Fix copyright headers and sync with upstream

Author: devesh-047

src/bindings/python/src/openvino/frontend/pytorch/torchdynamo/execute.py

@@ -4,28 +4,19 @@
 
 # mypy: ignore-errors
 
-from copy import deepcopy
-from dataclasses import dataclass
-from functools import lru_cache
 from types import MappingProxyType
-from warnings import warn
 
 import torch
 import torch.overrides
 
 from torch.fx import GraphModule
-from torch.utils._pytree import tree_flatten, tree_map, tree_unflatten
+from torch.utils._pytree import tree_flatten
 
-from openvino.frontend import FrontEndManager
-from openvino.frontend.pytorch.fx_decoder import TorchFXPythonDecoder
-from openvino.frontend.pytorch.torchdynamo.partition import Partitioner
 from openvino.frontend.pytorch.torchdynamo.compile import openvino_compile
-from openvino import Core, Type, PartialShape
-from openvino.frontend.pytorch.torchdynamo.backend_utils import _get_cache_dir, _get_device, _get_aot_autograd
+from openvino.frontend.pytorch.torchdynamo.backend_utils import _get_aot_autograd
 
 from typing import Optional, Any
 
-from torch.fx.experimental.proxy_tensor import make_fx, wrapper_and_args_for_make_fx
 
 import logging
 logger = logging.getLogger(__name__)
@@ -65,7 +56,6 @@ def execute(
     raise ValueError(msg)
 
 
-import numpy as np
 
 
 def execute_cached(compiled_model, *args):
@@ -144,7 +134,7 @@ def __call__(self, *args):
                 partition_id=self.partition_id,
                 options=self.options,
             )
-            logger.info(f"OpenVINO partition {self.partition_id} executed successfully")
+            logger.debug(f"OpenVINO partition {self.partition_id} executed successfully")
         except Exception as e:
             logger.warning(
                 f"OpenVINO partition {self.partition_id} execution failed, falling back to PyTorch. Reason: {str(e)}"

src/bindings/python/src/openvino/frontend/pytorch/torchdynamo/partition.py

@@ -5,19 +5,15 @@
 # mypy: ignore-errors
 
 
+
 import torch
-from torch.nn import Module
 from torch.fx import GraphModule, Node
 from torch.fx.passes.infra.partitioner import CapabilityBasedPartitioner, Partition
 
-from torch.fx.experimental.proxy_tensor import DecompositionInterpreter
-from torch._decomp import decomposition_table
 from torch.fx.experimental.proxy_tensor import make_fx
-from torch.utils._pytree import tree_flatten, tree_map, tree_unflatten
 from openvino.frontend.pytorch.torchdynamo.op_support import OperatorSupport
 from openvino.frontend.pytorch.torchdynamo.backend_utils import _is_testing
 
-import typing as t
 import logging
 
 logger = logging.getLogger(__name__)
@@ -149,6 +145,8 @@ def make_partitions(self, graph_module: GraphModule, options) -> GraphModule:
         num_partitions = 0
         num_non_partition_nodes = 0
         for node in fused_graph_module.graph.nodes:
+            # NOTE: Currently relying on naming convention "fused_" to identify fused nodes.
+            # This may need to be replaced with a more robust mechanism in future.
             if node.op == "call_module" and "fused_" in node.name:
                 num_partitions += 1
             elif node.op != "placeholder" and node.op != "output":