[pull] master from comfyanonymous:master

comfy/cli_args.py

@@ -49,7 +49,8 @@ def __call__(self, parser, namespace, values, option_string=None):
 parser.add_argument("--input-directory", type=str, default=None, help="Set the ComfyUI input directory. Overrides --base-directory.")
 parser.add_argument("--auto-launch", action="store_true", help="Automatically launch ComfyUI in the default browser.")
 parser.add_argument("--disable-auto-launch", action="store_true", help="Disable auto launching the browser.")
-parser.add_argument("--cuda-device", type=int, default=None, metavar="DEVICE_ID", help="Set the id of the cuda device this instance will use.")
+parser.add_argument("--cuda-device", type=int, default=None, metavar="DEVICE_ID", help="Set the id of the cuda device this instance will use. All other devices will not be visible.")
+parser.add_argument("--default-device", type=int, default=None, metavar="DEFAULT_DEVICE_ID", help="Set the id of the default device, all other devices will stay visible.")
 cm_group = parser.add_mutually_exclusive_group()
 cm_group.add_argument("--cuda-malloc", action="store_true", help="Enable cudaMallocAsync (enabled by default for torch 2.0 and up).")
 cm_group.add_argument("--disable-cuda-malloc", action="store_true", help="Disable cudaMallocAsync.")

comfy/model_management.py

@@ -186,10 +186,7 @@ def get_total_memory(dev=None, torch_total_too=False):
         elif is_intel_xpu():
             stats = torch.xpu.memory_stats(dev)
             mem_reserved = stats['reserved_bytes.all.current']
-            if torch_version_numeric < (2, 6):
-                mem_total_xpu = torch.xpu.get_device_properties(dev).total_memory
-            else:
-                _, mem_total_xpu = torch.xpu.mem_get_info(dev)
+            mem_total_xpu = torch.xpu.get_device_properties(dev).total_memory
             mem_total_torch = mem_reserved
             mem_total = mem_total_xpu
         elif is_ascend_npu():
@@ -880,6 +877,7 @@ def vae_dtype(device=None, allowed_dtypes=[]):
             return d
 
         # NOTE: bfloat16 seems to work on AMD for the VAE but is extremely slow in some cases compared to fp32
+        # slowness still a problem on pytorch nightly 2.9.0.dev20250720+rocm6.4 tested on RDNA3
         if d == torch.bfloat16 and (not is_amd()) and should_use_bf16(device):
             return d
 
@@ -1109,10 +1107,7 @@ def get_free_memory(dev=None, torch_free_too=False):
             stats = torch.xpu.memory_stats(dev)
             mem_active = stats['active_bytes.all.current']
             mem_reserved = stats['reserved_bytes.all.current']
-            if torch_version_numeric < (2, 6):
-                mem_free_xpu = torch.xpu.get_device_properties(dev).total_memory - mem_reserved
-            else:
-                mem_free_xpu, _ = torch.xpu.mem_get_info(dev)
+            mem_free_xpu = torch.xpu.get_device_properties(dev).total_memory - mem_reserved
             mem_free_torch = mem_reserved - mem_active
             mem_free_total = mem_free_xpu + mem_free_torch
         elif is_ascend_npu():

main.py

@@ -115,6 +115,15 @@ def execute_script(script_path):
     logging.getLogger("xformers").addFilter(lambda record: 'A matching Triton is not available' not in record.getMessage())
 
 if __name__ == "__main__":
+    if args.default_device is not None:
+        default_dev = args.default_device
+        devices = list(range(32))
+        devices.remove(default_dev)
+        devices.insert(0, default_dev)
+        devices = ','.join(map(str, devices))
+        os.environ['CUDA_VISIBLE_DEVICES'] = str(devices)
+        os.environ['HIP_VISIBLE_DEVICES'] = str(devices)
+
     if args.cuda_device is not None:
         os.environ['CUDA_VISIBLE_DEVICES'] = str(args.cuda_device)
         os.environ['HIP_VISIBLE_DEVICES'] = str(args.cuda_device)