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Fix a bug where Face Correction (GFPGAN) would fail on cuda:N (i.e. GPUs other than cuda:0), as well as fail on CPU if the system had an incompatible GPU.

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cmdr2 2022-11-17 12:27:06 +05:30
parent cc3186a683
commit 97ee085f30
4 changed files with 17 additions and 20 deletions
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13
CHANGES.md
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@ -1,9 +1,8 @@
# What's new? # What's new?
### 2.4.6 ### 2.4
* 16 Nov 2022 - Fix a regression in VRAM usage during startup, which caused 'Out of Memory' errors when starting on GPUs with 4gb (or less) VRAM * 2.4.7 - 17 Nov 2022 - Fix a bug where Face Correction (GFPGAN) would fail on cuda:N (i.e. GPUs other than cuda:0), as well as fail on CPU if the system had an incompatible GPU.
* 2.4.6 - 16 Nov 2022 - Fix a regression in VRAM usage during startup, which caused 'Out of Memory' errors when starting on GPUs with 4gb (or less) VRAM
### 2.4.5 * 2.4.5 - 16 Nov 2022 - Add checkbox for "Open browser on startup".
* 16 Nov 2022 - Add checkbox for "Open browser on startup". * 2.4.5 - 16 Nov 2022 - Add a directory for core plugins that ship with Stable Diffusion UI by default.
* 16 Nov 2022 - Add a directory for core plugins that ship with Stable Diffusion UI by default. * 2.4.5 - 16 Nov 2022 - Add a "What's New?" tab as a core plugin, which fetches the contents of CHANGES.md from the app's release branch.
* 16 Nov 2022 - Add a "What's New?" tab as a core plugin, which fetches the contents of CHANGES.md from the app's release branch.

2
ui/index.html
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@ -20,7 +20,7 @@
<div id="container"> <div id="container">
<div id="top-nav"> <div id="top-nav">
<div id="logo"> <div id="logo">
<h1>Stable Diffusion UI <small>v2.4.6 <span id="updateBranchLabel"></span></small></h1> <h1>Stable Diffusion UI <small>v2.4.7 <span id="updateBranchLabel"></span></small></h1>
</div> </div>
<div id="server-status"> <div id="server-status">
<div id="server-status-color">●</div> <div id="server-status-color">●</div>

18
ui/sd_internal/runtime.py
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@ -236,9 +236,14 @@ def wait_model_move_to(model, target_device): # Send to target_device and wait u
def load_model_gfpgan(): def load_model_gfpgan():
if thread_data.gfpgan_file is None: raise ValueError(f'Thread gfpgan_file is undefined.') if thread_data.gfpgan_file is None: raise ValueError(f'Thread gfpgan_file is undefined.')
# 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)
model_path = thread_data.gfpgan_file + ".pth" model_path = thread_data.gfpgan_file + ".pth"
device = 'cuda:0' if force_gfpgan_to_cuda0 else thread_data.device 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)
thread_data.model_gfpgan = GFPGANer(device=torch.device(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) print('loaded', thread_data.gfpgan_file, 'to', thread_data.model_gfpgan.device, 'precision', thread_data.precision)
def load_model_real_esrgan(): def load_model_real_esrgan():
@ -288,10 +293,10 @@ def apply_filters(filter_name, image_data, model_path=None):
print(f'Applying filter {filter_name}...') print(f'Applying filter {filter_name}...')
gc() # Free space before loading new data. gc() # Free space before loading new data.
if filter_name == 'gfpgan': if isinstance(image_data, torch.Tensor):
if isinstance(image_data, torch.Tensor): image_data.to(thread_data.device)
image_data.to('cuda:0' if force_gfpgan_to_cuda0 else thread_data.device)
if filter_name == 'gfpgan':
if model_path is not None and model_path != thread_data.gfpgan_file: if model_path is not None and model_path != thread_data.gfpgan_file:
thread_data.gfpgan_file = model_path thread_data.gfpgan_file = model_path
load_model_gfpgan() load_model_gfpgan()
@ -303,9 +308,6 @@ def apply_filters(filter_name, image_data, model_path=None):
image_data = output[:,:,::-1] image_data = output[:,:,::-1]
if filter_name == 'real_esrgan': if filter_name == 'real_esrgan':
if isinstance(image_data, torch.Tensor):
image_data.to(thread_data.device)
if model_path is not None and model_path != thread_data.real_esrgan_file: if model_path is not None and model_path != thread_data.real_esrgan_file:
thread_data.real_esrgan_file = model_path thread_data.real_esrgan_file = model_path
load_model_real_esrgan() load_model_real_esrgan()

4
ui/sd_internal/task_manager.py
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@ -217,10 +217,6 @@ def thread_get_next_task():
task = None task = None
try: # Select a render task. try: # Select a render task.
for queued_task in tasks_queue: for queued_task in tasks_queue:
if queued_task.request.use_face_correction and runtime.thread_data.device == 'cpu' and is_alive() == 1:
queued_task.error = Exception('The CPU cannot be used to run this task currently. Please remove "Fix incorrect faces" from Image Settings and try again.')
task = queued_task
break
if queued_task.render_device and runtime.thread_data.device != queued_task.render_device: if queued_task.render_device and runtime.thread_data.device != queued_task.render_device:
# Is asking for a specific render device. # Is asking for a specific render device.
if is_alive(queued_task.render_device) > 0: if is_alive(queued_task.render_device) > 0: