/******************************************************************************* * Copyright 2017-2018 Intel Corporation * * 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. *******************************************************************************/ #pragma once #include <exception> #include <list> #include <memory> #include "ngraph/descriptor/layout/tensor_view_layout.hpp" #include "ngraph/file_util.hpp" #include "ngraph/log.hpp" #include "ngraph/runtime/backend.hpp" #include "ngraph/runtime/tensor_view.hpp" #include "ngraph/serializer.hpp" namespace ngraph { class Node; class Function; } bool validate_list(const std::list<std::shared_ptr<ngraph::Node>>& nodes); std::shared_ptr<ngraph::Function> make_test_graph(); template <typename T> void copy_data(std::shared_ptr<ngraph::runtime::TensorView> tv, const std::vector<T>& data) { size_t data_size = data.size() * sizeof(T); tv->write(data.data(), 0, data_size); } template <typename T> std::vector<T> read_vector(std::shared_ptr<ngraph::runtime::TensorView> tv) { if (ngraph::element::from<T>() != tv->get_tensor_view_layout()->get_element_type()) { throw std::invalid_argument("read_vector type must match TensorView type"); } size_t element_count = ngraph::shape_size(tv->get_shape()); size_t size = element_count * sizeof(T); std::vector<T> rc(element_count); tv->read(rc.data(), 0, size); return rc; } std::vector<float> read_float_vector(std::shared_ptr<ngraph::runtime::TensorView> tv); template <typename T> void write_vector(std::shared_ptr<ngraph::runtime::TensorView> tv, const std::vector<T>& values) { tv->write(values.data(), 0, values.size() * sizeof(T)); } template <typename T> std::vector<std::shared_ptr<T>> get_ops_of_type(std::shared_ptr<ngraph::Function> f) { std::vector<std::shared_ptr<T>> ops; for (auto op : f->get_ops()) { if (auto cop = std::dynamic_pointer_cast<T>(op)) { ops.push_back(cop); } } return ops; } template <typename T> size_t count_ops_of_type(std::shared_ptr<ngraph::Function> f) { size_t count = 0; for (auto op : f->get_ops()) { if (std::dynamic_pointer_cast<T>(op)) { count++; } } return count; } template <typename T> std::vector<std::vector<T>> execute(std::shared_ptr<ngraph::Function> f, std::vector<std::vector<T>> args, std::string cbackend) { auto backend = ngraph::runtime::Backend::create(cbackend); auto parms = f->get_parameters(); if (parms.size() != args.size()) { throw ngraph::ngraph_error("number of parameters and arguments don't match"); } std::vector<std::shared_ptr<ngraph::runtime::TensorView>> arg_tensors(args.size()); for (size_t i = 0; i < args.size(); i++) { auto t = backend->create_tensor(parms.at(i)->get_element_type(), parms.at(i)->get_shape()); copy_data(t, args.at(i)); arg_tensors.at(i) = t; } auto results = f->get_results(); std::vector<std::shared_ptr<ngraph::runtime::TensorView>> result_tensors(results.size()); for (size_t i = 0; i < results.size(); i++) { result_tensors.at(i) = backend->create_tensor(results.at(i)->get_element_type(), results.at(i)->get_shape()); } backend->call(f, result_tensors, arg_tensors); std::vector<std::vector<T>> result_vectors; for (auto rt : result_tensors) { result_vectors.push_back(read_vector<T>(rt)); } return result_vectors; }