faeaf045a9
* Moved FrameworkNode to nGraph * Moved graph comparator to ngraph test util * Fixed build * Try to fix centos * Fix export target * Moved engine utils to separate library * Removed ONNX util from common library * Fixed build * Fixed code style
83 lines
3.2 KiB
C++
83 lines
3.2 KiB
C++
// Copyright (C) 2018-2021 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#include "engines_util/execute_tools.hpp"
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#include "engines_util/random.hpp"
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#include "gtest/gtest.h"
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#include "ngraph/ngraph.hpp"
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#include "ngraph/runtime/tensor.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/ndarray.hpp"
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#include "util/test_control.hpp"
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using namespace std;
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using namespace ngraph;
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static string s_manifest = "${MANIFEST}";
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// This tests a backend's implementation of the two parameter version of create_tensor
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NGRAPH_TEST(${BACKEND_NAME}, create_tensor_1) {
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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::v1::Add>(A, B), ParameterVector{A, B});
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auto backend = runtime::Backend::create("${BACKEND_NAME}");
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// Create some tensors for input/output
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vector<float> av = {1, 2, 3, 4};
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vector<float> bv = {5, 6, 7, 8};
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shared_ptr<runtime::Tensor> a = backend->create_tensor(element::f32, shape);
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shared_ptr<runtime::Tensor> b = backend->create_tensor(element::f32, shape);
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copy_data(a, av);
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copy_data(b, bv);
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shared_ptr<runtime::Tensor> result = backend->create_tensor(element::f32, shape);
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auto handle = backend->compile(f);
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handle->call_with_validate({result}, {a, b});
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vector<float> expected = {6, 8, 10, 12};
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EXPECT_TRUE(test::all_close_f(read_vector<float>(result), expected, MIN_FLOAT_TOLERANCE_BITS));
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}
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NGRAPH_TEST(${BACKEND_NAME}, get_parameters_and_results) {
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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 C = make_shared<op::Parameter>(element::f32, shape);
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auto arg = make_shared<op::v1::Multiply>(make_shared<op::v1::Add>(A, B), C);
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auto f = make_shared<Function>(arg, ParameterVector{A, B, C});
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auto backend = runtime::Backend::create("${BACKEND_NAME}");
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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> c = 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(a, test::NDArray<float, 2>({{1, 2}, {3, 4}}).get_vector());
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copy_data(b, test::NDArray<float, 2>({{5, 6}, {7, 8}}).get_vector());
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copy_data(c, test::NDArray<float, 2>({{9, 10}, {11, 12}}).get_vector());
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auto handle = backend->compile(f);
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auto parameters = handle->get_parameters();
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auto results = handle->get_results();
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ASSERT_EQ(parameters.size(), 3);
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ASSERT_EQ(results.size(), 1);
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// This part can't be enabled until we force backends to make a copy of the source graph
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// auto func_parameters = f->get_parameters();
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// auto func_results = f->get_results();
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// for (size_t i = 0; i < 3; ++i)
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// {
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// EXPECT_NE(parameters[i], func_parameters[i]);
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// }
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// for (size_t i = 0; i < 1; ++i)
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// {
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// EXPECT_NE(results[i], func_results[i]);
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// }
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}
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