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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/27546 Add files in csrc/jit/mobile folder to torch_core, as a first step to have light interpreter built in BUCK. Next the files will be independent of torch_core (T54912812) ghstack-source-id: 91523987 Test Plan: buck build -c pytorch.enable_rtti=1 -c project.ignore= -c ndk.app_platform=android-23 -c user.libcxx_cflags=-DFOLLY_USE_LIBCPP=1 -c user.libcxx_cxxflags=-DFOLLY_USE_LIBCPP=1 -c ndk.cxx_runtime=libcxx -c user.ndk_cxxflags=-g0 //xplat/experimental/pytorch/mobile:lite_predictorAndroid#android-armv7 && adb push buck-out/gen/xplat/experimental/pytorch/mobile/lite_predictorAndroid#android-armv7 /data/local/tmp/ In adb shell: data/local/tmp/lite_predictorAndroid\#android-armv7 add_it.bc buck build -c project.ignore= @//fbcode/mode/dev-asan //xplat/experimental/pytorch/mobile:lite_predictor Reviewed By: ljk53 Differential Revision: D17717547 fbshipit-source-id: 4c00a35eb231968d05d0d7b56bcfd5dc0258d4bb
37 lines
958 B
C++
37 lines
958 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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void append_operator(const std::string& name,
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const std::string& overload_name);
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void append_vararg_operator(const std::string& name,
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const std::string& overload_name);
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void build_vararg_operator_table();
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void append_constant(const c10::IValue& constant);
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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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