pytorch/torch/csrc/jit/mobile/code.h
Han Qi (qihqi) 3822a472ef Python function to extract information on mobile::Module from flatbuffer (#77624)
Summary:
Includes following refactor:
1. common loading on operator validation that is dup'd in pickle and
   flatbuffer loader moved to function.h/cpp
2. Allow loading of a function without wiring operator.

This function will be used to implement get_bundled_input and friends
for flatbuffer.

Test Plan: contbuild & OSS CI, see 69fa49f123

Reviewed By: cccclai

Differential Revision: D36348549

Pull Request resolved: https://github.com/pytorch/pytorch/pull/77624
Approved by: https://github.com/cccclai
2022-05-18 00:42:57 +00:00

40 lines
1.2 KiB
C++

#pragma once
#include <vector>
#include <ATen/core/ivalue.h>
#include <ATen/core/operator_name.h>
#include <torch/csrc/jit/runtime/instruction.h>
namespace torch {
namespace jit {
namespace mobile {
using Stack = std::vector<c10::IValue>;
using DebugHandle = int64_t;
class Function;
// NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
struct Code {
std::vector<Instruction> instructions_;
std::vector<DebugHandle> debug_handles_;
std::vector<c10::OperatorName> op_names_;
std::vector<int> operator_input_sizes_;
std::vector<std::function<void(Stack&)>> operators_;
std::vector<c10::IValue> constants_;
std::vector<c10::TypePtr> types_;
// TODO After we actually export CALL instructions we can remove this.
// We may need a two-stage importing scheme, where we firstly construct all
// function objects, and then append referenced function pointers. This could
// be done in parseMethods().
std::vector<mobile::Function*> functions_;
size_t register_size_ = 0; // Aggregated output size.
// initialized means operators_ array is filled with operators
bool initialized = false;
};
} // namespace mobile
} // namespace jit
} // namespace torch