b4a4c9110c
* Revise reference implementation for ReduceL1 operation * Revise reference implementation for ReduceL2 operation * Move op_eval tests to backend unit tests * Added minor changes * Replace CoordinateTransform for CoordinateTransformBasic * Added constant expression to set keep_dims as false * Add const qualifier to local variables * Use rank from host tensor to normalize axes
62 lines
2.3 KiB
C++
62 lines
2.3 KiB
C++
// Copyright (C) 2021 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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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 "util/all_close.hpp"
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#include "util/all_close_f.hpp"
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#include "util/test_control.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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static string s_manifest = "${MANIFEST}";
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NGRAPH_TEST(${BACKEND_NAME}, reduce_l2_one_axis_keep_dims)
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{
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auto data = make_shared<op::Parameter>(element::f32, Shape{3, 2, 2});
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auto axes = op::Constant::create(element::i32, Shape{1}, {2});
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auto reduce_l2 = make_shared<op::v4::ReduceL2>(data, axes, true);
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auto f = make_shared<Function>(OutputVector{reduce_l2}, ParameterVector{data});
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auto backend = runtime::Backend::create("${BACKEND_NAME}");
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std::vector<float> input{1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0};
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std::vector<float> expected_result{
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2.23606798, 5.0, 7.81024968, 10.63014581, 13.45362405, 16.2788206};
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auto data_tensor = backend->create_tensor(element::f32, Shape{3, 2, 2});
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copy_data(data_tensor, input);
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auto result_tensor = backend->create_tensor(element::f32, Shape{3, 2, 1});
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auto handle = backend->compile(f);
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handle->call_with_validate({result_tensor}, {data_tensor});
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EXPECT_TRUE(test::all_close_f((expected_result), read_vector<float>(result_tensor)));
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}
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NGRAPH_TEST(${BACKEND_NAME}, reduce_l2_one_axis_do_not_keep_dims)
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{
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auto data = make_shared<op::Parameter>(element::f32, Shape{3, 2, 2});
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auto axes = op::Constant::create(element::i32, Shape{1}, {2});
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auto reduce_l2 = make_shared<op::v4::ReduceL2>(data, axes, false);
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auto f = make_shared<Function>(OutputVector{reduce_l2}, ParameterVector{data});
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auto backend = runtime::Backend::create("${BACKEND_NAME}");
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std::vector<float> input{1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0};
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std::vector<float> expected_result{
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2.23606798, 5.0, 7.81024968, 10.63014581, 13.45362405, 16.2788206};
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auto data_tensor = backend->create_tensor(element::f32, Shape{3, 2, 2});
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copy_data(data_tensor, input);
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auto result_tensor = backend->create_tensor(element::f32, Shape{3, 2});
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auto handle = backend->compile(f);
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handle->call_with_validate({result_tensor}, {data_tensor});
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EXPECT_TRUE(test::all_close_f((expected_result), read_vector<float>(result_tensor)));
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}
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