Merge branch 'master' into dev

README.md

@@ -66,10 +66,10 @@ Additional models will be added as they become available and there is public int
 - *nVidia* GPUs using **CUDA** libraries on both *Windows and Linux*
 - *AMD* GPUs using **ROCm** libraries on *Linux*.  
   Support will be extended to *Windows* once AMD releases ROCm for Windows
-- Any GPU compatibile with *DirectX* on *Windows* using **DirectML** libraries.  
-  This includes support for AMD GPUs that are not supported by native ROCm libraries
 - *Intel Arc* GPUs using **OneAPI** with *IPEX XPU* libraries on both *Windows and Linux*
-- *Intel* GPUs using **OpenVINO** libraries on both *Windows and Linux*
+- Any GPU compatible with *DirectX* on *Windows* using **DirectML** libraries.  
+  This includes support for AMD GPUs that are not supported by native ROCm libraries
+- Any GPU compatible with **OpenVINO** libraries on both *Windows and Linux*
 - *Apple M1/M2* on *OSX* using built-in support in Torch with **MPS** optimizations
 
 ## Install & Run

installer.py

@@ -419,7 +419,7 @@ def check_torch():
     elif allow_openvino and args.use_openvino:
         #Remove this after 2.1.0 releases
         log.info('Using OpenVINO')
-        torch_command = os.environ.get('TORCH_COMMAND', '--pre torch==2.1.0.dev20230726+cpu torchvision==0.16.0.dev20230726+cpu -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html')
+        torch_command = os.environ.get('TORCH_COMMAND', '--pre torch==2.1.0.dev20230820+cpu torchvision==0.16.0.dev20230820+cpu -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html')
     else:
         machine = platform.machine()
         if sys.platform == 'darwin':

modules/intel/openvino/__init__.py

@@ -1,4 +1,5 @@
 import os
+import sys
 import torch
 from openvino.frontend import FrontEndManager
 from openvino.frontend.pytorch.fx_decoder import TorchFXPythonDecoder
@@ -13,6 +14,25 @@ from hashlib import sha256
 import functools
 from modules import shared, devices
 
+def BUILD_MAP_UNPACK(self, inst):
+        items = self.popn(inst.argval)
+        # ensure everything is a dict
+        items = [BuiltinVariable(dict).call_function(self, [x], {}) for x in items] # noqa: F821
+        result = dict()
+        for x in items:
+            assert isinstance(x, ConstDictVariable) # noqa: F821
+        result.update(x.items)
+        self.push(
+            ConstDictVariable( # noqa: F821
+                result,
+                dict,
+                mutable_local=MutableLocal(), # noqa: F821
+                **VariableTracker.propagate(items), # noqa: F821
+            )
+        )
+tmp_torch = sys.modules["torch"]
+tmp_torch.BUILD_MAP_UNPACK_WITH_CALL = BUILD_MAP_UNPACK
+
 compiled_cache = {}
 max_openvino_partitions = 0
 partitioned_modules = {}
@@ -65,10 +85,6 @@ def get_device():
         shared.log.warning("OpenVINO: No compatible GPU detected!")
     os.environ.setdefault('OPENVINO_TORCH_BACKEND_DEVICE', device)
     shared.log.debug(f"OpenVINO Device: {device}")
-    if shared.opts.cuda_compile_errors and device not in core.available_devices:
-        shared.log.error(f"OpenVINO: Specified device {device} is not in the list of OpenVINO Available Devices")
-    assert device in core.available_devices, f"OpenVINO: Specified device {device} is not in the list of OpenVINO Available Devices"
-
     return device
 
 def cache_root_path():