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12daa4f663
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/65964 ghstack-source-id: 141425519 Test Plan: buck run xplat/caffe2:test_lite_interpreter Reviewed By: cccclai Differential Revision: D31326149 fbshipit-source-id: 8a599d92f3fa4e6c125100adb36d89592e71e547
37 lines
1.0 KiB
C++
37 lines
1.0 KiB
C++
#pragma once
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#include <vector>
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#include <ATen/core/ivalue.h>
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#include <ATen/core/operator_name.h>
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#include <torch/csrc/jit/runtime/instruction.h>
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namespace torch {
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namespace jit {
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namespace mobile {
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using Stack = std::vector<c10::IValue>;
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using DebugHandle = int64_t;
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class Function;
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// NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
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struct Code {
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std::vector<Instruction> instructions_;
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std::vector<DebugHandle> debug_handles_;
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std::vector<c10::OperatorName> op_names_;
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std::vector<std::function<void(Stack&)>> operators_;
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std::vector<c10::IValue> constants_;
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std::vector<c10::TypePtr> types_;
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// TODO After we actually export CALL instructions we can remove this.
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// We may need a two-stage importing scheme, where we firstly construct all
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// function objects, and then append referenced function pointers. This could
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// be done in parseMethods().
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std::vector<mobile::Function*> functions_;
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size_t register_size_; // Aggregated output size.
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};
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} // namespace mobile
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} // namespace jit
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} // namespace torch
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