 255)
-        # image[where_0], image[where_1] = 255, 0
-
-    if h0 is not None and w0 is not None:
-        h, w = h0, w0
-
-    w, h = map(lambda x: x - x % 64, (w, h))  # resize to integer multiple of 64
-
-    print(f"New mask size ({w}, {h})")
-    image = image.resize((newW, newH), resample=Image.Resampling.LANCZOS)
-    image = np.array(image)
-
-    image = image.astype(np.float32) / 255.0
-    image = image[None].transpose(0, 3, 1, 2)
-    image = torch.from_numpy(image)
-    return image
-
-# https://stackoverflow.com/a/61114178
-def img_to_base64_str(img, output_format="PNG", output_quality=75):
-    buffered = img_to_buffer(img, output_format, quality=output_quality)
-    return buffer_to_base64_str(buffered, output_format)
-
-def img_to_buffer(img, output_format="PNG", output_quality=75):
-    buffered = BytesIO()
-    if ( output_format.upper() == "JPEG" ):
-        img.save(buffered, format=output_format, quality=output_quality)
-    else:
-        img.save(buffered, format=output_format)
-    buffered.seek(0)
-    return buffered
-
-def buffer_to_base64_str(buffered, output_format="PNG"):
-    buffered.seek(0)
-    img_byte = buffered.getvalue()
-    mime_type = "image/png" if output_format.lower() == "png" else "image/jpeg"
-    img_str = f"data:{mime_type};base64," + base64.b64encode(img_byte).decode()
-    return img_str
-
-def base64_str_to_buffer(img_str):
-    mime_type = "image/png" if img_str.startswith("data:image/png;") else "image/jpeg"
-    img_str = img_str[len(f"data:{mime_type};base64,"):]
-    data = base64.b64decode(img_str)
-    buffered = BytesIO(data)
-    return buffered
-
-def base64_str_to_img(img_str):
-    buffered = base64_str_to_buffer(img_str)
-    img = Image.open(buffered)
-    return img
-
-def split_weighted_subprompts(text):
-    """
-    grabs all text up to the first occurrence of ':' 
-    uses the grabbed text as a sub-prompt, and takes the value following ':' as weight
-    if ':' has no value defined, defaults to 1.0
-    repeats until no text remaining
-    """
-    remaining = len(text)
-    prompts = []
-    weights = []
-    while remaining > 0:
-        if ":" in text:
-            idx = text.index(":") # first occurrence from start
-            # grab up to index as sub-prompt
-            prompt = text[:idx]
-            remaining -= idx
-            # remove from main text
-            text = text[idx+1:]
-            # find value for weight 
-            if " " in text:
-                idx = text.index(" ") # first occurence
-            else: # no space, read to end
-                idx = len(text)
-            if idx != 0:
-                try:
-                    weight = float(text[:idx])
-                except: # couldn't treat as float
-                    print(f"Warning: '{text[:idx]}' is not a value, are you missing a space?")
-                    weight = 1.0
-            else: # no value found
-                weight = 1.0
-            # remove from main text
-            remaining -= idx
-            text = text[idx+1:]
-            # append the sub-prompt and its weight
-            prompts.append(prompt)
-            weights.append(weight)
-        else: # no : found
-            if len(text) > 0: # there is still text though
-                # take remainder as weight 1
-                prompts.append(text)
-                weights.append(1.0)
-            remaining = 0
-    return prompts, weights
diff --git a/ui/sd_internal/save_utils.py b/ui/sd_internal/save_utils.py
index 29c4a29c..db9d0671 100644
--- a/ui/sd_internal/save_utils.py
+++ b/ui/sd_internal/save_utils.py
@@ -3,8 +3,8 @@ import time
 import base64
 import re
 
-from diffusionkit import data_utils
-from diffusionkit.types import GenerateImageRequest
+from sdkit.utils import save_images, save_dicts
+from sdkit.types import GenerateImageRequest
 
 from sd_internal import TaskData
 
@@ -33,12 +33,12 @@ def save_to_disk(images: list, filtered_images: list, req: GenerateImageRequest,
     metadata_entries = get_metadata_entries(req, task_data)
 
     if task_data.show_only_filtered_image or filtered_images == images:
-        data_utils.save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
-        data_utils.save_metadata(metadata_entries, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.metadata_output_format)
+        save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        save_dicts(metadata_entries, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.metadata_output_format)
     else:
-        data_utils.save_images(images, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
-        data_utils.save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.output_format, output_quality=task_data.output_quality)
-        data_utils.save_metadata(metadata_entries, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.metadata_output_format)
+        save_images(images, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        save_dicts(metadata_entries, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.metadata_output_format)
 
 def get_metadata_entries(req: GenerateImageRequest, task_data: TaskData):
     metadata = get_printable_request(req)
diff --git a/ui/sd_internal/task_manager.py b/ui/sd_internal/task_manager.py
index 094d853c..f9080a74 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/sd_internal/task_manager.py
@@ -15,7 +15,7 @@ import queue, threading, time, weakref
 from typing import Any, Hashable
 
 from sd_internal import TaskData, device_manager
-from diffusionkit.types import GenerateImageRequest
+from sdkit.types import GenerateImageRequest
 
 log = logging.getLogger()
 
diff --git a/ui/server.py b/ui/server.py
index 284fed1b..43a11347 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -15,7 +15,7 @@ from pydantic import BaseModel
 
 from sd_internal import app, model_manager, task_manager
 from sd_internal import TaskData
-from diffusionkit.types import GenerateImageRequest
+from sdkit.types import GenerateImageRequest
 
 log = logging.getLogger()
 

From 47e3884994aeca791c0421c47ab5d02ddc5d450f Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Mon, 19 Dec 2022 19:39:15 +0530
Subject: [PATCH 53/74] Rename the python package name to easydiffusion (from
 sd_internal)

---
 ui/easydiffusion/__init__.py                  |  0
 ui/{sd_internal => easydiffusion}/app.py      |  5 ++--
 .../device_manager.py                         |  3 +--
 .../model_manager.py                          |  8 +++----
 ui/{sd_internal => easydiffusion}/renderer.py | 23 +++++++++----------
 .../task_manager.py                           | 12 +++++-----
 .../__init__.py => easydiffusion/types.py}    |  0
 ui/easydiffusion/utils/__init__.py            |  8 +++++++
 .../utils}/save_utils.py                      | 10 ++++----
 ui/server.py                                  |  8 +++----
 10 files changed, 40 insertions(+), 37 deletions(-)
 create mode 100644 ui/easydiffusion/__init__.py
 rename ui/{sd_internal => easydiffusion}/app.py (98%)
 rename ui/{sd_internal => easydiffusion}/device_manager.py (99%)
 rename ui/{sd_internal => easydiffusion}/model_manager.py (98%)
 rename ui/{sd_internal => easydiffusion}/renderer.py (84%)
 rename ui/{sd_internal => easydiffusion}/task_manager.py (98%)
 rename ui/{sd_internal/__init__.py => easydiffusion/types.py} (100%)
 create mode 100644 ui/easydiffusion/utils/__init__.py
 rename ui/{sd_internal => easydiffusion/utils}/save_utils.py (91%)

diff --git a/ui/easydiffusion/__init__.py b/ui/easydiffusion/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/ui/sd_internal/app.py b/ui/easydiffusion/app.py
similarity index 98%
rename from ui/sd_internal/app.py
rename to ui/easydiffusion/app.py
index 471ee074..c0af06a3 100644
--- a/ui/sd_internal/app.py
+++ b/ui/easydiffusion/app.py
@@ -6,7 +6,8 @@ import traceback
 import logging
 from rich.logging import RichHandler
 
-from sd_internal import task_manager
+from easydiffusion import task_manager
+from easydiffusion.utils import log
 
 LOG_FORMAT = '%(asctime)s.%(msecs)03d %(levelname)s %(threadName)s %(message)s'
 logging.basicConfig(
@@ -16,8 +17,6 @@ logging.basicConfig(
         handlers=[RichHandler(markup=True, rich_tracebacks=True, show_time=False, show_level=False)]
 )
 
-log = logging.getLogger()
-
 SD_DIR = os.getcwd()
 
 SD_UI_DIR = os.getenv('SD_UI_PATH', None)
diff --git a/ui/sd_internal/device_manager.py b/ui/easydiffusion/device_manager.py
similarity index 99%
rename from ui/sd_internal/device_manager.py
rename to ui/easydiffusion/device_manager.py
index 56508fad..0f2ab850 100644
--- a/ui/sd_internal/device_manager.py
+++ b/ui/easydiffusion/device_manager.py
@@ -2,9 +2,8 @@ import os
 import torch
 import traceback
 import re
-import logging
 
-log = logging.getLogger()
+from easydiffusion.utils import log
 
 '''
 Set `FORCE_FULL_PRECISION` in the environment variables, or in `config.bat`/`config.sh` to set full precision (i.e. float32).
diff --git a/ui/sd_internal/model_manager.py b/ui/easydiffusion/model_manager.py
similarity index 98%
rename from ui/sd_internal/model_manager.py
rename to ui/easydiffusion/model_manager.py
index ec72e6fa..eb8aa7fd 100644
--- a/ui/sd_internal/model_manager.py
+++ b/ui/easydiffusion/model_manager.py
@@ -1,13 +1,13 @@
 import os
-import logging
 import picklescan.scanner
 
-from sd_internal import app, TaskData, device_manager
+from easydiffusion import app, device_manager
+from easydiffusion.types import TaskData
+from easydiffusion.utils import log
+
 from sdkit.models import model_loader
 from sdkit.types import Context
 
-log = logging.getLogger()
-
 KNOWN_MODEL_TYPES = ['stable-diffusion', 'vae', 'hypernetwork', 'gfpgan', 'realesrgan']
 MODEL_EXTENSIONS = {
     'stable-diffusion': ['.ckpt', '.safetensors'],
diff --git a/ui/sd_internal/renderer.py b/ui/easydiffusion/renderer.py
similarity index 84%
rename from ui/sd_internal/renderer.py
rename to ui/easydiffusion/renderer.py
index 1d289c99..610e14fa 100644
--- a/ui/sd_internal/renderer.py
+++ b/ui/easydiffusion/renderer.py
@@ -1,16 +1,15 @@
 import queue
 import time
 import json
-import logging
 
-from sd_internal import device_manager, save_utils
-from sd_internal import TaskData, Response, Image as ResponseImage, UserInitiatedStop
+from easydiffusion import device_manager
+from easydiffusion.types import TaskData, Response, Image as ResponseImage, UserInitiatedStop
+from easydiffusion.utils import get_printable_request, save_images_to_disk, log
 
-from sdkit import model_loader, image_generator, image_utils, filters as image_filters
+from sdkit import model_loader, image_generator, filters as image_filters
+from sdkit.utils import img_to_buffer, img_to_base64_str, latent_samples_to_images
 from sdkit.types import Context, GenerateImageRequest, FilterImageRequest
 
-log = logging.getLogger()
-
 context = Context() # thread-local
 '''
 runtime data (bound locally to this thread), for e.g. device, references to loaded models, optimization flags etc
@@ -28,7 +27,7 @@ def init(device):
 
 def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
     context.stop_processing = False
-    log.info(f'request: {save_utils.get_printable_request(req)}')
+    log.info(f'request: {get_printable_request(req)}')
     log.info(f'task data: {task_data.dict()}')
 
     images = _make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
@@ -45,7 +44,7 @@ def _make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_q
     filtered_images = apply_filters(task_data, images, user_stopped)
 
     if task_data.save_to_disk_path is not None:
-        save_utils.save_to_disk(images, filtered_images, req, task_data)
+        save_images_to_disk(images, filtered_images, req, task_data)
 
     return filtered_images if task_data.show_only_filtered_image else images + filtered_images
 
@@ -61,7 +60,7 @@ def generate_images(req: GenerateImageRequest, task_data: TaskData, data_queue:
         images = []
         user_stopped = True
         if context.partial_x_samples is not None:
-            images = image_utils.latent_samples_to_images(context, context.partial_x_samples)
+            images = latent_samples_to_images(context, context.partial_x_samples)
             context.partial_x_samples = None
     finally:
         model_loader.gc(context)
@@ -89,7 +88,7 @@ def apply_filters(task_data: TaskData, images: list, user_stopped):
 def construct_response(images: list, task_data: TaskData, base_seed: int):
     return [
         ResponseImage(
-            data=image_utils.img_to_base64_str(img, task_data.output_format, task_data.output_quality),
+            data=img_to_base64_str(img, task_data.output_format, task_data.output_quality),
             seed=base_seed + i
         ) for i, img in enumerate(images)
     ]
@@ -100,9 +99,9 @@ def make_step_callback(req: GenerateImageRequest, task_data: TaskData, data_queu
 
     def update_temp_img(x_samples, task_temp_images: list):
         partial_images = []
-        images = image_utils.latent_samples_to_images(context, x_samples)
+        images = latent_samples_to_images(context, x_samples)
         for i, img in enumerate(images):
-            buf = image_utils.img_to_buffer(img, output_format='JPEG')
+            buf = img_to_buffer(img, output_format='JPEG')
 
             context.temp_images[f"{task_data.request_id}/{i}"] = buf
             task_temp_images[i] = buf
diff --git a/ui/sd_internal/task_manager.py b/ui/easydiffusion/task_manager.py
similarity index 98%
rename from ui/sd_internal/task_manager.py
rename to ui/easydiffusion/task_manager.py
index f9080a74..19638715 100644
--- a/ui/sd_internal/task_manager.py
+++ b/ui/easydiffusion/task_manager.py
@@ -6,7 +6,6 @@ Notes:
 """
 import json
 import traceback
-import logging
 
 TASK_TTL = 15 * 60 # seconds, Discard last session's task timeout
 
@@ -14,10 +13,11 @@ import torch
 import queue, threading, time, weakref
 from typing import Any, Hashable
 
-from sd_internal import TaskData, device_manager
-from sdkit.types import GenerateImageRequest
+from easydiffusion import device_manager
+from easydiffusion.types import TaskData
+from easydiffusion.utils import log
 
-log = logging.getLogger()
+from sdkit.types import GenerateImageRequest
 
 THREAD_NAME_PREFIX = ''
 ERR_LOCK_FAILED = ' failed to acquire lock within timeout.'
@@ -186,7 +186,7 @@ class SessionState():
         return True
 
 def thread_get_next_task():
-    from sd_internal import renderer
+    from easydiffusion import renderer
     if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
         log.warn(f'Render thread on device: {renderer.context.device} failed to acquire manager lock.')
         return None
@@ -219,7 +219,7 @@ def thread_get_next_task():
 def thread_render(device):
     global current_state, current_state_error
 
-    from sd_internal import renderer, model_manager
+    from easydiffusion import renderer, model_manager
     try:
         renderer.init(device)
 
diff --git a/ui/sd_internal/__init__.py b/ui/easydiffusion/types.py
similarity index 100%
rename from ui/sd_internal/__init__.py
rename to ui/easydiffusion/types.py
diff --git a/ui/easydiffusion/utils/__init__.py b/ui/easydiffusion/utils/__init__.py
new file mode 100644
index 00000000..8be070b4
--- /dev/null
+++ b/ui/easydiffusion/utils/__init__.py
@@ -0,0 +1,8 @@
+import logging
+
+log = logging.getLogger('easydiffusion')
+
+from .save_utils import (
+    save_images_to_disk,
+    get_printable_request,
+)
\ No newline at end of file
diff --git a/ui/sd_internal/save_utils.py b/ui/easydiffusion/utils/save_utils.py
similarity index 91%
rename from ui/sd_internal/save_utils.py
rename to ui/easydiffusion/utils/save_utils.py
index db9d0671..bb1d09c9 100644
--- a/ui/sd_internal/save_utils.py
+++ b/ui/easydiffusion/utils/save_utils.py
@@ -3,11 +3,11 @@ import time
 import base64
 import re
 
+from easydiffusion.types import TaskData
+
 from sdkit.utils import save_images, save_dicts
 from sdkit.types import GenerateImageRequest
 
-from sd_internal import TaskData
-
 filename_regex = re.compile('[^a-zA-Z0-9]')
 
 # keep in sync with `ui/media/js/dnd.js`
@@ -28,9 +28,9 @@ TASK_TEXT_MAPPING = {
     'hypernetwork_strength': 'Hypernetwork Strength'
 }
 
-def save_to_disk(images: list, filtered_images: list, req: GenerateImageRequest, task_data: TaskData):
+def save_images_to_disk(images: list, filtered_images: list, req: GenerateImageRequest, task_data: TaskData):
     save_folder_path = os.path.join(task_data.save_to_disk_path, filename_regex.sub('_', task_data.session_id))
-    metadata_entries = get_metadata_entries(req, task_data)
+    metadata_entries = get_metadata_entries_for_request(req, task_data)
 
     if task_data.show_only_filtered_image or filtered_images == images:
         save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
@@ -40,7 +40,7 @@ def save_to_disk(images: list, filtered_images: list, req: GenerateImageRequest,
         save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.output_format, output_quality=task_data.output_quality)
         save_dicts(metadata_entries, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.metadata_output_format)
 
-def get_metadata_entries(req: GenerateImageRequest, task_data: TaskData):
+def get_metadata_entries_for_request(req: GenerateImageRequest, task_data: TaskData):
     metadata = get_printable_request(req)
     metadata.update({
         'use_stable_diffusion_model': task_data.use_stable_diffusion_model,
diff --git a/ui/server.py b/ui/server.py
index 43a11347..8ee34fec 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -4,7 +4,6 @@ Notes:
 """
 import os
 import traceback
-import logging
 import datetime
 from typing import List, Union
 
@@ -13,12 +12,11 @@ from fastapi.staticfiles import StaticFiles
 from starlette.responses import FileResponse, JSONResponse, StreamingResponse
 from pydantic import BaseModel
 
-from sd_internal import app, model_manager, task_manager
-from sd_internal import TaskData
+from easydiffusion import app, model_manager, task_manager
+from easydiffusion.types import TaskData
+from easydiffusion.utils import log
 from sdkit.types import GenerateImageRequest
 
-log = logging.getLogger()
-
 log.info(f'started in {app.SD_DIR}')
 log.info(f'started at {datetime.datetime.now():%x %X}')
 

From 5eeef41d8cabcdc485e8a1095198c07f7ac92632 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Tue, 20 Dec 2022 15:16:47 +0530
Subject: [PATCH 54/74] Update to use the latest sdkit API

---
 ui/easydiffusion/model_manager.py    | 18 ++++++------
 ui/easydiffusion/renderer.py         | 43 ++++++++++++----------------
 ui/easydiffusion/task_manager.py     |  4 +--
 ui/easydiffusion/types.py            | 21 +++++++++++++-
 ui/easydiffusion/utils/save_utils.py |  3 +-
 ui/server.py                         |  3 +-
 6 files changed, 50 insertions(+), 42 deletions(-)

diff --git a/ui/easydiffusion/model_manager.py b/ui/easydiffusion/model_manager.py
index eb8aa7fd..4c9fb1d1 100644
--- a/ui/easydiffusion/model_manager.py
+++ b/ui/easydiffusion/model_manager.py
@@ -5,14 +5,14 @@ from easydiffusion import app, device_manager
 from easydiffusion.types import TaskData
 from easydiffusion.utils import log
 
-from sdkit.models import model_loader
-from sdkit.types import Context
+from sdkit import Context
+from sdkit.models import load_model, unload_model
 
 KNOWN_MODEL_TYPES = ['stable-diffusion', 'vae', 'hypernetwork', 'gfpgan', 'realesrgan']
 MODEL_EXTENSIONS = {
     'stable-diffusion': ['.ckpt', '.safetensors'],
-    'vae': ['.vae.pt', '.ckpt'],
-    'hypernetwork': ['.pt'],
+    'vae': ['.vae.pt', '.ckpt', '.safetensors'],
+    'hypernetwork': ['.pt', '.safetensors'],
     'gfpgan': ['.pth'],
     'realesrgan': ['.pth'],
 }
@@ -44,13 +44,13 @@ def load_default_models(context: Context):
     set_vram_optimizations(context)
 
     # load mandatory models
-    model_loader.load_model(context, 'stable-diffusion')
-    model_loader.load_model(context, 'vae')
-    model_loader.load_model(context, 'hypernetwork')
+    load_model(context, 'stable-diffusion')
+    load_model(context, 'vae')
+    load_model(context, 'hypernetwork')
 
 def unload_all(context: Context):
     for model_type in KNOWN_MODEL_TYPES:
-        model_loader.unload_model(context, model_type)
+        unload_model(context, model_type)
 
 def resolve_model_to_use(model_name:str=None, model_type:str=None):
     model_extensions = MODEL_EXTENSIONS.get(model_type, [])
@@ -107,7 +107,7 @@ def reload_models_if_necessary(context: Context, task_data: TaskData):
     for model_type, model_path_in_req in models_to_reload.items():
         context.model_paths[model_type] = model_path_in_req
 
-        action_fn = model_loader.unload_model if context.model_paths[model_type] is None else model_loader.load_model
+        action_fn = unload_model if context.model_paths[model_type] is None else load_model
         action_fn(context, model_type)
 
 def resolve_model_paths(task_data: TaskData):
diff --git a/ui/easydiffusion/renderer.py b/ui/easydiffusion/renderer.py
index 610e14fa..4b9847c0 100644
--- a/ui/easydiffusion/renderer.py
+++ b/ui/easydiffusion/renderer.py
@@ -3,12 +3,13 @@ import time
 import json
 
 from easydiffusion import device_manager
-from easydiffusion.types import TaskData, Response, Image as ResponseImage, UserInitiatedStop
+from easydiffusion.types import TaskData, Response, Image as ResponseImage, UserInitiatedStop, GenerateImageRequest
 from easydiffusion.utils import get_printable_request, save_images_to_disk, log
 
-from sdkit import model_loader, image_generator, filters as image_filters
-from sdkit.utils import img_to_buffer, img_to_base64_str, latent_samples_to_images
-from sdkit.types import Context, GenerateImageRequest, FilterImageRequest
+from sdkit import Context
+from sdkit.generate import generate_images
+from sdkit.filter import apply_filters
+from sdkit.utils import img_to_buffer, img_to_base64_str, latent_samples_to_images, gc
 
 context = Context() # thread-local
 '''
@@ -30,7 +31,7 @@ def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queu
     log.info(f'request: {get_printable_request(req)}')
     log.info(f'task data: {task_data.dict()}')
 
-    images = _make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
+    images = make_images_internal(req, task_data, data_queue, task_temp_images, step_callback)
 
     res = Response(req, task_data, images=construct_response(images, task_data, base_seed=req.seed))
     res = res.json()
@@ -39,22 +40,22 @@ def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queu
 
     return res
 
-def _make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
-    images, user_stopped = generate_images(req, task_data, data_queue, task_temp_images, step_callback, task_data.stream_image_progress)
-    filtered_images = apply_filters(task_data, images, user_stopped)
+def make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
+    images, user_stopped = generate_images_internal(req, task_data, data_queue, task_temp_images, step_callback, task_data.stream_image_progress)
+    filtered_images = filter_images(task_data, images, user_stopped)
 
     if task_data.save_to_disk_path is not None:
         save_images_to_disk(images, filtered_images, req, task_data)
 
     return filtered_images if task_data.show_only_filtered_image else images + filtered_images
 
-def generate_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
+def generate_images_internal(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
     context.temp_images.clear()
 
-    image_generator.on_image_step = make_step_callback(req, task_data, data_queue, task_temp_images, step_callback, stream_image_progress)
+    callback = make_step_callback(req, task_data, data_queue, task_temp_images, step_callback, stream_image_progress)
 
     try:
-        images = image_generator.make_images(context=context, req=req)
+        images = generate_images(context, callback=callback, **req.dict())
         user_stopped = False
     except UserInitiatedStop:
         images = []
@@ -63,27 +64,19 @@ def generate_images(req: GenerateImageRequest, task_data: TaskData, data_queue:
             images = latent_samples_to_images(context, context.partial_x_samples)
             context.partial_x_samples = None
     finally:
-        model_loader.gc(context)
+        gc(context)
 
     return images, user_stopped
 
-def apply_filters(task_data: TaskData, images: list, user_stopped):
+def filter_images(task_data: TaskData, images: list, user_stopped):
     if user_stopped or (task_data.use_face_correction is None and task_data.use_upscale is None):
         return images
 
-    filters = []
-    if 'gfpgan' in task_data.use_face_correction.lower(): filters.append('gfpgan')
-    if 'realesrgan' in task_data.use_face_correction.lower(): filters.append('realesrgan')
+    filters_to_apply = []
+    if 'gfpgan' in task_data.use_face_correction.lower(): filters_to_apply.append('gfpgan')
+    if 'realesrgan' in task_data.use_face_correction.lower(): filters_to_apply.append('realesrgan')
 
-    filtered_images = []
-    for img in images:
-        filter_req = FilterImageRequest()
-        filter_req.init_image = img
-
-        filtered_image = image_filters.apply(context, filters, filter_req)
-        filtered_images.append(filtered_image)
-
-    return filtered_images
+    return apply_filters(context, filters_to_apply, images)
 
 def construct_response(images: list, task_data: TaskData, base_seed: int):
     return [
diff --git a/ui/easydiffusion/task_manager.py b/ui/easydiffusion/task_manager.py
index 19638715..3a764137 100644
--- a/ui/easydiffusion/task_manager.py
+++ b/ui/easydiffusion/task_manager.py
@@ -14,11 +14,9 @@ import queue, threading, time, weakref
 from typing import Any, Hashable
 
 from easydiffusion import device_manager
-from easydiffusion.types import TaskData
+from easydiffusion.types import TaskData, GenerateImageRequest
 from easydiffusion.utils import log
 
-from sdkit.types import GenerateImageRequest
-
 THREAD_NAME_PREFIX = ''
 ERR_LOCK_FAILED = ' failed to acquire lock within timeout.'
 LOCK_TIMEOUT = 15 # Maximum locking time in seconds before failing a task.
diff --git a/ui/easydiffusion/types.py b/ui/easydiffusion/types.py
index 3a748431..2a10d521 100644
--- a/ui/easydiffusion/types.py
+++ b/ui/easydiffusion/types.py
@@ -1,6 +1,25 @@
 from pydantic import BaseModel
+from typing import Any
 
-from sdkit.types import GenerateImageRequest
+class GenerateImageRequest(BaseModel):
+    prompt: str = ""
+    negative_prompt: str = ""
+
+    seed: int = 42
+    width: int = 512
+    height: int = 512
+
+    num_outputs: int = 1
+    num_inference_steps: int = 50
+    guidance_scale: float = 7.5
+
+    init_image: Any = None
+    init_image_mask: Any = None
+    prompt_strength: float = 0.8
+    preserve_init_image_color_profile = False
+
+    sampler_name: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
+    hypernetwork_strength: float = 0
 
 class TaskData(BaseModel):
     request_id: str = None
diff --git a/ui/easydiffusion/utils/save_utils.py b/ui/easydiffusion/utils/save_utils.py
index bb1d09c9..d7fa82a3 100644
--- a/ui/easydiffusion/utils/save_utils.py
+++ b/ui/easydiffusion/utils/save_utils.py
@@ -3,10 +3,9 @@ import time
 import base64
 import re
 
-from easydiffusion.types import TaskData
+from easydiffusion.types import TaskData, GenerateImageRequest
 
 from sdkit.utils import save_images, save_dicts
-from sdkit.types import GenerateImageRequest
 
 filename_regex = re.compile('[^a-zA-Z0-9]')
 
diff --git a/ui/server.py b/ui/server.py
index 8ee34fec..8d9a129e 100644
--- a/ui/server.py
+++ b/ui/server.py
@@ -13,9 +13,8 @@ from starlette.responses import FileResponse, JSONResponse, StreamingResponse
 from pydantic import BaseModel
 
 from easydiffusion import app, model_manager, task_manager
-from easydiffusion.types import TaskData
+from easydiffusion.types import TaskData, GenerateImageRequest
 from easydiffusion.utils import log
-from sdkit.types import GenerateImageRequest
 
 log.info(f'started in {app.SD_DIR}')
 log.info(f'started at {datetime.datetime.now():%x %X}')

From c804a9971ea5d8d00747ccb3d84ad712ad642ce3 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Thu, 22 Dec 2022 11:54:00 +0530
Subject: [PATCH 55/74] Work-in-progress code for adding a model config
 dropdown in the UI. Doesn't work yet

---
 ui/easydiffusion/model_manager.py    |  7 ++++++-
 ui/easydiffusion/types.py            |  1 +
 ui/easydiffusion/utils/save_utils.py | 12 ++++++------
 ui/index.html                        |  4 ++++
 4 files changed, 17 insertions(+), 7 deletions(-)

diff --git a/ui/easydiffusion/model_manager.py b/ui/easydiffusion/model_manager.py
index 4c9fb1d1..7bc2b3af 100644
--- a/ui/easydiffusion/model_manager.py
+++ b/ui/easydiffusion/model_manager.py
@@ -6,7 +6,8 @@ from easydiffusion.types import TaskData
 from easydiffusion.utils import log
 
 from sdkit import Context
-from sdkit.models import load_model, unload_model
+from sdkit.models import load_model, unload_model, get_known_model_info
+from sdkit.utils import hash_file_quick
 
 KNOWN_MODEL_TYPES = ['stable-diffusion', 'vae', 'hypernetwork', 'gfpgan', 'realesrgan']
 MODEL_EXTENSIONS = {
@@ -104,6 +105,10 @@ def reload_models_if_necessary(context: Context, task_data: TaskData):
     if set_vram_optimizations(context): # reload SD
         models_to_reload['stable-diffusion'] = model_paths_in_req['stable-diffusion']
 
+    if 'stable-diffusion' in models_to_reload:
+        quick_hash = hash_file_quick(models_to_reload['stable-diffusion'])
+        known_model_info = get_known_model_info(quick_hash=quick_hash)
+
     for model_type, model_path_in_req in models_to_reload.items():
         context.model_paths[model_type] = model_path_in_req
 
diff --git a/ui/easydiffusion/types.py b/ui/easydiffusion/types.py
index 2a10d521..805c8683 100644
--- a/ui/easydiffusion/types.py
+++ b/ui/easydiffusion/types.py
@@ -30,6 +30,7 @@ class TaskData(BaseModel):
     use_face_correction: str = None # or "GFPGANv1.3"
     use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
     use_stable_diffusion_model: str = "sd-v1-4"
+    use_stable_diffusion_config: str = "v1-inference"
     use_vae_model: str = None
     use_hypernetwork_model: str = None
 
diff --git a/ui/easydiffusion/utils/save_utils.py b/ui/easydiffusion/utils/save_utils.py
index d7fa82a3..b9ce8aba 100644
--- a/ui/easydiffusion/utils/save_utils.py
+++ b/ui/easydiffusion/utils/save_utils.py
@@ -28,16 +28,16 @@ TASK_TEXT_MAPPING = {
 }
 
 def save_images_to_disk(images: list, filtered_images: list, req: GenerateImageRequest, task_data: TaskData):
-    save_folder_path = os.path.join(task_data.save_to_disk_path, filename_regex.sub('_', task_data.session_id))
+    save_dir_path = os.path.join(task_data.save_to_disk_path, filename_regex.sub('_', task_data.session_id))
     metadata_entries = get_metadata_entries_for_request(req, task_data)
 
     if task_data.show_only_filtered_image or filtered_images == images:
-        save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
-        save_dicts(metadata_entries, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.metadata_output_format)
+        save_images(filtered_images, save_dir_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        save_dicts(metadata_entries, save_dir_path, file_name=make_filename_callback(req), output_format=task_data.metadata_output_format)
     else:
-        save_images(images, save_folder_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
-        save_images(filtered_images, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.output_format, output_quality=task_data.output_quality)
-        save_dicts(metadata_entries, save_folder_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.metadata_output_format)
+        save_images(images, save_dir_path, file_name=make_filename_callback(req), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        save_images(filtered_images, save_dir_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.output_format, output_quality=task_data.output_quality)
+        save_dicts(metadata_entries, save_dir_path, file_name=make_filename_callback(req, suffix='filtered'), output_format=task_data.metadata_output_format)
 
 def get_metadata_entries_for_request(req: GenerateImageRequest, task_data: TaskData):
     metadata = get_printable_request(req)
diff --git a/ui/index.html b/ui/index.html
index 9f36033f..5d12d419 100644
--- a/ui/index.html
+++ b/ui/index.html
@@ -125,6 +125,10 @@
                         </select>
                         <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Custom-Models" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about custom models</span></i></a>
                     </td></tr>
+                    <tr id="modelConfigSelection" class="pl-5"><td><label for="model_config">Model Config:</i></label></td><td>
+                        <select id="model_config" name="model_config">
+                        </select>
+                    </td></tr>
                     <tr class="pl-5"><td><label for="vae_model">Custom VAE:</i></label></td><td>
                         <select id="vae_model" name="vae_model">
                             <!-- <option value="" selected>None</option> -->

From d8b79d8b5c71e27541fbf1a72bb53fbec3afb6df Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Thu, 22 Dec 2022 15:43:25 +0530
Subject: [PATCH 56/74] Don't crash if IP listing fails. Thanks @JeLuf

---
 ui/easydiffusion/app.py | 10 +++++++---
 1 file changed, 7 insertions(+), 3 deletions(-)

diff --git a/ui/easydiffusion/app.py b/ui/easydiffusion/app.py
index c0af06a3..7f2dd12d 100644
--- a/ui/easydiffusion/app.py
+++ b/ui/easydiffusion/app.py
@@ -142,9 +142,13 @@ def getUIPlugins():
     return plugins
 
 def getIPConfig():
-    ips = socket.gethostbyname_ex(socket.gethostname())
-    ips[2].append(ips[0])
-    return ips[2]
+    try:
+        ips = socket.gethostbyname_ex(socket.gethostname())
+        ips[2].append(ips[0])
+        return ips[2]
+    except Exception as e:
+        log.exception(e)
+        return []
 
 def open_browser():
     config = getConfig()

From d8543d1358e4316544b57ea351c2833d6a9aa0f5 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Thu, 22 Dec 2022 16:47:59 +0530
Subject: [PATCH 57/74] Use the sdkit model scan; Disable scan-per-load since
 we scan them before allowing them to be invoked

---
 ui/easydiffusion/model_manager.py | 9 ++++-----
 1 file changed, 4 insertions(+), 5 deletions(-)

diff --git a/ui/easydiffusion/model_manager.py b/ui/easydiffusion/model_manager.py
index 7bc2b3af..367312ca 100644
--- a/ui/easydiffusion/model_manager.py
+++ b/ui/easydiffusion/model_manager.py
@@ -1,12 +1,11 @@
 import os
-import picklescan.scanner
 
 from easydiffusion import app, device_manager
 from easydiffusion.types import TaskData
 from easydiffusion.utils import log
 
 from sdkit import Context
-from sdkit.models import load_model, unload_model, get_known_model_info
+from sdkit.models import load_model, unload_model, get_known_model_info, scan_model
 from sdkit.utils import hash_file_quick
 
 KNOWN_MODEL_TYPES = ['stable-diffusion', 'vae', 'hypernetwork', 'gfpgan', 'realesrgan']
@@ -45,7 +44,7 @@ def load_default_models(context: Context):
     set_vram_optimizations(context)
 
     # load mandatory models
-    load_model(context, 'stable-diffusion')
+    load_model(context, 'stable-diffusion', scan_model=False) # we've scanned them already
     load_model(context, 'vae')
     load_model(context, 'hypernetwork')
 
@@ -113,7 +112,7 @@ def reload_models_if_necessary(context: Context, task_data: TaskData):
         context.model_paths[model_type] = model_path_in_req
 
         action_fn = unload_model if context.model_paths[model_type] is None else load_model
-        action_fn(context, model_type)
+        action_fn(context, model_type, scan_model=False) # we've scanned them already
 
 def resolve_model_paths(task_data: TaskData):
     task_data.use_stable_diffusion_model = resolve_model_to_use(task_data.use_stable_diffusion_model, model_type='stable-diffusion')
@@ -157,7 +156,7 @@ def make_model_folders():
 
 def is_malicious_model(file_path):
     try:
-        scan_result = picklescan.scanner.scan_file_path(file_path)
+        scan_result = scan_model(file_path)
         if scan_result.issues_count > 0 or scan_result.infected_files > 0:
             log.warn(":warning: [bold red]Scan %s: %d scanned, %d issue, %d infected.[/bold red]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files))
             return True

From 107112d1c485fdaaed048c55859d5001c574ca0e Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 12:37:20 +0530
Subject: [PATCH 58/74] Integration bugs

---
 ui/easydiffusion/model_manager.py | 19 ++++++++-----------
 ui/easydiffusion/renderer.py      |  4 ++--
 2 files changed, 10 insertions(+), 13 deletions(-)

diff --git a/ui/easydiffusion/model_manager.py b/ui/easydiffusion/model_manager.py
index 367312ca..e08328fe 100644
--- a/ui/easydiffusion/model_manager.py
+++ b/ui/easydiffusion/model_manager.py
@@ -5,7 +5,7 @@ from easydiffusion.types import TaskData
 from easydiffusion.utils import log
 
 from sdkit import Context
-from sdkit.models import load_model, unload_model, get_known_model_info, scan_model
+from sdkit.models import load_model, unload_model, get_model_info_from_db, scan_model
 from sdkit.utils import hash_file_quick
 
 KNOWN_MODEL_TYPES = ['stable-diffusion', 'vae', 'hypernetwork', 'gfpgan', 'realesrgan']
@@ -29,6 +29,7 @@ VRAM_USAGE_LEVEL_TO_OPTIMIZATIONS = {
     'low': {'KEEP_ENTIRE_MODEL_IN_CPU'},
     'high': {},
 }
+MODELS_TO_LOAD_ON_START = ['stable-diffusion', 'vae', 'hypernetwork']
 
 known_models = {}
 
@@ -37,16 +38,12 @@ def init():
     getModels() # run this once, to cache the picklescan results
 
 def load_default_models(context: Context):
-    # init default model paths
-    for model_type in KNOWN_MODEL_TYPES:
-        context.model_paths[model_type] = resolve_model_to_use(model_type=model_type)
-
     set_vram_optimizations(context)
 
-    # load mandatory models
-    load_model(context, 'stable-diffusion', scan_model=False) # we've scanned them already
-    load_model(context, 'vae')
-    load_model(context, 'hypernetwork')
+    # init default model paths
+    for model_type in MODELS_TO_LOAD_ON_START:
+        context.model_paths[model_type] = resolve_model_to_use(model_type=model_type)
+        load_model(context, model_type)
 
 def unload_all(context: Context):
     for model_type in KNOWN_MODEL_TYPES:
@@ -106,7 +103,7 @@ def reload_models_if_necessary(context: Context, task_data: TaskData):
 
     if 'stable-diffusion' in models_to_reload:
         quick_hash = hash_file_quick(models_to_reload['stable-diffusion'])
-        known_model_info = get_known_model_info(quick_hash=quick_hash)
+        known_model_info = get_model_info_from_db(quick_hash=quick_hash)
 
     for model_type, model_path_in_req in models_to_reload.items():
         context.model_paths[model_type] = model_path_in_req
@@ -120,7 +117,7 @@ def resolve_model_paths(task_data: TaskData):
     task_data.use_hypernetwork_model = resolve_model_to_use(task_data.use_hypernetwork_model, model_type='hypernetwork')
 
     if task_data.use_face_correction: task_data.use_face_correction = resolve_model_to_use(task_data.use_face_correction, 'gfpgan')
-    if task_data.use_upscale: task_data.use_upscale = resolve_model_to_use(task_data.use_upscale, 'gfpgan')
+    if task_data.use_upscale: task_data.use_upscale = resolve_model_to_use(task_data.use_upscale, 'realesrgan')
 
 def set_vram_optimizations(context: Context):
     config = app.getConfig()
diff --git a/ui/easydiffusion/renderer.py b/ui/easydiffusion/renderer.py
index 4b9847c0..b55f3667 100644
--- a/ui/easydiffusion/renderer.py
+++ b/ui/easydiffusion/renderer.py
@@ -73,8 +73,8 @@ def filter_images(task_data: TaskData, images: list, user_stopped):
         return images
 
     filters_to_apply = []
-    if 'gfpgan' in task_data.use_face_correction.lower(): filters_to_apply.append('gfpgan')
-    if 'realesrgan' in task_data.use_face_correction.lower(): filters_to_apply.append('realesrgan')
+    if task_data.use_face_correction and 'gfpgan' in task_data.use_face_correction.lower(): filters_to_apply.append('gfpgan')
+    if task_data.use_upscale and 'realesrgan' in task_data.use_upscale.lower(): filters_to_apply.append('realesrgan')
 
     return apply_filters(context, filters_to_apply, images)
 

From 6662dc66d53e3af274fa7b83e98121d71e5aee97 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 13:37:50 +0530
Subject: [PATCH 59/74] Updated scripts to install sdkit into existing
 installations, while still working with new installations

---
 scripts/Developer Console.cmd |  19 ++--
 scripts/check_modules.py      |  15 +++
 scripts/developer_console.sh  |  20 ++--
 scripts/on_env_start.bat      |   1 +
 scripts/on_env_start.sh       |   1 +
 scripts/on_sd_start.bat       | 194 ++++++++++------------------------
 scripts/on_sd_start.sh        | 144 +++++++------------------
 7 files changed, 129 insertions(+), 265 deletions(-)
 create mode 100644 scripts/check_modules.py

diff --git a/scripts/Developer Console.cmd b/scripts/Developer Console.cmd
index 750e4311..921a9dca 100644
--- a/scripts/Developer Console.cmd	
+++ b/scripts/Developer Console.cmd	
@@ -23,23 +23,20 @@ call conda --version
 
 echo.
 
-@rem activate the environment
-call conda activate .\stable-diffusion\env
+@rem activate the legacy environment (if present) and set PYTHONPATH
+if exist "installer_files\env" (
+    set PYTHONPATH=%cd%\installer_files\env\lib\site-packages
+)
+if exist "stable-diffusion\env" (
+    call conda activate .\stable-diffusion\env
+    set PYTHONPATH=%cd%\stable-diffusion\env\lib\site-packages
+)
 
 call where python
 call python --version
 
-@rem set the PYTHONPATH
-cd stable-diffusion
-set SD_DIR=%cd%
-
-cd env\lib\site-packages
-set PYTHONPATH=%SD_DIR%;%cd%
-cd ..\..\..
 echo PYTHONPATH=%PYTHONPATH%
 
-cd ..
-
 @rem done
 echo.
 
diff --git a/scripts/check_modules.py b/scripts/check_modules.py
new file mode 100644
index 00000000..2944f540
--- /dev/null
+++ b/scripts/check_modules.py
@@ -0,0 +1,15 @@
+'''
+This script checks if the given modules exist
+'''
+
+import sys
+import pkgutil
+
+modules = sys.argv[1:]
+missing_modules = []
+for m in modules:
+    if pkgutil.find_loader(m) is None:
+        print('module', m, 'not found')
+        exit(1)
+
+print('ok')
diff --git a/scripts/developer_console.sh b/scripts/developer_console.sh
index 49e71b34..73972568 100755
--- a/scripts/developer_console.sh
+++ b/scripts/developer_console.sh
@@ -26,21 +26,23 @@ if [ "$0" == "bash" ]; then
 
   echo ""
 
-  # activate the environment
-  CONDA_BASEPATH=$(conda info --base)
-  source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # otherwise conda complains about 'shell not initialized' (needed when running in a script)
+  # activate the legacy environment (if present) and set PYTHONPATH
+  if [ -e "installer_files/env" ]; then
+    export PYTHONPATH="$(pwd)/installer_files/env/lib/python3.8/site-packages"
+  fi
+  if [ -e "stable-diffusion/env" ]; then
+    CONDA_BASEPATH=$(conda info --base)
+    source "$CONDA_BASEPATH/etc/profile.d/conda.sh" # otherwise conda complains about 'shell not initialized' (needed when running in a script)
 
-  conda activate ./stable-diffusion/env
+    conda activate ./stable-diffusion/env
+
+    export PYTHONPATH="$(pwd)/stable-diffusion/env/lib/python3.8/site-packages"
+  fi
 
   which python
   python --version
 
-  # set the PYTHONPATH
-  cd stable-diffusion
-  SD_PATH=`pwd`
-  export PYTHONPATH="$SD_PATH:$SD_PATH/env/lib/python3.8/site-packages"
   echo "PYTHONPATH=$PYTHONPATH"
-  cd ..
 
   # done
 
diff --git a/scripts/on_env_start.bat b/scripts/on_env_start.bat
index b18b4f4e..13d54161 100644
--- a/scripts/on_env_start.bat
+++ b/scripts/on_env_start.bat
@@ -53,6 +53,7 @@ if "%update_branch%"=="" (
 @xcopy sd-ui-files\ui ui /s /i /Y /q
 @copy sd-ui-files\scripts\on_sd_start.bat scripts\ /Y
 @copy sd-ui-files\scripts\bootstrap.bat scripts\ /Y
+@copy sd-ui-files\scripts\check_modules.py scripts\ /Y
 @copy "sd-ui-files\scripts\Start Stable Diffusion UI.cmd" . /Y
 @copy "sd-ui-files\scripts\Developer Console.cmd" . /Y
 
diff --git a/scripts/on_env_start.sh b/scripts/on_env_start.sh
index 185e4fd4..cac307c2 100755
--- a/scripts/on_env_start.sh
+++ b/scripts/on_env_start.sh
@@ -37,6 +37,7 @@ rm -rf ui
 cp -Rf sd-ui-files/ui .
 cp sd-ui-files/scripts/on_sd_start.sh scripts/
 cp sd-ui-files/scripts/bootstrap.sh scripts/
+cp sd-ui-files/scripts/check_modules.py scripts/
 cp sd-ui-files/scripts/start.sh .
 cp sd-ui-files/scripts/developer_console.sh .
 
diff --git a/scripts/on_sd_start.bat b/scripts/on_sd_start.bat
index 620d0909..55b8e377 100644
--- a/scripts/on_sd_start.bat
+++ b/scripts/on_sd_start.bat
@@ -10,6 +10,14 @@ if exist "%cd%\profile" (
     set USERPROFILE=%cd%\profile
 )
 
+@rem set the correct installer path (current vs legacy)
+if exist "%cd%\installer_files\env" (
+    set INSTALL_ENV_DIR=%cd%\installer_files\env
+)
+if exist "%cd%\stable-diffusion\env" (
+    set INSTALL_ENV_DIR=%cd%\stable-diffusion\env
+)
+
 @mkdir tmp
 @set TMP=%cd%\tmp
 @set TEMP=%cd%\tmp
@@ -27,137 +35,71 @@ if exist "Open Developer Console.cmd" del "Open Developer Console.cmd"
 
 @call python -c "import os; import shutil; frm = 'sd-ui-files\\ui\\hotfix\\9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'; dst = os.path.join(os.path.expanduser('~'), '.cache', 'huggingface', 'transformers', '9c24e6cd9f499d02c4f21a033736dabd365962dc80fe3aeb57a8f85ea45a20a3.26fead7ea4f0f843f6eb4055dfd25693f1a71f3c6871b184042d4b126244e142'); shutil.copyfile(frm, dst) if os.path.exists(dst) else print(''); print('Hotfixed broken JSON file from OpenAI');"
 
-if NOT DEFINED test_sd2 set test_sd2=N
+@rem create the stable-diffusion folder, to work with legacy installations
+if not exist "stable-diffusion" mkdir stable-diffusion
+cd stable-diffusion
 
-@>nul findstr /m "sd_git_cloned" scripts\install_status.txt
-@if "%ERRORLEVEL%" EQU "0" (
-    @echo "Stable Diffusion's git repository was already installed. Updating.."
-
-    @cd stable-diffusion
-
-    @call git remote set-url origin https://github.com/easydiffusion/diffusion-kit.git
-
-    @call git reset --hard
-    @call git pull
-
-    if "%test_sd2%" == "N" (
-        @call git -c advice.detachedHead=false checkout 7f32368ed1030a6e710537047bacd908adea183a
-    )
-    if "%test_sd2%" == "Y" (
-        @call git -c advice.detachedHead=false checkout 733a1f6f9cae9b9a9b83294bf3281b123378cb1f
-    )
-
-    @cd ..
-) else (
-    @echo. & echo "Downloading Stable Diffusion.." & echo.
-
-    @call git clone https://github.com/easydiffusion/diffusion-kit.git stable-diffusion && (
-        @echo sd_git_cloned >> scripts\install_status.txt
-    ) || (
-        @echo "Error downloading Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
-        pause
-        @exit /b
-    )
-
-    @cd stable-diffusion
-    @call git -c advice.detachedHead=false checkout 7f32368ed1030a6e710537047bacd908adea183a
-
-    @cd ..
+@rem activate the old stable-diffusion env, if it exists
+if exist "env" (
+    call conda activate .\env
 )
 
-@cd stable-diffusion
-
-@>nul findstr /m "conda_sd_env_created" ..\scripts\install_status.txt
-@if "%ERRORLEVEL%" EQU "0" (
-    @echo "Packages necessary for Stable Diffusion were already installed"
-
-    @call conda activate .\env
+@rem install torch and torchvision
+call python ..\scripts\check_modules.py torch torchvision
+if "%ERRORLEVEL%" EQU "0" (
+    echo "torch and torchvision have already been installed."
 ) else (
-    @echo. & echo "Downloading packages necessary for Stable Diffusion.." & echo. & echo "***** This will take some time (depending on the speed of the Internet connection) and may appear to be stuck, but please be patient ***** .." & echo.
-
-    @rmdir /s /q .\env
+    echo "Installing torch and torchvision.."
 
     @REM prevent conda from using packages from the user's home directory, to avoid conflicts
-    @set PYTHONNOUSERSITE=1
+    set PYTHONNOUSERSITE=1
+    set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
 
-    set USERPROFILE=%cd%\profile
-
-    set PYTHONPATH=%cd%;%cd%\env\lib\site-packages
-
-    @call conda env create --prefix env -f environment.yaml || (
-        @echo. & echo "Error installing the packages necessary for Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+    call pip install --upgrade torch torchvision --extra-index-url https://download.pytorch.org/whl/cu116 || (
+        echo "Error installing torch. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
         pause
         exit /b
     )
+)
 
-    @call conda activate .\env
+@rem install/upgrade sdkit
+call python ..\scripts\check_modules.py sdkit sdkit.models ldm transformers numpy antlr4 gfpgan realesrgan
+if "%ERRORLEVEL%" EQU "0" (
+    echo "sdkit is already installed."
 
-    for /f "tokens=*" %%a in ('python -c "import torch; import ldm; import transformers; import numpy; import antlr4; print(42)"') do if "%%a" NEQ "42" (
-        @echo. & echo "Dependency test failed! Error installing the packages necessary for Stable Diffusion. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
+    @REM prevent conda from using packages from the user's home directory, to avoid conflicts
+    set PYTHONNOUSERSITE=1
+    set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
+
+    call >nul pip install --upgrade sdkit || (
+        echo "Error updating sdkit"
+    )
+) else (
+    echo "Installing sdkit: https://pypi.org/project/sdkit/"
+
+    @REM prevent conda from using packages from the user's home directory, to avoid conflicts
+    set PYTHONNOUSERSITE=1
+    set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
+
+    call pip install sdkit || (
+        echo "Error installing sdkit. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
         pause
         exit /b
     )
-
-    @echo conda_sd_env_created >> ..\scripts\install_status.txt
 )
 
 set PATH=C:\Windows\System32;%PATH%
 
-@>nul findstr /m "conda_sd_gfpgan_deps_installed" ..\scripts\install_status.txt
-@if "%ERRORLEVEL%" EQU "0" (
-    @echo "Packages necessary for GFPGAN (Face Correction) were already installed"
-) else (
-    @echo. & echo "Downloading packages necessary for GFPGAN (Face Correction).." & echo.
-
-    @set PYTHONNOUSERSITE=1
-
-    set USERPROFILE=%cd%\profile
-
-    set PYTHONPATH=%cd%;%cd%\env\lib\site-packages
-
-    for /f "tokens=*" %%a in ('python -c "from gfpgan import GFPGANer; print(42)"') do if "%%a" NEQ "42" (
-        @echo. & echo "Dependency test failed! Error installing the packages necessary for GFPGAN (Face Correction). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-        pause
-        exit /b
-    )
-
-    @echo conda_sd_gfpgan_deps_installed >> ..\scripts\install_status.txt
-)
-
-@>nul findstr /m "conda_sd_esrgan_deps_installed" ..\scripts\install_status.txt
-@if "%ERRORLEVEL%" EQU "0" (
-    @echo "Packages necessary for ESRGAN (Resolution Upscaling) were already installed"
-) else (
-    @echo. & echo "Downloading packages necessary for ESRGAN (Resolution Upscaling).." & echo.
-
-    @set PYTHONNOUSERSITE=1
-
-    set USERPROFILE=%cd%\profile
-
-    set PYTHONPATH=%cd%;%cd%\env\lib\site-packages
-
-    for /f "tokens=*" %%a in ('python -c "from basicsr.archs.rrdbnet_arch import RRDBNet; from realesrgan import RealESRGANer; print(42)"') do if "%%a" NEQ "42" (
-        @echo. & echo "Dependency test failed! Error installing the packages necessary for ESRGAN (Resolution Upscaling). Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
-        pause
-        exit /b
-    )
-
-    @echo conda_sd_esrgan_deps_installed >> ..\scripts\install_status.txt
-)
-
-@>nul findstr /m "conda_sd_ui_deps_installed" ..\scripts\install_status.txt
+call python ..\scripts\check_modules.py uvicorn fastapi
 @if "%ERRORLEVEL%" EQU "0" (
     echo "Packages necessary for Stable Diffusion UI were already installed"
 ) else (
     @echo. & echo "Downloading packages necessary for Stable Diffusion UI.." & echo.
 
-    @set PYTHONNOUSERSITE=1
+    set PYTHONNOUSERSITE=1
+    set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
 
-    set USERPROFILE=%cd%\profile
-
-    set PYTHONPATH=%cd%;%cd%\env\lib\site-packages
-
-    @call conda install -c conda-forge -y --prefix env uvicorn fastapi || (
+    @call conda install -c conda-forge -y uvicorn fastapi || (
         echo "Error installing the packages necessary for Stable Diffusion UI. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
         pause
         exit /b
@@ -172,26 +114,6 @@ call WHERE uvicorn > .tmp
     exit /b
 )
 
-@>nul 2>nul call python -m picklescan --help
-@if "%ERRORLEVEL%" NEQ "0" (
-    @echo. & echo Picklescan not found. Installing
-    @call pip install picklescan || (
-        echo "Error installing the picklescan package necessary for Stable Diffusion UI. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
-        pause
-        exit /b
-    )
-)
-
-@>nul 2>nul call python -c "import safetensors"
-@if "%ERRORLEVEL%" NEQ "0" (
-    @echo. & echo SafeTensors not found. Installing
-    @call pip install safetensors || (
-        echo "Error installing the safetensors package necessary for Stable Diffusion UI. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
-        pause
-        exit /b
-    )
-)
-
 @>nul findstr /m "conda_sd_ui_deps_installed" ..\scripts\install_status.txt
 @if "%ERRORLEVEL%" NEQ "0" (
     @echo conda_sd_ui_deps_installed >> ..\scripts\install_status.txt
@@ -357,10 +279,6 @@ if not exist "..\models\vae" mkdir "..\models\vae"
     )
 )
 
-if "%test_sd2%" == "Y" (
-    @call pip install open_clip_torch==2.0.2
-)
-
 @>nul findstr /m "sd_install_complete" ..\scripts\install_status.txt
 @if "%ERRORLEVEL%" NEQ "0" (
     @echo sd_weights_downloaded >> ..\scripts\install_status.txt
@@ -371,10 +289,8 @@ if "%test_sd2%" == "Y" (
 
 @set SD_DIR=%cd%
 
-@cd env\lib\site-packages
-@set PYTHONPATH=%SD_DIR%;%cd%
-@cd ..\..\..
-@echo PYTHONPATH=%PYTHONPATH%
+set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
+echo PYTHONPATH=%PYTHONPATH%
 
 call where python
 call python --version
@@ -383,13 +299,9 @@ call python --version
 @set SD_UI_PATH=%cd%\ui
 @cd stable-diffusion
 
-@rem
-@rem Rewrite easy-install.pth. This fixes the installation if the user has relocated the SDUI installation
-@rem
->env\Lib\site-packages\easy-install.pth echo %cd%\src\taming-transformers
->>env\Lib\site-packages\easy-install.pth echo %cd%\src\clip
->>env\Lib\site-packages\easy-install.pth echo %cd%\src\gfpgan
->>env\Lib\site-packages\easy-install.pth echo %cd%\src\realesrgan
+@rem disable the legacy src and ldm folder
+if exist src rename src src-old
+if exist ldm rename ldm ldm-old
 
 @if NOT DEFINED SD_UI_BIND_PORT set SD_UI_BIND_PORT=9000
 @if NOT DEFINED SD_UI_BIND_IP set SD_UI_BIND_IP=0.0.0.0
diff --git a/scripts/on_sd_start.sh b/scripts/on_sd_start.sh
index 3e082b81..53f73277 100755
--- a/scripts/on_sd_start.sh
+++ b/scripts/on_sd_start.sh
@@ -21,116 +21,69 @@ python -c "import os; import shutil; frm = 'sd-ui-files/ui/hotfix/9c24e6cd9f499d
 # Caution, this file will make your eyes and brain bleed. It's such an unholy mess.
 # Note to self: Please rewrite this in Python. For the sake of your own sanity.
 
-if [ "$test_sd2" == "" ]; then
-    export test_sd2="N"
-fi
-
-if [ -e "scripts/install_status.txt" ] && [ `grep -c sd_git_cloned scripts/install_status.txt` -gt "0" ]; then
-    echo "Stable Diffusion's git repository was already installed. Updating.."
-
-    cd stable-diffusion
-
-    git remote set-url origin https://github.com/easydiffusion/diffusion-kit.git
-
-    git reset --hard
-    git pull
-
-    if [ "$test_sd2" == "N" ]; then
-        git -c advice.detachedHead=false checkout 7f32368ed1030a6e710537047bacd908adea183a
-    elif [ "$test_sd2" == "Y" ]; then
-        git -c advice.detachedHead=false checkout 733a1f6f9cae9b9a9b83294bf3281b123378cb1f
-    fi
-
-    cd ..
-else
-    printf "\n\nDownloading Stable Diffusion..\n\n"
-
-    if git clone https://github.com/easydiffusion/diffusion-kit.git stable-diffusion ; then
-        echo sd_git_cloned >> scripts/install_status.txt
-    else
-        fail "git clone of basujindal/stable-diffusion.git failed"
-    fi
-
-    cd stable-diffusion
-    git -c advice.detachedHead=false checkout 7f32368ed1030a6e710537047bacd908adea183a
-
-    cd ..
+# set the correct installer path (current vs legacy)
+if [ -e "installer_files/env" ]; then
+    export INSTALL_ENV_DIR="$(pwd)/installer_files/env"
+fi
+if [ -e "stable-diffusion/env" ]; then
+    export INSTALL_ENV_DIR="$(pwd)/stable-diffusion/env"
 fi
 
+# create the stable-diffusion folder, to work with legacy installations
+if [ ! -e "stable-diffusion" ]; then mkdir stable-diffusion; fi
 cd stable-diffusion
 
-if [ `grep -c conda_sd_env_created ../scripts/install_status.txt` -gt "0" ]; then
-    echo "Packages necessary for Stable Diffusion were already installed"
-
+# activate the old stable-diffusion env, if it exists
+if [ -e "env" ]; then
     conda activate ./env || fail "conda activate failed"
+fi
+
+# install torch and torchvision
+if python ../scripts/check_modules.py torch torchvision; then
+    echo "torch and torchvision have already been installed."
 else
-    printf "\n\nDownloading packages necessary for Stable Diffusion..\n"
-    printf "\n\n***** This will take some time (depending on the speed of the Internet connection) and may appear to be stuck, but please be patient ***** ..\n\n"
+    echo "Installing torch and torchvision.."
 
-    # prevent conda from using packages from the user's home directory, to avoid conflicts
     export PYTHONNOUSERSITE=1
-    export PYTHONPATH="$(pwd):$(pwd)/env/lib/site-packages"
+    export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
 
-    if conda env create --prefix env --force -f environment.yaml ; then
-        echo "Installed. Testing.."
+    if pip install --upgrade torch torchvision --extra-index-url https://download.pytorch.org/whl/cu116 ; then
+        echo "Installed."
     else
-        fail "'conda env create' failed"
+        fail "torch install failed" 
     fi
-
-    conda activate ./env || fail "conda activate failed"
-
-    out_test=`python -c "import torch; import ldm; import transformers; import numpy; import antlr4; print(42)"`
-    if [ "$out_test" != "42" ]; then
-        fail "Dependency test failed"
-    fi
-
-    echo conda_sd_env_created >> ../scripts/install_status.txt
 fi
 
-if [ `grep -c conda_sd_gfpgan_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
-    echo "Packages necessary for GFPGAN (Face Correction) were already installed"
-else
-    printf "\n\nDownloading packages necessary for GFPGAN (Face Correction)..\n"
+# install/upgrade sdkit
+if python ../scripts/check_modules.py sdkit sdkit.models ldm transformers numpy antlr4 gfpgan realesrgan ; then
+    echo "sdkit is already installed."
 
     export PYTHONNOUSERSITE=1
-    export PYTHONPATH="$(pwd):$(pwd)/env/lib/site-packages"
+    export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
 
-    out_test=`python -c "from gfpgan import GFPGANer; print(42)"`
-    if [ "$out_test" != "42" ]; then
-        echo "EE The dependency check has failed. This usually means that some system libraries are missing."
-	echo "EE On Debian/Ubuntu systems, this are often these packages: libsm6 libxext6 libxrender-dev"
-	echo "EE Other Linux distributions might have different package names for these libraries."
-        fail "GFPGAN dependency test failed"
-    fi
-
-    echo conda_sd_gfpgan_deps_installed >> ../scripts/install_status.txt
-fi
-
-if [ `grep -c conda_sd_esrgan_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
-    echo "Packages necessary for ESRGAN (Resolution Upscaling) were already installed"
+    pip install --upgrade sdkit > /dev/null
 else
-    printf "\n\nDownloading packages necessary for ESRGAN (Resolution Upscaling)..\n"
+    echo "Installing sdkit: https://pypi.org/project/sdkit/"
 
     export PYTHONNOUSERSITE=1
-    export PYTHONPATH="$(pwd):$(pwd)/env/lib/site-packages"
+    export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
 
-    out_test=`python -c "from basicsr.archs.rrdbnet_arch import RRDBNet; from realesrgan import RealESRGANer; print(42)"`
-    if [ "$out_test" != "42" ]; then
-        fail "ESRGAN dependency test failed"
+    if pip install sdkit ; then
+        echo "Installed."
+    else
+        fail "sdkit install failed"
     fi
-
-    echo conda_sd_esrgan_deps_installed >> ../scripts/install_status.txt
 fi
 
-if [ `grep -c conda_sd_ui_deps_installed ../scripts/install_status.txt` -gt "0" ]; then
+if python ../scripts/check_modules.py uvicorn fastapi ; then
     echo "Packages necessary for Stable Diffusion UI were already installed"
 else
     printf "\n\nDownloading packages necessary for Stable Diffusion UI..\n\n"
 
     export PYTHONNOUSERSITE=1
-    export PYTHONPATH="$(pwd):$(pwd)/env/lib/site-packages"
+    export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
 
-    if conda install -c conda-forge --prefix ./env -y uvicorn fastapi ; then
+    if conda install -c conda-forge -y uvicorn fastapi ; then
         echo "Installed. Testing.."
     else
         fail "'conda install uvicorn' failed" 
@@ -139,26 +92,8 @@ else
     if ! command -v uvicorn &> /dev/null; then
         fail "UI packages not found!"
     fi
-
-    echo conda_sd_ui_deps_installed >> ../scripts/install_status.txt
 fi
 
-if python -m picklescan --help >/dev/null 2>&1; then
-    echo "Picklescan is already installed."
-else
-    echo "Picklescan not found, installing."
-    pip install picklescan || fail "Picklescan installation failed."
-fi
-
-if python -c "import safetensors" --help >/dev/null 2>&1; then
-    echo "SafeTensors is already installed."
-else
-    echo "SafeTensors not found, installing."
-    pip install safetensors || fail "SafeTensors installation failed."
-fi
-
-
-
 mkdir -p "../models/vae"
 
 if [ -f "sd-v1-4.ckpt" ]; then
@@ -300,10 +235,6 @@ if [ ! -f "../models/vae/vae-ft-mse-840000-ema-pruned.ckpt" ]; then
     fi
 fi
 
-if [ "$test_sd2" == "Y" ]; then
-    pip install open_clip_torch==2.0.2
-fi
-
 if [ `grep -c sd_install_complete ../scripts/install_status.txt` -gt "0" ]; then
     echo sd_weights_downloaded >> ../scripts/install_status.txt
     echo sd_install_complete >> ../scripts/install_status.txt
@@ -312,7 +243,8 @@ fi
 printf "\n\nStable Diffusion is ready!\n\n"
 
 SD_PATH=`pwd`
-export PYTHONPATH="$SD_PATH:$SD_PATH/env/lib/python3.8/site-packages"
+
+export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
 echo "PYTHONPATH=$PYTHONPATH"
 
 which python
@@ -322,6 +254,10 @@ cd ..
 export SD_UI_PATH=`pwd`/ui
 cd stable-diffusion
 
+# disable the legacy src and ldm folder
+if [ -e "src" ]; then mv src src-old; fi
+if [ -e "ldm" ]; then mv ldm ldm-old; fi
+
 uvicorn server:server_api --app-dir "$SD_UI_PATH" --port ${SD_UI_BIND_PORT:-9000} --host ${SD_UI_BIND_IP:-0.0.0.0} --log-level error
 
 read -p "Press any key to continue"

From 243556656e964bdba29cfc96487ccbcc100cdf36 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 13:38:55 +0530
Subject: [PATCH 60/74] Temporarily disable the model config dropdown in the UI

---
 ui/index.html | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/ui/index.html b/ui/index.html
index c8d231ba..3114db96 100644
--- a/ui/index.html
+++ b/ui/index.html
@@ -129,10 +129,10 @@
                         </select>
                         <a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Custom-Models" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about custom models</span></i></a>
                     </td></tr>
-                    <tr id="modelConfigSelection" class="pl-5"><td><label for="model_config">Model Config:</i></label></td><td>
+                    <!-- <tr id="modelConfigSelection" class="pl-5"><td><label for="model_config">Model Config:</i></label></td><td>
                         <select id="model_config" name="model_config">
                         </select>
-                    </td></tr>
+                    </td></tr> -->
                     <tr class="pl-5"><td><label for="vae_model">Custom VAE:</i></label></td><td>
                         <select id="vae_model" name="vae_model">
                             <!-- <option value="" selected>None</option> -->

From ba7cae683ad26fe31612b9f8e6683b8eac78ad4b Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 13:39:28 +0530
Subject: [PATCH 61/74] Bump to 2.5

---
 ui/index.html | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ui/index.html b/ui/index.html
index 3114db96..58a6390f 100644
--- a/ui/index.html
+++ b/ui/index.html
@@ -25,7 +25,7 @@
         <div id="logo">
             <h1>
                 Stable Diffusion UI
-                <small>v2.4.21 <span id="updateBranchLabel"></span></small>
+                <small>v2.5.0 <span id="updateBranchLabel"></span></small>
             </h1>
         </div>
         <div id="server-status">

From 3a6780bd50bba3931b2f0dd31918df63ee107bfd Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 13:56:05 +0530
Subject: [PATCH 62/74] Copy check_modules.py the first time an existing user
 runs the new version

---
 scripts/on_sd_start.bat | 1 +
 scripts/on_sd_start.sh  | 1 +
 2 files changed, 2 insertions(+)

diff --git a/scripts/on_sd_start.bat b/scripts/on_sd_start.bat
index 55b8e377..b086485b 100644
--- a/scripts/on_sd_start.bat
+++ b/scripts/on_sd_start.bat
@@ -5,6 +5,7 @@
 
 @copy sd-ui-files\scripts\on_env_start.bat scripts\ /Y
 @copy sd-ui-files\scripts\bootstrap.bat scripts\ /Y
+@copy sd-ui-files\scripts\check_modules.py scripts\ /Y
 
 if exist "%cd%\profile" (
     set USERPROFILE=%cd%\profile
diff --git a/scripts/on_sd_start.sh b/scripts/on_sd_start.sh
index 53f73277..cc625ff6 100755
--- a/scripts/on_sd_start.sh
+++ b/scripts/on_sd_start.sh
@@ -4,6 +4,7 @@ source ./scripts/functions.sh
 
 cp sd-ui-files/scripts/on_env_start.sh scripts/
 cp sd-ui-files/scripts/bootstrap.sh scripts/
+cp sd-ui-files/scripts/check_modules.py scripts/
 
 # activate the installer env
 CONDA_BASEPATH=$(conda info --base)

From 8154a5709b7ee195d30a212ca566bf7771bbc215 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 14:01:33 +0530
Subject: [PATCH 63/74] disable the legacy src and ldm folder (otherwise this
 prevents installing gfpgan and realesrgan)

---
 scripts/on_sd_start.bat | 8 ++++----
 scripts/on_sd_start.sh  | 8 ++++----
 2 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/scripts/on_sd_start.bat b/scripts/on_sd_start.bat
index b086485b..73a22472 100644
--- a/scripts/on_sd_start.bat
+++ b/scripts/on_sd_start.bat
@@ -45,6 +45,10 @@ if exist "env" (
     call conda activate .\env
 )
 
+@rem disable the legacy src and ldm folder (otherwise this prevents installing gfpgan and realesrgan)
+if exist src rename src src-old
+if exist ldm rename ldm ldm-old
+
 @rem install torch and torchvision
 call python ..\scripts\check_modules.py torch torchvision
 if "%ERRORLEVEL%" EQU "0" (
@@ -300,10 +304,6 @@ call python --version
 @set SD_UI_PATH=%cd%\ui
 @cd stable-diffusion
 
-@rem disable the legacy src and ldm folder
-if exist src rename src src-old
-if exist ldm rename ldm ldm-old
-
 @if NOT DEFINED SD_UI_BIND_PORT set SD_UI_BIND_PORT=9000
 @if NOT DEFINED SD_UI_BIND_IP set SD_UI_BIND_IP=0.0.0.0
 @uvicorn server:server_api --app-dir "%SD_UI_PATH%" --port %SD_UI_BIND_PORT% --host %SD_UI_BIND_IP% --log-level error
diff --git a/scripts/on_sd_start.sh b/scripts/on_sd_start.sh
index cc625ff6..dee314c3 100755
--- a/scripts/on_sd_start.sh
+++ b/scripts/on_sd_start.sh
@@ -39,6 +39,10 @@ if [ -e "env" ]; then
     conda activate ./env || fail "conda activate failed"
 fi
 
+# disable the legacy src and ldm folder (otherwise this prevents installing gfpgan and realesrgan)
+if [ -e "src" ]; then mv src src-old; fi
+if [ -e "ldm" ]; then mv ldm ldm-old; fi
+
 # install torch and torchvision
 if python ../scripts/check_modules.py torch torchvision; then
     echo "torch and torchvision have already been installed."
@@ -255,10 +259,6 @@ cd ..
 export SD_UI_PATH=`pwd`/ui
 cd stable-diffusion
 
-# disable the legacy src and ldm folder
-if [ -e "src" ]; then mv src src-old; fi
-if [ -e "ldm" ]; then mv ldm ldm-old; fi
-
 uvicorn server:server_api --app-dir "$SD_UI_PATH" --port ${SD_UI_BIND_PORT:-9000} --host ${SD_UI_BIND_IP:-0.0.0.0} --log-level error
 
 read -p "Press any key to continue"

From fb5c0a3db796c414ae621b4ee870f8bc3fcfbe62 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 14:57:57 +0530
Subject: [PATCH 64/74] Install python 3.8.5 during installation. Torch isn't
 available for 3.11

---
 scripts/bootstrap.bat | 2 +-
 scripts/bootstrap.sh  | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/scripts/bootstrap.bat b/scripts/bootstrap.bat
index cb0909d0..c58ddcce 100644
--- a/scripts/bootstrap.bat
+++ b/scripts/bootstrap.bat
@@ -24,7 +24,7 @@ if exist "%INSTALL_ENV_DIR%" set PATH=%INSTALL_ENV_DIR%;%INSTALL_ENV_DIR%\Librar
 set PACKAGES_TO_INSTALL=
 
 if not exist "%LEGACY_INSTALL_ENV_DIR%\etc\profile.d\conda.sh" (
-    if not exist "%INSTALL_ENV_DIR%\etc\profile.d\conda.sh" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% conda
+    if not exist "%INSTALL_ENV_DIR%\etc\profile.d\conda.sh" set PACKAGES_TO_INSTALL=%PACKAGES_TO_INSTALL% conda python=3.8.5
 )
 
 call git --version >.tmp1 2>.tmp2
diff --git a/scripts/bootstrap.sh b/scripts/bootstrap.sh
index 6a929133..6a8df9b3 100755
--- a/scripts/bootstrap.sh
+++ b/scripts/bootstrap.sh
@@ -39,7 +39,7 @@ if [ -e "$INSTALL_ENV_DIR" ]; then export PATH="$INSTALL_ENV_DIR/bin:$PATH"; fi
 
 PACKAGES_TO_INSTALL=""
 
-if [ ! -e "$LEGACY_INSTALL_ENV_DIR/etc/profile.d/conda.sh" ] && [ ! -e "$INSTALL_ENV_DIR/etc/profile.d/conda.sh" ]; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL conda"; fi
+if [ ! -e "$LEGACY_INSTALL_ENV_DIR/etc/profile.d/conda.sh" ] && [ ! -e "$INSTALL_ENV_DIR/etc/profile.d/conda.sh" ]; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL conda python=3.8.5"; fi
 if ! hash "git" &>/dev/null; then PACKAGES_TO_INSTALL="$PACKAGES_TO_INSTALL git"; fi
 
 if "$MAMBA_ROOT_PREFIX/micromamba" --version &>/dev/null; then umamba_exists="T"; fi

From e0b33a4febb9d6cbde268f7e9d9316ae73dcbd47 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 15:10:46 +0530
Subject: [PATCH 65/74] Install rich

---
 scripts/on_sd_start.bat | 23 ++++++++++++++++++++---
 scripts/on_sd_start.sh  | 16 ++++++++++++++++
 2 files changed, 36 insertions(+), 3 deletions(-)

diff --git a/scripts/on_sd_start.bat b/scripts/on_sd_start.bat
index 73a22472..5fb629e4 100644
--- a/scripts/on_sd_start.bat
+++ b/scripts/on_sd_start.bat
@@ -56,7 +56,7 @@ if "%ERRORLEVEL%" EQU "0" (
 ) else (
     echo "Installing torch and torchvision.."
 
-    @REM prevent conda from using packages from the user's home directory, to avoid conflicts
+    @REM prevent from using packages from the user's home directory, to avoid conflicts
     set PYTHONNOUSERSITE=1
     set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
 
@@ -72,7 +72,7 @@ call python ..\scripts\check_modules.py sdkit sdkit.models ldm transformers nump
 if "%ERRORLEVEL%" EQU "0" (
     echo "sdkit is already installed."
 
-    @REM prevent conda from using packages from the user's home directory, to avoid conflicts
+    @REM prevent from using packages from the user's home directory, to avoid conflicts
     set PYTHONNOUSERSITE=1
     set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
 
@@ -82,7 +82,7 @@ if "%ERRORLEVEL%" EQU "0" (
 ) else (
     echo "Installing sdkit: https://pypi.org/project/sdkit/"
 
-    @REM prevent conda from using packages from the user's home directory, to avoid conflicts
+    @REM prevent from using packages from the user's home directory, to avoid conflicts
     set PYTHONNOUSERSITE=1
     set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
 
@@ -93,6 +93,23 @@ if "%ERRORLEVEL%" EQU "0" (
     )
 )
 
+@rem install rich
+call python ..\scripts\check_modules.py rich
+if "%ERRORLEVEL%" EQU "0" (
+    echo "rich has already been installed."
+) else (
+    echo "Installing rich.."
+
+    set PYTHONNOUSERSITE=1
+    set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
+
+    call pip install rich || (
+        echo "Error installing rich. Sorry about that, please try to:" & echo "  1. Run this installer again." & echo "  2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo "  3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo "  4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!"
+        pause
+        exit /b
+    )
+)
+
 set PATH=C:\Windows\System32;%PATH%
 
 call python ..\scripts\check_modules.py uvicorn fastapi
diff --git a/scripts/on_sd_start.sh b/scripts/on_sd_start.sh
index dee314c3..c98dff46 100755
--- a/scripts/on_sd_start.sh
+++ b/scripts/on_sd_start.sh
@@ -80,6 +80,22 @@ else
     fi
 fi
 
+# install rich
+if python ../scripts/check_modules.py rich; then
+    echo "rich has already been installed."
+else
+    echo "Installing rich.."
+
+    export PYTHONNOUSERSITE=1
+    export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
+
+    if pip install rich ; then
+        echo "Installed."
+    else
+        fail "Install failed for rich"
+    fi
+fi
+
 if python ../scripts/check_modules.py uvicorn fastapi ; then
     echo "Packages necessary for Stable Diffusion UI were already installed"
 else

From a4728190c0bfaf4982ac4231f18a28dde3047c23 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 15:29:49 +0530
Subject: [PATCH 66/74] Refactor server.py

---
 scripts/on_sd_start.bat          |  2 +-
 scripts/on_sd_start.sh           |  2 +-
 ui/{ => easydiffusion}/server.py | 80 +++++++++++++++++++-------------
 ui/main.py                       | 10 ++++
 4 files changed, 60 insertions(+), 34 deletions(-)
 rename ui/{ => easydiffusion}/server.py (82%)
 create mode 100644 ui/main.py

diff --git a/scripts/on_sd_start.bat b/scripts/on_sd_start.bat
index 5fb629e4..60118056 100644
--- a/scripts/on_sd_start.bat
+++ b/scripts/on_sd_start.bat
@@ -323,7 +323,7 @@ call python --version
 
 @if NOT DEFINED SD_UI_BIND_PORT set SD_UI_BIND_PORT=9000
 @if NOT DEFINED SD_UI_BIND_IP set SD_UI_BIND_IP=0.0.0.0
-@uvicorn server:server_api --app-dir "%SD_UI_PATH%" --port %SD_UI_BIND_PORT% --host %SD_UI_BIND_IP% --log-level error
+@uvicorn main:server_api --app-dir "%SD_UI_PATH%" --port %SD_UI_BIND_PORT% --host %SD_UI_BIND_IP% --log-level error
 
 
 @pause
diff --git a/scripts/on_sd_start.sh b/scripts/on_sd_start.sh
index c98dff46..ce898be3 100755
--- a/scripts/on_sd_start.sh
+++ b/scripts/on_sd_start.sh
@@ -275,6 +275,6 @@ cd ..
 export SD_UI_PATH=`pwd`/ui
 cd stable-diffusion
 
-uvicorn server:server_api --app-dir "$SD_UI_PATH" --port ${SD_UI_BIND_PORT:-9000} --host ${SD_UI_BIND_IP:-0.0.0.0} --log-level error
+uvicorn main:server_api --app-dir "$SD_UI_PATH" --port ${SD_UI_BIND_PORT:-9000} --host ${SD_UI_BIND_IP:-0.0.0.0} --log-level error
 
 read -p "Press any key to continue"
diff --git a/ui/server.py b/ui/easydiffusion/server.py
similarity index 82%
rename from ui/server.py
rename to ui/easydiffusion/server.py
index 8d9a129e..56535f1f 100644
--- a/ui/server.py
+++ b/ui/easydiffusion/server.py
@@ -39,13 +39,50 @@ class SetAppConfigRequest(BaseModel):
     listen_to_network: bool = None
     listen_port: int = None
 
-server_api.mount('/media', NoCacheStaticFiles(directory=os.path.join(app.SD_UI_DIR, 'media')), name="media")
+def init():
+    server_api.mount('/media', NoCacheStaticFiles(directory=os.path.join(app.SD_UI_DIR, 'media')), name="media")
 
-for plugins_dir, dir_prefix in app.UI_PLUGINS_SOURCES:
-    server_api.mount(f'/plugins/{dir_prefix}', NoCacheStaticFiles(directory=plugins_dir), name=f"plugins-{dir_prefix}")
+    for plugins_dir, dir_prefix in app.UI_PLUGINS_SOURCES:
+        server_api.mount(f'/plugins/{dir_prefix}', NoCacheStaticFiles(directory=plugins_dir), name=f"plugins-{dir_prefix}")
 
-@server_api.post('/app_config')
-async def setAppConfig(req : SetAppConfigRequest):
+    @server_api.post('/app_config')
+    async def set_app_config(req : SetAppConfigRequest):
+        return set_app_config_internal(req)
+
+    @server_api.get('/get/{key:path}')
+    def read_web_data(key:str=None):
+        return read_web_data_internal(key)
+
+    @server_api.get('/ping') # Get server and optionally session status.
+    def ping(session_id:str=None):
+        return ping_internal(session_id)
+
+    @server_api.post('/render')
+    def render(req: dict):
+        return render_internal(req)
+
+    @server_api.get('/image/stream/{task_id:int}')
+    def stream(task_id:int):
+        return stream_internal(task_id)
+
+    @server_api.get('/image/stop')
+    def stop(task: int):
+        return stop_internal(task)
+
+    @server_api.get('/image/tmp/{task_id:int}/{img_id:int}')
+    def get_image(task_id: int, img_id: int):
+        return get_image_internal(task_id, img_id)
+
+    @server_api.get('/')
+    def read_root():
+        return FileResponse(os.path.join(app.SD_UI_DIR, 'index.html'), headers=NOCACHE_HEADERS)
+
+    @server_api.on_event("shutdown")
+    def shutdown_event(): # Signal render thread to close on shutdown
+        task_manager.current_state_error = SystemExit('Application shutting down.')
+
+# API implementations
+def set_app_config_internal(req : SetAppConfigRequest):
     config = app.getConfig()
     if req.update_branch is not None:
         config['update_branch'] = req.update_branch
@@ -83,8 +120,7 @@ def update_render_devices_in_config(config, render_devices):
 
     config['render_devices'] = render_devices
 
-@server_api.get('/get/{key:path}')
-def read_web_data(key:str=None):
+def read_web_data_internal(key:str=None):
     if not key: # /get without parameters, stable-diffusion easter egg.
         raise HTTPException(status_code=418, detail="StableDiffusion is drawing a teapot!") # HTTP418 I'm a teapot
     elif key == 'app_config':
@@ -105,8 +141,7 @@ def read_web_data(key:str=None):
     else:
         raise HTTPException(status_code=404, detail=f'Request for unknown {key}') # HTTP404 Not Found
 
-@server_api.get('/ping') # Get server and optionally session status.
-def ping(session_id:str=None):
+def ping_internal(session_id:str=None):
     if task_manager.is_alive() <= 0: # Check that render threads are alive.
         if task_manager.current_state_error: raise HTTPException(status_code=500, detail=str(task_manager.current_state_error))
         raise HTTPException(status_code=500, detail='Render thread is dead.')
@@ -119,8 +154,7 @@ def ping(session_id:str=None):
     response['devices'] = task_manager.get_devices()
     return JSONResponse(response, headers=NOCACHE_HEADERS)
 
-@server_api.post('/render')
-def render(req: dict):
+def render_internal(req: dict):
     try:
         # separate out the request data into rendering and task-specific data
         render_req: GenerateImageRequest = GenerateImageRequest.parse_obj(req)
@@ -147,8 +181,7 @@ def render(req: dict):
         log.error(traceback.format_exc())
         raise HTTPException(status_code=500, detail=str(e))
 
-@server_api.get('/image/stream/{task_id:int}')
-def stream(task_id:int):
+def stream_internal(task_id:int):
     #TODO Move to WebSockets ??
     task = task_manager.get_cached_task(task_id, update_ttl=True)
     if not task: raise HTTPException(status_code=404, detail=f'Request {task_id} not found.') # HTTP404 NotFound
@@ -161,8 +194,7 @@ def stream(task_id:int):
     #log.info(f'Session {session_id} opened live render stream {id(task.buffer_queue)}')
     return StreamingResponse(task.read_buffer_generator(), media_type='application/json')
 
-@server_api.get('/image/stop')
-def stop(task: int):
+def stop_internal(task: int):
     if not task:
         if task_manager.current_state == task_manager.ServerStates.Online or task_manager.current_state == task_manager.ServerStates.Unavailable:
             raise HTTPException(status_code=409, detail='Not currently running any tasks.') # HTTP409 Conflict
@@ -175,8 +207,7 @@ def stop(task: int):
     task.error = StopAsyncIteration(f'Task {task_id} stop requested.')
     return {'OK'}
 
-@server_api.get('/image/tmp/{task_id:int}/{img_id:int}')
-def get_image(task_id: int, img_id: int):
+def get_image_internal(task_id: int, img_id: int):
     task = task_manager.get_cached_task(task_id, update_ttl=True)
     if not task: raise HTTPException(status_code=410, detail=f'Task {task_id} could not be found.') # HTTP404 NotFound
     if not task.temp_images[img_id]: raise HTTPException(status_code=425, detail='Too Early, task data is not available yet.') # HTTP425 Too Early
@@ -186,18 +217,3 @@ def get_image(task_id: int, img_id: int):
         return StreamingResponse(img_data, media_type='image/jpeg')
     except KeyError as e:
         raise HTTPException(status_code=500, detail=str(e))
-
-@server_api.get('/')
-def read_root():
-    return FileResponse(os.path.join(app.SD_UI_DIR, 'index.html'), headers=NOCACHE_HEADERS)
-
-@server_api.on_event("shutdown")
-def shutdown_event(): # Signal render thread to close on shutdown
-    task_manager.current_state_error = SystemExit('Application shutting down.')
-
-# Init the app
-model_manager.init()
-app.init()
-
-# start the browser ui
-app.open_browser()
diff --git a/ui/main.py b/ui/main.py
new file mode 100644
index 00000000..77def4a5
--- /dev/null
+++ b/ui/main.py
@@ -0,0 +1,10 @@
+from easydiffusion import model_manager, app, server
+from easydiffusion.server import server_api # required for uvicorn
+
+# Init the app
+model_manager.init()
+app.init()
+server.init()
+
+# start the browser ui
+app.open_browser()

From 7a9f2190371bfb1729bd90f817bb196f8a6abe27 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 15:41:19 +0530
Subject: [PATCH 67/74] color logging

---
 ui/easydiffusion/app.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/ui/easydiffusion/app.py b/ui/easydiffusion/app.py
index 7f2dd12d..452e07cd 100644
--- a/ui/easydiffusion/app.py
+++ b/ui/easydiffusion/app.py
@@ -6,6 +6,8 @@ import traceback
 import logging
 from rich.logging import RichHandler
 
+from sdkit.utils import log as sdkit_log # hack, so we can overwrite the log config
+
 from easydiffusion import task_manager
 from easydiffusion.utils import log
 

From 73e92a688fdaaff613e0ffd91ab901965e1b1779 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 15:43:06 +0530
Subject: [PATCH 68/74] color logging 2

---
 ui/easydiffusion/app.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/ui/easydiffusion/app.py b/ui/easydiffusion/app.py
index 452e07cd..2a8d0804 100644
--- a/ui/easydiffusion/app.py
+++ b/ui/easydiffusion/app.py
@@ -11,6 +11,10 @@ from sdkit.utils import log as sdkit_log # hack, so we can overwrite the log con
 from easydiffusion import task_manager
 from easydiffusion.utils import log
 
+# Remove all handlers associated with the root logger object.
+for handler in logging.root.handlers[:]:
+    logging.root.removeHandler(handler)
+
 LOG_FORMAT = '%(asctime)s.%(msecs)03d %(levelname)s %(threadName)s %(message)s'
 logging.basicConfig(
         level=logging.INFO,

From 5f6b798e3598001e2ef723001f5f96e9d39f9cab Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 19:13:17 +0530
Subject: [PATCH 69/74] Stop printing annoying ok messages

---
 scripts/check_modules.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/scripts/check_modules.py b/scripts/check_modules.py
index 2944f540..416ad851 100644
--- a/scripts/check_modules.py
+++ b/scripts/check_modules.py
@@ -11,5 +11,3 @@ for m in modules:
     if pkgutil.find_loader(m) is None:
         print('module', m, 'not found')
         exit(1)
-
-print('ok')

From 84bddee2cef4486777dfcf9bc31d986e29f44880 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 19:41:36 +0530
Subject: [PATCH 70/74] Treat none as a boolean false in drag-and-drop

---
 ui/media/js/dnd.js | 1 +
 1 file changed, 1 insertion(+)

diff --git a/ui/media/js/dnd.js b/ui/media/js/dnd.js
index 37d99d44..b5d91880 100644
--- a/ui/media/js/dnd.js
+++ b/ui/media/js/dnd.js
@@ -25,6 +25,7 @@ function parseBoolean(stringValue) {
         case "no":
         case "off":
         case "0":
+        case "none":
         case null:
         case undefined:
           return false;

From 01320ac7353ecd067c2f3a34ae476e5c33855917 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 21:36:47 +0530
Subject: [PATCH 71/74] Rename project to Easy Diffusion

---
 ui/index.html | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ui/index.html b/ui/index.html
index 200825a5..9cd66eb5 100644
--- a/ui/index.html
+++ b/ui/index.html
@@ -24,7 +24,7 @@
     <div id="top-nav">
         <div id="logo">
             <h1>
-                Stable Diffusion UI
+                Easy Diffusion
                 <small>v2.5.0 <span id="updateBranchLabel"></span></small>
             </h1>
         </div>

From a2b55c0df73be217ce8de366b4d8ea4bcfdcf61a Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 21:44:42 +0530
Subject: [PATCH 72/74] Report precision

---
 ui/easydiffusion/device_manager.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ui/easydiffusion/device_manager.py b/ui/easydiffusion/device_manager.py
index 0f2ab850..252aeee4 100644
--- a/ui/easydiffusion/device_manager.py
+++ b/ui/easydiffusion/device_manager.py
@@ -115,7 +115,7 @@ def device_init(context, device):
         # Apply force_full_precision now before models are loaded.
         context.half_precision = False
 
-    log.info(f'Setting {device} as active')
+    log.info(f'Setting {device} as active, with precision: {"half" if context.half_precision else "full"}')
     torch.cuda.device(device)
 
     return

From 9a975321db098857a604e4405383ead49a49ae57 Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 23:11:13 +0530
Subject: [PATCH 73/74] v2.5 changelog

---
 CHANGES.md | 17 +++++++++++++++++
 1 file changed, 17 insertions(+)

diff --git a/CHANGES.md b/CHANGES.md
index 324bf261..c0a3877c 100644
--- a/CHANGES.md
+++ b/CHANGES.md
@@ -1,5 +1,22 @@
 # What's new?
 
+## v2.5
+### Major Changes
+- **Nearly twice as fast** - significantly faster speed of image generation. We're now pretty close to automatic1111's speed. Code contributions are welcome to make our project even faster: https://github.com/easydiffusion/sdkit/#is-it-fast
+- **Full support for Stable Diffusion 2.1** - supports loading v1.4 or v2.0 or v2.1 models seamlessly. No need to enable "Test SD2", and no need to add `sd2_` to your SD 2.0 model file names.
+- **Memory optimized Stable Diffusion 2.1** - you can now use 768x768 models for SD 2.1, with the same low VRAM optimizations that we've always had for SD 1.4.
+- **6 new samplers!** - explore the new samplers, some of which can generate great images in less than 10 inference steps!
+- **Model Merging** - You can now merge two models (`.ckpt` or `.safetensors`) and output `.ckpt` or `.safetensors` models, optionally in `fp16` precision. Details: https://github.com/cmdr2/stable-diffusion-ui/wiki/Model-Merging
+- **Fast loading/unloading of VAEs** - No longer needs to reload the entire Stable Diffusion model, each time you change the VAE
+- **Database of known models** - automatically picks the right configuration for known models. E.g. we automatically detect and apply "v" parameterization (required for some SD 2.0 models), and "fp32" attention precision (required for some SD 2.1 models).
+- **Color correction for img2img** - an option to preserve the color profile (histogram) of the initial image. This is especially useful if you're getting red-tinted images after inpainting/masking.
+- **Three GPU Memory Usage Settings** - `High` (fastest, maximum VRAM usage), `Balanced` (default - almost as fast, significantly lower VRAM usage), `Low` (slowest, very low VRAM usage). The `Low` setting is applied automatically for GPUs with less than 4 GB of VRAM.
+- **Save metadata as JSON** - You can now save the metadata files as either text or json files (choose in the Settings tab).
+- **Major rewrite of the code** - The codebase has been rewritten almost entirely (except for our task manager), to make it more manageable and easier for new developers to contribute features to. We've seperated our core engine into a new project called `sdkit`, which allows anyone to easily integrate Stable Diffusion into their programming projects (via a simple `pip install sdkit`): https://github.com/easydiffusion/sdkit/
+- **Name change** - Last, and probably the least, the UI is now called "Easy Diffusion". It indicates the focus of this project - an easy way for people to play with Stable Diffusion.
+
+Our focus continues to remain on an easy installation experience, and an easy user-interface. While still remaining pretty powerful, in terms of features and speed.
+
 ## v2.4
 ### Major Changes
 - **Allow reordering the task queue** (by dragging and dropping tasks). Thanks @madrang

From 13721f160e8296b635acc9ec9ab27993416a98cd Mon Sep 17 00:00:00 2001
From: cmdr2 <secondary.cmdr2@gmail.com>
Date: Sat, 24 Dec 2022 23:22:47 +0530
Subject: [PATCH 74/74] changelog grammar

---
 CHANGES.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/CHANGES.md b/CHANGES.md
index c0a3877c..9681dbe8 100644
--- a/CHANGES.md
+++ b/CHANGES.md
@@ -12,7 +12,7 @@
 - **Color correction for img2img** - an option to preserve the color profile (histogram) of the initial image. This is especially useful if you're getting red-tinted images after inpainting/masking.
 - **Three GPU Memory Usage Settings** - `High` (fastest, maximum VRAM usage), `Balanced` (default - almost as fast, significantly lower VRAM usage), `Low` (slowest, very low VRAM usage). The `Low` setting is applied automatically for GPUs with less than 4 GB of VRAM.
 - **Save metadata as JSON** - You can now save the metadata files as either text or json files (choose in the Settings tab).
-- **Major rewrite of the code** - The codebase has been rewritten almost entirely (except for our task manager), to make it more manageable and easier for new developers to contribute features to. We've seperated our core engine into a new project called `sdkit`, which allows anyone to easily integrate Stable Diffusion into their programming projects (via a simple `pip install sdkit`): https://github.com/easydiffusion/sdkit/
+- **Major rewrite of the code** - Most of the codebase has been reorganized and rewritten, to make it more manageable and easier for new developers to contribute features. We've separated our core engine into a new project called `sdkit`, which allows anyone to easily integrate Stable Diffusion (and related modules like GFPGAN etc) into their programming projects (via a simple `pip install sdkit`): https://github.com/easydiffusion/sdkit/
 - **Name change** - Last, and probably the least, the UI is now called "Easy Diffusion". It indicates the focus of this project - an easy way for people to play with Stable Diffusion.
 
 Our focus continues to remain on an easy installation experience, and an easy user-interface. While still remaining pretty powerful, in terms of features and speed.