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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
63 lines
1.9 KiB
C++
63 lines
1.9 KiB
C++
#include "function.h"
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#include "interpreter.h"
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#include <torch/csrc/jit/runtime/instruction.h>
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#include <torch/csrc/jit/runtime/vararg_functions.h>
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#include <ATen/core/op_registration/op_registration.h>
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namespace torch{
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namespace jit{
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char const * toString(OpCode op);
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namespace mobile {
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Function::Function(c10::QualifiedName name)
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: name_(name), code_(std::make_shared<Code>()) {}
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void Function::append_instruction(OpCode op, int X, int N) {
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TORCH_CHECK(isOpSupportedInMobile(op), toString(op),
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" is not supported in mobile module.");
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code_->instructions_.emplace_back(op, X, N);
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}
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bool Function::append_operator(const std::string& name,
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const std::string& overload_name) {
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// Keep the original opname in code_
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code_->op_names_.emplace_back(name, overload_name);
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auto opname = code_->op_names_.back();
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// Add "_" prefix to work around the double registration both of jit/generated
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// and here. TODO: remove it when we have separate build for lite interpreter.
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if (opname.name != "aten::Int") {
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opname.name = "_" + opname.name;
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}
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auto op = c10::Dispatcher::singleton().findSchema(opname);
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if (not op.has_value()) {
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return false;
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}
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// TODO: operator.h now does not depend on Node* so we can also look up operators from
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// that registry for use in mobile as a way to share implementations.
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auto fn = [op](Stack& stack) {
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c10::Dispatcher::singleton().callBoxed(*op, &stack);
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};
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code_->operators_.emplace_back(fn);
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return true;
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}
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void Function::append_constant(const c10::IValue& constant) {
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code_->constants_.push_back(constant);
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}
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void Function::append_type(const at::TypePtr& type) {
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code_->types_.push_back(type);
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}
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void Function::set_register_size(size_t size) {
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code_->register_size_ = size;
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}
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bool Function::run(Stack& stack) const {
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InterpreterState interp_state(code_);
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return interp_state.run(stack);
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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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