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7cfd054075
Summary: When we compute contiguity for a tensor with dynamic shapes we first: 1) Try to compute it without guarding. 2) If all shapes hinted, compute it with potentially adding guards. 3) if any input is not hinted, compute it symbolically. sym_is_contiguous return a SymBool that is then either evaluated or guard_or_false can be called on it to avoid data dependent errors. ex: bool is_contiguous = input.sym_is_contiguous().guard_or_false(__FILE__, __LINE__); is_contiguous_or_false is a helper function that does that. In this PR I only handle default contiguity, will follow up with changes for other formats like channel_last . We use this patter in this PR for several locations to avoid DDEs. Test Plan: contbuild & OSS CI, Rollback Plan: Reviewed By: malfet Differential Revision: D77639021 Pull Request resolved: https://github.com/pytorch/pytorch/pull/157472 Approved by: https://github.com/aorenste |
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| .. | ||
| __init__.py | ||
| opinfo_schema.py | ||
| random_dag.py | ||
| test_converter.py | ||
| test_cpp_serdes.py | ||
| test_db.py | ||
| test_draft_export.py | ||
| test_experimental.py | ||
| test_export_strict.py | ||
| test_export_training_ir_to_run_decomp.py | ||
| test_export_with_inline_and_install.py | ||
| test_export.py | ||
| test_functionalized_assertions.py | ||
| test_hop.py | ||
| test_lift_unlift.py | ||
| test_package.py | ||
| test_pass_infra.py | ||
| test_passes.py | ||
| test_retraceability.py | ||
| test_schema.py | ||
| test_serdes.py | ||
| test_serialize.py | ||
| test_sparse.py | ||
| test_swap.py | ||
| test_tools.py | ||
| test_torchbind.py | ||
| test_tree_utils.py | ||
| test_unflatten_training_ir.py | ||
| test_unflatten.py | ||
| test_upgrader.py | ||
| test_verifier.py | ||
| testing.py | ||