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//*****************************************************************************
// 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_layout.hpp"
#include "ngraph/file_util.hpp"
#include "ngraph/log.hpp"
#include "ngraph/runtime/backend.hpp"
#include "ngraph/runtime/tensor.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::Tensor> 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::Tensor> tv)
{
if (ngraph::element::from<T>() != tv->get_tensor_layout()->get_element_type())
{
throw std::invalid_argument("read_vector type must match Tensor 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::Tensor> tv);
template <typename T>
void write_vector(std::shared_ptr<ngraph::runtime::Tensor> 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, typename T1 = T>
std::vector<std::vector<T1>> execute(const std::shared_ptr<ngraph::Function>& function,
std::vector<std::vector<T>> args,
const std::string& backend_id)
{
auto backend = ngraph::runtime::Backend::create(backend_id);
auto parms = function->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::Tensor>> 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 = function->get_results();
std::vector<std::shared_ptr<ngraph::runtime::Tensor>> 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_with_validate(function, result_tensors, arg_tensors);
std::vector<std::vector<T1>> result_vectors;
for (auto rt : result_tensors)
{
result_vectors.push_back(read_vector<T1>(rt));
}
return result_vectors;
}