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Keep track of
ViewMeta
with symbolic inputs.
Fix: #125387 This PR helps keep track of whether an instantiated `ViewMeta` has symbolic values as input or not. This is used for checking whether we use the AOTAutograd `ViewMeta`-replay execution path, e.g. it doesn't support tensors that have `ViewMeta` with symbolic inputs. In summary, the changes are: - Add the field `ViewMeta::has_symbolic_inputs` and make it a required constructor parameter - Add the field `FunctionalTensorWrapper::is_symbolic_` and the method `FunctionalTensorWrapper::maybe_mark_symbolic` - Marks a `FunctionalTensorWrapper` as symbolic iff any of its `ViewMeta` have symbolic inputs - Add the plumbing of `FunctionalTensorWrapper::is_symbolic` to the Python API - Codegen the computation of `ViewMeta::has_symbolic_inputs` for each view operation - Use the AOTAutograd `ViewMeta`-replay path if: - `target_functional_tensor` is not `None`; and - `target_functional_tensor` is not symbolic (instead of using a functorch config) ghstack-source-id: 5acff826e8e26c407af1e9ea999846c83e2c7787 Pull Request resolved: #125876
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