Add support for MPS when running on Apple silicon

Changes:

* autodetect if MPS is available and the pytorch version has MPS support.
* change logic from "is the device CPU?" to "is the device not CUDA?".
* set PYTORCH_ENABLE_MPS_FALLBACK=1

Known issues:

* Some samplers (eg DDIM) will fail on MPS unless forced to CPU-only mode

scripts/on_sd_start.sh

@@ -285,6 +285,7 @@ printf "\n\nEasy Diffusion installation complete, starting the server!\n\n"
 
 SD_PATH=`pwd`
 
+export PYTORCH_ENABLE_MPS_FALLBACK=1
 export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
 echo "PYTHONPATH=$PYTHONPATH"
 

ui/easydiffusion/device_manager.py

@@ -1,4 +1,5 @@
 import os
+import platform
 import torch
 import traceback
 import re
@@ -66,6 +67,9 @@ def get_device_delta(render_devices, active_devices):
 def auto_pick_devices(currently_active_devices):
     global mem_free_threshold
 
+    if platform.system() == "Darwin" and torch.backends.mps.is_available() and torch.backends.mps.is_built():
+        return ["mps"]
+
     if not torch.cuda.is_available():
         return ["cpu"]
 
@@ -115,11 +119,11 @@ def device_init(context, device):
 
     validate_device_id(device, log_prefix="device_init")
 
-    if device == "cpu":
-        context.device = "cpu"
+    if "cuda" not in device:
+        context.device = device
         context.device_name = get_processor_name()
         context.half_precision = False
-        log.debug(f"Render device CPU available as {context.device_name}")
+        log.debug(f"Render device available as {context.device_name}")
         return
 
     context.device_name = torch.cuda.get_device_name(device)
@@ -134,8 +138,6 @@ def device_init(context, device):
     log.info(f'Setting {device} as active, with precision: {"half" if context.half_precision else "full"}')
     torch.cuda.device(device)
 
-    return
-
 
 def needs_to_force_full_precision(context):
     if "FORCE_FULL_PRECISION" in os.environ:
@@ -174,7 +176,7 @@ def validate_device_id(device, log_prefix=""):
     def is_valid():
         if not isinstance(device, str):
             return False
-        if device == "cpu":
+        if device == "cpu" or device == "mps":
             return True
         if not device.startswith("cuda:") or not device[5:].isnumeric():
             return False
@@ -182,7 +184,7 @@ def validate_device_id(device, log_prefix=""):
 
     if not is_valid():
         raise EnvironmentError(
-            f"{log_prefix}: device id should be 'cpu', or 'cuda:N' (where N is an integer index for the GPU). Got: {device}"
+            f"{log_prefix}: device id should be 'cpu', 'mps', or 'cuda:N' (where N is an integer index for the GPU). Got: {device}"
         )
 
 
@@ -217,14 +219,14 @@ def is_device_compatible(device):
 
 def get_processor_name():
     try:
-        import platform, subprocess
+        import subprocess
 
         if platform.system() == "Windows":
             return platform.processor()
         elif platform.system() == "Darwin":
             os.environ["PATH"] = os.environ["PATH"] + os.pathsep + "/usr/sbin"
             command = "sysctl -n machdep.cpu.brand_string"
-            return subprocess.check_output(command).strip()
+            return subprocess.check_output(command, shell=True).decode().strip()
         elif platform.system() == "Linux":
             command = "cat /proc/cpuinfo"
             all_info = subprocess.check_output(command, shell=True).decode().strip()

ui/easydiffusion/task_manager.py

@@ -385,7 +385,7 @@ def get_devices():
     }
 
     def get_device_info(device):
-        if device == "cpu":
+        if "cuda" not in device:
             return {"name": device_manager.get_processor_name()}
 
         mem_free, mem_total = torch.cuda.mem_get_info(device)