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Fix: #141974 This PR makes `ViewMeta` sequence, present in functional tensors, serializable with pickle. In order to accomplish that, it makes `ViewMeta` an abstract class with overridable `forward` and `reverse` functions. In this context, each operation that once instanciated `ViewMeta`, should now create a new specialized class that inherits from `ViewMeta. Therefore, this PR also uses codegen for creating these specializations. In summary, these are the changes this PR introduces: - `ViewMeta` is turned into an abstract class (see _FunctionalStorageImpl.cpp_). `forward` and `reverse` are pure virtual functions that need to be implemented. `to_out_index` should be implemented by operations that might return more than 1 output. - New `ViewMeta` specializations for `resize_` and `_unsafe_view` are created (see _FunctionalizeFallbackKernel.h_). - New templates _ViewMetaClasses.{cpp,h}_ are created. They hold the declaration and definition of the `ViewMeta` specializations, which are automatically generated in the ATen codegen (see _gen.py_). - New `_functionalization` Python sub-module is created (see _Module.cpp_). It serves as namespace for the `ViewMeta` specializations and `InverseReturnMode` enum. - New template _ViewMetaClassesPythonBinding.cpp_ is created. It holds the automatically generated Python bindings for the `ViewMeta` specialization, which are generated in the torch codegen (see _generate_code.py_). Note that this PR makes use of codegen at 2 different moments: - ATen codegen (_gen.py_): generates the `ViewMeta` specialized classes. - Torch codegen (_generate_code.py_): generated the Python bindings for them. Pull Request resolved: https://github.com/pytorch/pytorch/pull/143712 Approved by: https://github.com/bdhirsh
17 lines
566 B
Python
17 lines
566 B
Python
from torch import Tensor
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from torch.types import _bool
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# Defined in torch/csrc/functionalization/Module.cpp
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class ViewMeta:
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has_symbolic_inputs: _bool
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# Returns the list of ViewMeta instances of the given functional tensor.
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#
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# Although we do have python bindings for their types, we won't
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# expose them here, since they should not be used by users.
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def get_view_meta_sequence(tensor: Tensor) -> list[ViewMeta]: ...
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# Applies the ViewMeta sequence on top of the given base.
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def apply_view_meta_sequence(base: Tensor, sequence: list[ViewMeta]) -> Tensor: ...
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