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9fff8155c3
This PR applies clang-tidy readability checks to jit sources and all headers in the code base. `readability-redundant-inline-specifier` is suppressed because it incurs too many changes. `readability-redundant-inline-specifier` is used to detect redundant inline specifiers on function and variable declarations. There are many in-class method definitions that are marked inline. Pull Request resolved: https://github.com/pytorch/pytorch/pull/164652 Approved by: https://github.com/Skylion007
73 lines
2.0 KiB
C++
73 lines
2.0 KiB
C++
#pragma once
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#include <torch/csrc/jit/api/module.h>
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#include <torch/csrc/jit/ir/ir.h>
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namespace torch::jit {
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// Utility functions for PyTorch to ONNX conversion.
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static const int OPSET_VERSION_1 = 1;
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static const int OPSET_VERSION_9 = 9;
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static const int OPSET_VERSION_10 = 10;
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static const int OPSET_VERSION_11 = 11;
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static const int OPSET_VERSION_12 = 12;
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static const int OPSET_VERSION_13 = 13;
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static const int OPSET_VERSION_14 = 14;
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static const int OPSET_VERSION_15 = 15;
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static const int OPSET_VERSION_16 = 16;
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using ValueToParamPairMap = std::map<Value*, std::pair<std::string, IValue>>;
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using ParamMap = std::map<std::string, IValue>;
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TORCH_API void buildParamsMapFromValueToParamsMap(
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const ValueToParamPairMap& valsToParamsMap,
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ParamMap& paramsDict);
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TORCH_API ValueToParamPairMap
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buildValueToParamsMap(Block* b, const ParamMap& paramsDict);
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TORCH_API void eraseUnusedValuesFromMap(ValueToParamPairMap& valsToParamsMap);
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TORCH_API void eraseUnusedBlockInputs(Block* b);
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TORCH_API Node* addNodeToBlock(
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Block* block,
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Symbol kind,
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ArrayRef<Value*> inputs);
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TORCH_API Value* addInputToBlock(Block* block);
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TORCH_API std::optional<at::ScalarType> ONNXTypeToATenType(int32_t onnx_type);
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// Use int return type as no sable way exists to forward declare protobuf enum
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TORCH_API int ATenTypeToOnnxType(at::ScalarType at_type);
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TORCH_API void ONNXLintGraph(const std::shared_ptr<Graph>& graph);
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Node* createONNXUnsqueeze(
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Graph* graph,
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Node* n_to_insert_before,
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Value* input,
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int axis,
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int opset_version);
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Node* createONNXConstant(
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Graph* graph,
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Node* n_to_insert_before,
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at::Tensor value);
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bool isValidToTransformToONNXConcatNode(Node* lc_node);
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Node* transformToONNXConcatNode(
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Graph* graph,
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Node* lc_node,
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bool need_new_input,
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int opset_version);
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class ScalarTypeHashFunction {
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public:
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size_t operator()(const c10::ScalarType& type) const {
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return static_cast<size_t>(type);
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}
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};
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} // namespace torch::jit
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