93 lines
3.0 KiB
C++
93 lines
3.0 KiB
C++
//*****************************************************************************
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// Copyright 2017-2020 Intel Corporation
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//*****************************************************************************
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#include "gtest/gtest.h"
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#include "ngraph/ngraph.hpp"
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#include "ngraph/util.hpp"
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#include "runtime/backend.hpp"
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#include "util/all_close_f.hpp"
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#include "util/test_tools.hpp"
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using namespace std;
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using namespace ngraph;
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TEST(backend_api, registered_devices)
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{
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vector<string> devices = runtime::Backend::get_registered_devices();
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EXPECT_GE(devices.size(), 0);
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EXPECT_TRUE(find(devices.begin(), devices.end(), "INTERPRETER") != devices.end());
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}
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TEST(backend_api, invalid_name)
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{
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ASSERT_ANY_THROW(ngraph::runtime::Backend::create("COMPLETELY-BOGUS-NAME"));
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}
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TEST(backend_api, config)
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{
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auto backend = runtime::Backend::create("INTERPRETER");
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string error;
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string message = "hello";
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map<string, string> config = {{"test_echo", message}};
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EXPECT_TRUE(backend->set_config(config, error));
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EXPECT_STREQ(error.c_str(), message.c_str());
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EXPECT_FALSE(backend->set_config({}, error));
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EXPECT_STREQ(error.c_str(), "");
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}
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TEST(backend_api, DISABLED_config_unsupported)
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{
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auto backend = runtime::Backend::create("NOP");
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string error;
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string message = "hello";
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map<string, string> config = {{"test_echo", message}};
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EXPECT_FALSE(backend->set_config(config, error));
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EXPECT_FALSE(error == "");
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}
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#ifndef NGRAPH_JSON_DISABLE
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TEST(backend_api, save_load)
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{
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Shape shape{2, 2};
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auto A = make_shared<op::Parameter>(element::f32, shape);
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auto B = make_shared<op::Parameter>(element::f32, shape);
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auto f = make_shared<Function>(make_shared<op::Add>(A, B), ParameterVector{A, B});
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auto backend = runtime::Backend::create("INTERPRETER");
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// Create some tensors for input/output
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shared_ptr<runtime::Tensor> a = backend->create_tensor(element::f32, shape);
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shared_ptr<runtime::Tensor> b = backend->create_tensor(element::f32, shape);
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shared_ptr<runtime::Tensor> result = backend->create_tensor(element::f32, shape);
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copy_data<float>(a, {1.f, 2.f, 3.f, 4.f});
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copy_data<float>(b, {5.f, 6.f, 7.f, 8.f});
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stringstream file;
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{
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auto handle = backend->compile(f);
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handle->save(file);
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}
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{
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auto handle = backend->load(file);
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ASSERT_NE(handle, nullptr);
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handle->call_with_validate({result}, {a, b});
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EXPECT_TRUE(test::all_close_f(read_vector<float>(result), {6.f, 8.f, 10.f, 12.f}));
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}
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}
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#endif
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