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43b56b3814
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/75119 Add support for parsing Tensor constants like Double(4, 4) ... by initializing random tensors. This makes saving IR and then parsing it lossy, so I have it toggled as default not on, but is useful in cases like repro-ing Fusions with tensor constants post-freezing. cc Krovatkin Test Plan: Imported from OSS Reviewed By: ejguan Differential Revision: D35373999 Pulled By: eellison fbshipit-source-id: a5c8d9f93f23a7442258fc745ed6b6def330dca8 (cherry picked from commit 32dd6567522973563bd452bf486ed27b02e4e35c)
41 lines
1.1 KiB
C++
41 lines
1.1 KiB
C++
#pragma once
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#include <torch/csrc/Export.h>
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#include <string>
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#include <unordered_map>
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#include <c10/util/Optional.h>
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#include <torch/csrc/Export.h>
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namespace torch {
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namespace jit {
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struct Graph;
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struct Value;
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// \brief Parse IR from \p STR constructing the corresponding IR in\ GRAPH.
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// if parse_tensor_constants is true will construct empty tensors
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// for Tensor constants with random or unitialized contents, otherwise will
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// throw
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TORCH_API void parseIR(
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const std::string& str,
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torch::jit::Graph* graph,
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bool parse_tensor_constants = false);
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/** \brief Parse IR from \p STR constructing the corresponding IR in\ GRAPH.
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*
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* \p VMAP is filled with String to Value pairs allowing to index Values in the
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* newly created graph by their name in the original IR string.
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* if parse_tensor_constants is true will construct empty tensors
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* for Tensor constants with random or unitialized contents, otherwise will
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* throw
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*/
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TORCH_API void parseIR(
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const std::string& str,
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torch::jit::Graph* graph,
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std::unordered_map<std::string, Value*>& vmap,
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bool parse_tensor_constants = false);
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} // namespace jit
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} // namespace torch
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