Upate OpenVINO to PyTorch 2.6 and fix mismatched shapes error on too many resolution changes

modules/intel/openvino/__init__.py

@@ -3,10 +3,10 @@ import sys
 import torch
 import nncf
 
-from openvino.frontend import FrontEndManager
-from openvino.frontend.pytorch.fx_decoder import TorchFXPythonDecoder
 from openvino.frontend.pytorch.torchdynamo.partition import Partitioner
-from openvino.runtime import Core, Type, PartialShape, serialize
+from openvino.frontend.pytorch.fx_decoder import TorchFXPythonDecoder
+from openvino.frontend import FrontEndManager
+from openvino import Core, Type, PartialShape, serialize
 from openvino.properties import hint as ov_hints
 
 from torch._dynamo.backends.common import fake_tensor_unsupported
@@ -23,6 +23,11 @@ import functools
 from modules import shared, devices, sd_models
 
 
+torch._dynamo.eval_frame.check_if_dynamo_supported = lambda: True # pylint: disable=protected-access
+if hasattr(torch._dynamo.config, "inline_inbuilt_nn_modules"):
+    torch._dynamo.config.inline_inbuilt_nn_modules = False # pylint: disable=protected-access
+
+
 DEFAULT_OPENVINO_PYTHON_CONFIG = MappingProxyType(
     {
         "use_python_fusion_cache": True,
@@ -114,9 +119,9 @@ def cached_model_name(model_hash_str, device, args, cache_root, reversed = False
     for input_data in args:
         if isinstance(input_data, torch.SymInt):
             if reversed:
-                inputs_str = "_" + "torch.SymInt1" + inputs_str
+                inputs_str = "_" + "torch.SymInt[]" + inputs_str
             else:
-                inputs_str += "_" + "torch.SymInt1"
+                inputs_str += "_" + "torch.SymInt[]"
         elif isinstance(input_data, int):
             pass
         else:
@@ -176,7 +181,7 @@ def openvino_compile(gm: GraphModule, *example_inputs, model_hash_str: str = Non
         for input_data in example_inputs:
             if isinstance(input_data, torch.SymInt):
                 input_types.append(torch.SymInt)
-                input_shapes.append(torch.Size([1]))
+                input_shapes.append(torch.Size([]))
             elif isinstance(input_data, int):
                 pass
             else:
@@ -426,9 +431,8 @@ def get_subgraph_type(tensor):
     return tensor
 
 
-@register_backend
 @fake_tensor_unsupported
-def openvino_fx(subgraph, example_inputs):
+def openvino_fx(subgraph, example_inputs, options=None):
     global dont_use_4bit_nncf
     global dont_use_nncf
     global dont_use_quant
@@ -528,6 +532,8 @@ def openvino_fx(subgraph, example_inputs):
     for node in model.graph.nodes:
         if node.target == torch.ops.aten.mul_.Tensor:
             node.target = torch.ops.aten.mul.Tensor
+        elif node.target == torch.ops.aten._unsafe_index.Tensor:
+            node.target = torch.ops.aten.index.Tensor
     with devices.inference_context():
         model.eval()
     partitioner = Partitioner(options=None)
@@ -543,3 +549,7 @@ def openvino_fx(subgraph, example_inputs):
         res = execute(compiled_model, *args, executor="openvino", executor_parameters=executor_parameters, file_name=maybe_fs_cached_name)
         return res
     return _call
+
+
+if "openvino_fx" not in torch.compiler.list_backends():
+    register_backend(compiler_fn=openvino_fx, name="openvino_fx")