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https://github.com/zebrajr/pytorch.git
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17a5c67796
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/34072 This diff helps check all the ops not supported by lite_interpreter. Helpful mainly to find all the ops that need to be added instead of adding them one by one. Test Plan: buck run caffe2/binaries:lite_interpreter_model_load -- --model=<bytecode-model-path> Reviewed By: iseeyuan Differential Revision: D20194092 fbshipit-source-id: 0d596cd0204308027194af7ed738551d0c32a374
36 lines
847 B
C++
36 lines
847 B
C++
#pragma once
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#include <ATen/core/ivalue.h>
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//#include <aten/src/Aten/core/operator_name.h>
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#include <vector>
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namespace torch{
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namespace jit{
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using Stack = std::vector<c10::IValue>;
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enum OpCode : uint8_t;
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namespace mobile {
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struct Code;
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class Function{
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public:
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Function(c10::QualifiedName name);
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bool run(Stack& stack) const;
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const std::string& name() const;
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const c10::QualifiedName& qualname() const;
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void append_instruction(OpCode op, int X, int N);
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bool append_operator(const std::string& name,
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const std::string& overload_name);
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void append_constant(const c10::IValue& constant);
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void append_type(const c10::TypePtr& type);
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void set_register_size(size_t size);
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private:
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c10::QualifiedName name_;
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std::shared_ptr<Code> code_;
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};
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} // namespace mobile
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} // namespace torch
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} // namespace jit
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