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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
50 lines
1.2 KiB
C++
50 lines
1.2 KiB
C++
#pragma once
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#include <c10/core/MemoryFormat.h>
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#include <c10/core/SymIntArrayRef.h>
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#include <c10/core/TensorImpl.h>
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#include <c10/macros/Export.h>
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#include <c10/util/ArrayRef.h>
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#include <cstdint>
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namespace c10 {
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struct C10_API UndefinedTensorImpl final : public TensorImpl {
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public:
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// Without this, we get:
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// error: identifier "at::UndefinedTensorImpl::_singleton" is undefined in
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// device code
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// (ostensibly because the constexpr tricks MSVC into trying to compile this
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// function for device as well).
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#ifdef _WIN32
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static inline TensorImpl* singleton() {
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return &getInstance();
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}
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#else
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static constexpr inline TensorImpl* singleton() {
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return &_singleton;
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}
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#endif
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#ifdef DEBUG
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bool has_storage() const override;
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#endif
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void set_storage_offset(int64_t offset) override;
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protected:
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c10::SymBool sym_is_contiguous_custom(MemoryFormat format) const override;
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IntArrayRef strides_custom() const override;
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SymIntArrayRef sym_strides_custom() const override;
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private:
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UndefinedTensorImpl();
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#ifdef _WIN32
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static UndefinedTensorImpl& getInstance();
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#else
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static UndefinedTensorImpl _singleton;
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#endif
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const char* tensorimpl_type_name() const override;
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};
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} // namespace c10
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