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8c8edc66 - Decentralize and Improve key hash implementation for Dict variable tracker (#169204)

Decentralize and Improve key hash implementation for Dict variable tracker (#169204) Summary: Fixes https://github.com/pytorch/pytorch/issues/167956 ## Summary This PR decentralizes and improves the hash implementation for dictionary keys in Dynamo's ConstDictVariable tracker. Instead of maintaining a centralized list of hashable types and custom equality logic in _HashableTracker, we now delegate hashability checks, hash computation, and equality comparison to individual VariableTracker subclasses. ## Motivation The previous implementation had several issues: 1. Centralized logic: All hashability checks and hash computations were centralized in dicts.py, making it difficult to add support for new hashable types 2. Maintainability: Adding a new hashable type required modifying multiple locations in _HashableTracker (underlying_value, _eq_impl, and the is_hashable function) 3. Scattered knowledge: Type-specific hashing logic was separated from the type's own implementation 4. Limited extensibility: No clear protocol for VariableTracker subclasses to declare themselves as hashable ## Changes New Protocol Methods Added three new methods to the VariableTracker base class: 1. is_python_hashable(): Returns whether the underlying Python object is hashable 2. get_python_hash(): Computes the hash value for the underlying Python object 3. is_python_equal(other): Checks Python-level equality between two VariableTrackers The base implementation raises unimplemented() with helpful error messages, and subclasses override these methods as appropriate. ## Simplified _HashableTracker The _HashableTracker class in ConstDictVariable is now much simpler: - Removed underlying_value property (centralized type handling) - Removed _eq_impl static method (centralized equality logic) - Simplified __hash__() to delegate to vt.get_python_hash() - Simplified __eq__() to delegate to vt.is_python_equal() ## Decentralized Implementations Implemented the new protocol methods across relevant VariableTracker subclasses: - ConstantVariable, TensorVariable, TupleVariable, ListVariable - FrozensetVariable, FrozenDataClassVariable - BuiltinVariable, UserFunctionVariable, SkipFunctionVariable - FunctoolsPartialVariable, WeakRefVariable - NumpyVariable, NNModuleVariable, MethodWrapperVariable - TorchInGraphFunctionVariable, TorchHigherOrderOperatorVariable - TypingVariable, UserDefinedObjectVariable, UserDefinedClassVariable - SymNodeVariable, EnumVariable ## Enhanced Test Coverage Added 14 new test cases covering various hashable types as dictionary keys: - range, tuples, enums, frozensets - Typing constructs (e.g., typing.Union) - NumPy dtypes, method wrappers - Torch builtin functions, frozen dataclasses - Custom objects with __hash__ - Negative test for unhashable types (lists) ## Improved Error Messages Updated error messages to be more informative when encountering unhashable types, showing both the Python type and the VariableTracker type. X-link: https://github.com/pytorch/pytorch/pull/169204 Approved by: https://github.com/jansel Reviewed By: williamwen42, huydhn Differential Revision: D88129557 fbshipit-source-id: 7404f4ba39f557300c894d664dd64b0c0a1632bb