pytorch/binaries/dump_operator_names.cc

85 lines
2.8 KiB
C++

/**
* Copyright (c) 2016-present, Facebook, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <torch/csrc/jit/api/module.h>
#include <torch/csrc/jit/mobile/module.h>
#include <torch/csrc/jit/serialization/import.h>
#include <torch/csrc/jit/runtime/instruction.h>
#include <c10/util/Flags.h>
#include <fstream>
namespace torch {
namespace jit {
void dump_opnames(const Module& m, std::unordered_set<std::string>& opnames) {
auto methods = m.get_methods();
for (const auto& method : methods) {
const auto& func = method.function();
std::cout << "function name: " << func.name() << std::endl;
auto graph = toGraphFunction(func).graph()->copy();
torch::jit::Code code(graph, "");
for (size_t i = 0; i < code.instructions().size(); ++i) {
auto ins = code.instructions()[i];
auto node = code.instructions_source()[i];
if (ins.op == OpCode::OP) {
auto opname = node->schema().operator_name();
std::string namestr = opname.name;
if (!opname.overload_name.empty())
namestr += "." + opname.overload_name;
std::cout << " " << namestr << std::endl;
opnames.emplace(namestr);
}
}
}
for (const auto& sub_m : m.children()) {
std::cout << "sub module name: " << sub_m.type()->name()->qualifiedName() << std::endl;
dump_opnames(sub_m, opnames);
}
}
}
}
C10_DEFINE_string(model, "", "The given torch script model.");
C10_DEFINE_string(output, "", "The output yaml file of operator list.");
int main(int argc, char** argv) {
c10::SetUsageMessage(
"Dump operators in a script module and its sub modules.\n"
"Example usage:\n"
"./dump_operator_names"
" --model=<model_file>"
" --output=<output.yaml>");
if (!c10::ParseCommandLineFlags(&argc, &argv)) {
std::cerr << "Failed to parse command line flags!" << std::endl;
return 1;
}
CAFFE_ENFORCE_GE(FLAGS_model.size(), 0, "Model file must be specified.");
CAFFE_ENFORCE_GE(FLAGS_output.size(), 0, "Output yaml file must be specified.");
auto m = torch::jit::load(FLAGS_model);
std::unordered_set<std::string> opnames;
torch::jit::dump_opnames(m, opnames);
std::ofstream ofile(FLAGS_output);
std::cout << "-- Final List --" << std::endl;
for (const auto& name : opnames) {
std::cout << name << std::endl;
ofile << "- " << name << std::endl;
}
ofile.close();
}