1189 lines
53 KiB
C++
1189 lines
53 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 "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.hpp"
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#include "util/all_close_f.hpp"
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#include "util/engine/test_engines.hpp"
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#include "util/known_element_types.hpp"
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#include "util/ndarray.hpp"
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#include "util/test_case.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 = "${MANIFEST}";
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using TestEngine = test::ENGINE_CLASS_NAME(${BACKEND_NAME});
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static void ConvolutionTest(const std::vector<float>& inputs,
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const Shape inputs_shape,
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const std::vector<float>& filters,
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const Shape filter_shape,
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const std::vector<float>& outputs,
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const Shape outputs_shape,
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const Strides& strides,
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const CoordinateDiff& padding,
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const Strides& dilations)
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{
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const CoordinateDiff pads_begin{padding};
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const CoordinateDiff pads_end{padding};
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const op::PadType auto_pad{op::PadType::EXPLICIT};
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auto inputs_param = make_shared<op::Parameter>(element::f32, inputs_shape);
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auto filters_param = make_shared<op::Parameter>(element::f32, filter_shape);
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auto conv = make_shared<op::v1::Convolution>(
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inputs_param, filters_param, strides, pads_begin, pads_end, dilations, auto_pad);
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auto f = make_shared<Function>(conv, ParameterVector{inputs_param, filters_param});
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auto test_case = test::TestCase<TestEngine>(f);
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test_case.add_input<float>(inputs);
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test_case.add_input<float>(filters);
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test_case.add_expected_output<float>(outputs_shape, outputs);
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test_case.run();
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}
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// --------------------- 1D convolution ------------------------------------------
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// clang-format off
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NGRAPH_TEST(${BACKEND_NAME}, convolution_1D_1batch_1channel)
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{
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const Strides strides{1};
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const CoordinateDiff padding{0};
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const Strides dilations{1};
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const Shape inputs_shape{1, 1, 6};
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const std::vector<float> inputs{1.0f, 3.0f, 3.0f, 0.0f, 1.0f, 2.0f};
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const Shape filter_shape{1, 1, 3};
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const std::vector<float> filters{2.0f, 0.0f, 1.0f};
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const Shape outputs_shape{1, 1, 4};
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const std::vector<float> outputs{5.0f, 6.0f, 7.0f, 2.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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NGRAPH_TEST(${BACKEND_NAME}, convolution_1D_1batch_1channel_padding)
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{
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const Strides strides{1};
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const CoordinateDiff padding{1};
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const Strides dilations{1};
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const Shape inputs_shape{1, 1, 4};
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const std::vector<float> inputs{1.0f, 3.0f, 3.0f, 0.0f};
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const Shape filter_shape{1, 1, 3};
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const std::vector<float> filters{2.0f, 0.0f, 1.0f};
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const Shape outputs_shape{1, 1, 4};
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const std::vector<float> outputs{3.0f, 5.0f, 6.0f, 6.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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NGRAPH_TEST(${BACKEND_NAME}, convolution_1D_1batch_1channel_stride)
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{
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const Strides strides{2};
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const CoordinateDiff padding{0};
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const Strides dilations{1};
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const Shape inputs_shape{1, 1, 5};
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const std::vector<float> inputs{1.0f, 3.0f, 3.0f, 0.0f, 1.0f};
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const Shape filter_shape{1, 1, 3};
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const std::vector<float> filters{2.0f, 0.0f, 1.0f};
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const Shape outputs_shape{1, 1, 2};
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const std::vector<float> outputs{5.0f, 7.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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NGRAPH_TEST(${BACKEND_NAME}, convolution_1D_1batch_1channel_dilation)
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{
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const Strides strides{1};
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const CoordinateDiff padding{0};
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const Strides dilations{2};
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const Shape inputs_shape{1, 1, 7};
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const std::vector<float> inputs{1.0f, 3.0f, 3.0f, 0.0f, 1.0f, 2.0f, 3.0f};
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const Shape filter_shape{1, 1, 3};
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const std::vector<float> filters{2.0f, 0.0f, 1.0f};
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const Shape outputs_shape{1, 1, 3};
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const std::vector<float> outputs{3.0f, 8.0f, 9.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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NGRAPH_TEST(${BACKEND_NAME}, convolution_1D_1batch_1channel_padding_stride_dilation)
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{
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const Strides strides{2};
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const CoordinateDiff padding{2};
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const Strides dilations{2};
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const Shape inputs_shape{1, 1, 7};
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const std::vector<float> inputs{1.0f, 3.0f, 3.0f, 0.0f, 1.0f, 2.0f, 3.0f};
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const Shape filter_shape{1, 1, 3};
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const std::vector<float> filters{2.0f, 0.0f, 1.0f};
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const Shape outputs_shape{1, 1, 4};
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const std::vector<float> outputs{3.0f, 3.0f, 9.0f, 2.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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NGRAPH_TEST(${BACKEND_NAME}, convolution_1D_1batch_2channel)
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{
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const Strides strides{1};
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const CoordinateDiff padding{0};
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const Strides dilations{1};
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const Shape inputs_shape{1, 2, 4};
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const std::vector<float> inputs{
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// channel 1
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1.0f, 3.0f, 2.0f, 1.0f,
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// channel 2
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2.0f, 2.0f, 3.0f, 1.0f};
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const Shape filter_shape{1, 2, 3};
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const std::vector<float> filters{
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// channel 1
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2.0f, 0.0f, 1.0f,
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// channel 2
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1.0f, 0.0f, 2.0f};
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const Shape outputs_shape{1, 1, 2};
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const std::vector<float> outputs{12.0f, 11.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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NGRAPH_TEST(${BACKEND_NAME}, convolution_1D_1batch_2filter)
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{
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const Strides strides{1};
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const CoordinateDiff padding{0};
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const Strides dilations{1};
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const Shape inputs_shape{1, 1, 4};
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const std::vector<float> inputs{1.0f, 3.0f, 2.0f, 1.0f};
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const Shape filter_shape{2, 1, 3};
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const std::vector<float> filters{
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// filter 1
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2.0f, 0.0f, 1.0f,
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// filter 2
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1.0f, 0.0f, 2.0f};
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const Shape outputs_shape{1, 2, 2};
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const std::vector<float> outputs{
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// channel 1
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4.0f, 7.0f,
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// channel 2
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5.0f, 5.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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NGRAPH_TEST(${BACKEND_NAME}, convolution_1D_2batch_1channel)
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{
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const Strides strides{1};
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const CoordinateDiff padding{0};
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const Strides dilations{1};
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const Shape inputs_shape{2, 1, 4};
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const std::vector<float> inputs{
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// batch 1
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1.0f, 3.0f, 2.0f, 1.0f,
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// batch 2
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2.0f, 2.0f, 3.0f, 1.0f};
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const Shape filter_shape{1, 1, 3};
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const std::vector<float> filters{2.0f, 0.0f, 1.0f};
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const Shape outputs_shape{2, 1, 2};
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const std::vector<float> outputs{
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// batch 1
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4.0f, 7.0f,
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// batch 2
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7.0f, 5.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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// --------------------- 2D convolution ------------------------------------------
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NGRAPH_TEST(${BACKEND_NAME}, convolution_2D_1batch_1channel)
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{
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const Strides strides{1, 1};
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const CoordinateDiff padding{0, 0};
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const Strides dilations{1, 1};
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const Shape inputs_shape{1, 1, 4, 4};
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const std::vector<float> inputs{1.0f, 3.0f, 5.0f, 7.0f,
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7.0f, 5.0f, 3.0f, 1.0f,
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2.0f, 4.0f, 6.0f, 8.0f,
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8.0f, 6.0f, 4.0f, 2.0f};
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const Shape filter_shape{1, 1, 3, 3};
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const std::vector<float> filters{1.0f, 2.0f, 3.0f,
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0.0f, 1.0f, 0.0f,
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3.0f, 2.0f, 1.0f};
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const Shape outputs_shape{1, 1, 2, 2};
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const std::vector<float> outputs{47.0f, 69.0f,
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70.0f, 48.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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NGRAPH_TEST(${BACKEND_NAME}, convolution_2D_1batch_1channel_padding)
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{
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const Strides strides{1, 1};
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const CoordinateDiff padding{1, 1};
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const Strides dilations{1, 1};
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const Shape inputs_shape{1, 1, 4, 4};
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const std::vector<float> inputs{1.0f, 3.0f, 5.0f, 7.0f,
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7.0f, 5.0f, 3.0f, 1.0f,
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2.0f, 4.0f, 6.0f, 8.0f,
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8.0f, 6.0f, 4.0f, 2.0f};
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const Shape filter_shape{1, 1, 3, 3};
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const std::vector<float> filters{1.0f, 2.0f, 3.0f,
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0.0f, 1.0f, 0.0f,
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2.0f, 1.0f, 2.0f};
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const Shape outputs_shape{1, 1, 4, 4};
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const std::vector<float> outputs{18.0f, 28.0f, 20.0f, 14.0f,
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28.0f, 47.0f, 67.0f, 40.0f,
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51.0f, 60.0f, 40.0f, 23.0f,
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24.0f, 34.0f, 44.0f, 24.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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NGRAPH_TEST(${BACKEND_NAME}, convolution_2D_1batch_1channel_stride)
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{
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const Strides strides{2, 2};
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const CoordinateDiff padding{0, 0};
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const Strides dilations{1, 1};
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const Shape inputs_shape{1, 1, 5, 5};
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const std::vector<float> inputs{1.0f, 3.0f, 5.0f, 7.0f, 9.0f,
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7.0f, 5.0f, 3.0f, 1.0f, 0.0f,
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2.0f, 4.0f, 6.0f, 8.0f, 10.0f,
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8.0f, 6.0f, 4.0f, 2.0f, 0.0f,
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2.0f, 4.0f, 6.0f, 8.0f, 10.0f};
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const Shape filter_shape{1, 1, 3, 3};
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const std::vector<float> filters{1.0f, 2.0f, 3.0f,
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1.0f, 1.0f, 1.0f,
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3.0f, 2.0f, 1.0f};
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const Shape outputs_shape{1, 1, 2, 2};
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const std::vector<float> outputs{57.0f, 94.0f,
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66.0f, 102.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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NGRAPH_TEST(${BACKEND_NAME}, convolution_2D_1batch_1channel_dilation)
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{
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const Strides strides{1, 1};
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const CoordinateDiff padding{0, 0};
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const Strides dilations{2, 2};
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const Shape inputs_shape{1, 1, 7, 7};
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const std::vector<float> inputs{1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 13.0f,
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7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
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2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
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8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f,
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2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
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7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
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8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f};
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const Shape filter_shape{1, 1, 3, 3};
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const std::vector<float> filters{1.0f, 2.0f, 3.0f,
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1.0f, 1.0f, 0.0f,
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3.0f, 1.0f, 2.0f};
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const Shape outputs_shape{1, 1, 3, 3};
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const std::vector<float> outputs{78.0f, 106.0f, 134.0f,
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44.0f, 16.0f, -12.0f,
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80.0f, 84.0f, 88.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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NGRAPH_TEST(${BACKEND_NAME}, convolution_2D_1batch_1channel_padding_strides_dilation)
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{
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const Strides strides{2, 2};
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const CoordinateDiff padding{2, 2};
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const Strides dilations{2, 2};
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const Shape inputs_shape{1, 1, 7, 7};
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const std::vector<float> inputs{1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 13.0f,
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7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
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2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
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8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f,
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2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
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7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
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8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f};
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const Shape filter_shape{1, 1, 3, 3};
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const std::vector<float> filters{1.0f, 2.0f, 3.0f,
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1.0f, 1.0f, 0.0f,
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3.0f, 1.0f, 2.0f};
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const Shape outputs_shape{1, 1, 4, 4};
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const std::vector<float> outputs{15.0f, 38.0f, 70.0f, 66.0f,
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33.0f, 78.0f, 134.0f, 103.0f,
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40.0f, 80.0f, 88.0f, 58.0f,
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30.0f, 56.0f, 72.0f, 34.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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NGRAPH_TEST(${BACKEND_NAME}, convolution_2D_1batch_2channel)
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{
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const Strides strides{1, 1};
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const CoordinateDiff padding{0, 0};
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const Strides dilations{1, 1};
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const Shape inputs_shape{1, 2, 4, 4};
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const std::vector<float> inputs{
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// channel 1
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1.0f, 3.0f, 5.0f, 7.0f,
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7.0f, 5.0f, 3.0f, 1.0f,
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2.0f, 4.0f, 6.0f, 8.0f,
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8.0f, 6.0f, 4.0f, 2.0f,
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// channel 2
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-1.0f, 3.0f, -5.0f, 7.0f,
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7.0f, -5.0f, 3.0f, -1.0f,
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-2.0f, 4.0f, -6.0f, 8.0f,
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8.0f, -6.0f, 4.0f, -2.0f};
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const Shape filter_shape{1, 2, 3, 3};
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const std::vector<float> filters{
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// channel 1
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5.0f, 3.0f, 5.0f,
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1.0f, 3.0f, 1.0f,
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4.0f, 2.0f, 4.0f,
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// channel 2
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-5.0f, 3.0f, 5.0f,
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1.0f, -3.0f, 1.0f,
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4.0f, 2.0f, -4.0f};
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const Shape outputs_shape{1, 1, 2, 2};
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const std::vector<float> outputs{142.0f, 102.0f,
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94.0f, 160.0f};
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ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
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strides, padding, dilations);
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}
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NGRAPH_TEST(${BACKEND_NAME}, convolution_2D_1batch_2filter)
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{
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const Strides strides{1, 1};
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const CoordinateDiff padding{0, 0};
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const Strides dilations{1, 1};
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const Shape inputs_shape{1, 1, 4, 4};
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const std::vector<float> inputs{
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1.0f, 3.0f, 5.0f, 7.0f,
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7.0f, 5.0f, 3.0f, 1.0f,
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2.0f, 4.0f, 6.0f, 8.0f,
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8.0f, 6.0f, 4.0f, 2.0f};
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const Shape filter_shape{2, 1, 3, 3};
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const std::vector<float> filters{
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// channel 1
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5.0f, 3.0f, 5.0f,
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1.0f, 3.0f, 1.0f,
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4.0f, 2.0f, 4.0f,
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// channel 2
|
|
-5.0f, 3.0f, 5.0f,
|
|
1.0f, -3.0f, 1.0f,
|
|
4.0f, 2.0f, -4.0f};
|
|
|
|
const Shape outputs_shape{1, 2, 2, 2};
|
|
const std::vector<float> outputs{
|
|
// channel 1
|
|
104.0f, 140.0f,
|
|
145.0f, 109.0f,
|
|
// channel 2
|
|
16.0f, 28.0f,
|
|
19.0f, 7.0f};
|
|
|
|
ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
|
|
strides, padding, dilations);
|
|
}
|
|
|
|
NGRAPH_TEST(${BACKEND_NAME}, convolution_2D_2batch_1channel)
|
|
{
|
|
const Strides strides{1, 1};
|
|
const CoordinateDiff padding{0, 0};
|
|
const Strides dilations{1, 1};
|
|
|
|
const Shape inputs_shape{2, 1, 4, 4};
|
|
const std::vector<float> inputs{
|
|
// batch 1
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// batch 2
|
|
-1.0f, 3.0f, 2.0f, -1.0f,
|
|
1.0f, 3.0f, -3.0f, 1.0f,
|
|
-2.0f, -1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, -3.0f};
|
|
|
|
const Shape filter_shape{1, 1, 3, 3};
|
|
const std::vector<float> filters{-5.0f, 3.0f, 5.0f,
|
|
1.0f, -3.0f, 1.0f,
|
|
4.0f, 2.0f, -4.0f};
|
|
|
|
const Shape outputs_shape{2, 1, 2, 2};
|
|
const std::vector<float> outputs{
|
|
// batch 1
|
|
15.0f, -15.0f,
|
|
23.0f, 2.0f,
|
|
// batch 2
|
|
-1.0f, -15.0f,
|
|
-5.0f, 6.0f};
|
|
|
|
|
|
ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
|
|
strides, padding, dilations);
|
|
}
|
|
|
|
// --------------------- 3D convolution ------------------------------------------
|
|
NGRAPH_TEST(${BACKEND_NAME}, convolution_3D_1batch_1channel)
|
|
{
|
|
const Strides strides{1, 1, 1};
|
|
const CoordinateDiff padding{0, 0, 0};
|
|
const Strides dilations{1, 1, 1};
|
|
|
|
const Shape inputs_shape{1, 1, 4, 4, 4};
|
|
const std::vector<float> inputs{
|
|
// depth: 1
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 2
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 3
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 4
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f
|
|
};
|
|
|
|
const Shape filter_shape{1, 1, 3, 3, 3};
|
|
const std::vector<float> filters{
|
|
// depth: 1
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 2
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 3
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f};
|
|
|
|
const Shape outputs_shape{1, 1, 2, 2, 2};
|
|
const std::vector<float> outputs{
|
|
// depth: 1
|
|
69.0f, 66.0f,
|
|
93.0f, 78.0f,
|
|
// depth: 2
|
|
69.0f, 66.0f,
|
|
93.0f, 78.0f};
|
|
|
|
ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
|
|
strides, padding, dilations);
|
|
}
|
|
|
|
NGRAPH_TEST(${BACKEND_NAME}, convolution_3D_1batch_1channel_padding)
|
|
{
|
|
const Strides strides{1, 1, 1};
|
|
const CoordinateDiff padding{1, 1, 1};
|
|
const Strides dilations{1, 1, 1};
|
|
|
|
const Shape inputs_shape{1, 1, 4, 4, 4};
|
|
const std::vector<float> inputs{
|
|
// depth: 1
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 2
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 3
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 4
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f
|
|
};
|
|
|
|
const Shape filter_shape{1, 1, 3, 3, 3};
|
|
const std::vector<float> filters{
|
|
// depth: 1
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 2
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 3
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f};
|
|
|
|
const Shape outputs_shape{1, 1, 4, 4, 4};
|
|
const std::vector<float> outputs{
|
|
// depth: 1
|
|
16.0f, 28.0f, 26.0f, 16.0f,
|
|
32.0f, 46.0f, 44.0f, 20.0f,
|
|
40.0f, 62.0f, 52.0f, 34.0f,
|
|
20.0f, 18.0f, 30.0f, 20.0f,
|
|
// depth: 2
|
|
24.0f, 42.0f, 39.0f, 24.0f,
|
|
48.0f, 69.0f, 66.0f, 30.0f,
|
|
60.0f, 93.0f, 78.0f, 51.0f,
|
|
30.0f, 27.0f, 45.0f, 30.0f,
|
|
// depth: 3
|
|
24.0f, 42.0f, 39.0f, 24.0f,
|
|
48.0f, 69.0f, 66.0f, 30.0f,
|
|
60.0f, 93.0f, 78.0f, 51.0f,
|
|
30.0f, 27.0f, 45.0f, 30.0f,
|
|
// depth: 4
|
|
16.0f, 28.0f, 26.0f, 16.0f,
|
|
32.0f, 46.0f, 44.0f, 20.0f,
|
|
40.0f, 62.0f, 52.0f, 34.0f,
|
|
20.0f, 18.0f, 30.0f, 20.0f,};
|
|
|
|
ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
|
|
strides, padding, dilations);
|
|
}
|
|
|
|
NGRAPH_TEST(${BACKEND_NAME}, convolution_3D_1batch_1channel_stride)
|
|
{
|
|
const Strides strides{2, 2, 2};
|
|
const CoordinateDiff padding{0, 0, 0};
|
|
const Strides dilations{1, 1, 1};
|
|
|
|
const Shape inputs_shape{1, 1, 5, 5, 5};
|
|
const std::vector<float> inputs{
|
|
// depth: 1
|
|
1.0f, 3.0f, 2.0f, 1.0f, 2.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f, 2.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f, 2.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 2.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 2.0f,
|
|
// depth: 2
|
|
1.0f, 3.0f, 2.0f, 1.0f, 2.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f, 2.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f, 2.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 2.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 2.0f,
|
|
// depth: 3
|
|
1.0f, 3.0f, 2.0f, 1.0f, 2.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f, 2.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f, 2.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 2.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 2.0f,
|
|
// depth: 4
|
|
1.0f, 3.0f, 2.0f, 1.0f, 2.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f, 2.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f, 2.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 2.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 2.0f,
|
|
// depth: 5
|
|
1.0f, 3.0f, 2.0f, 1.0f, 2.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f, 2.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f, 2.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 2.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 2.0f,
|
|
};
|
|
|
|
const Shape filter_shape{1, 1, 3, 3, 3};
|
|
const std::vector<float> filters{
|
|
// depth: 1
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 2
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 3
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f};
|
|
|
|
const Shape outputs_shape{1, 1, 2, 2, 2};
|
|
const std::vector<float> outputs{
|
|
// depth: 1
|
|
69.0f, 60.0f,
|
|
69.0f, 87.0f,
|
|
// depth: 2
|
|
69.0f, 60.0f,
|
|
69.0f, 87.0f};
|
|
|
|
ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
|
|
strides, padding, dilations);
|
|
}
|
|
|
|
NGRAPH_TEST(${BACKEND_NAME}, convolution_3D_1batch_1channel_padding_strides_dilation)
|
|
{
|
|
const Strides strides{2, 2, 2};
|
|
const CoordinateDiff padding{2, 2, 2};
|
|
const Strides dilations{2, 2, 2};
|
|
|
|
const Shape inputs_shape{1, 1, 7, 7, 7};
|
|
const std::vector<float> inputs{
|
|
// depth: 1
|
|
1.0f, 3.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
// depth: 2
|
|
1.0f, 3.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
// depth: 3
|
|
1.0f, 3.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
// depth: 4
|
|
1.0f, 3.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
// depth: 5
|
|
1.0f, 3.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
// depth: 6
|
|
1.0f, 3.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
// depth: 7
|
|
1.0f, 3.0f, 2.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f, 1.0f, 2.0f, 3.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f, 1.0f, 2.0f, 3.0f,
|
|
};
|
|
|
|
const Shape filter_shape{1, 1, 3, 3, 3};
|
|
const std::vector<float> filters{
|
|
// depth: 1
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 2
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 3
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f};
|
|
|
|
const Shape outputs_shape{1, 1, 4, 4, 4};
|
|
const std::vector<float> outputs{
|
|
// depth: 1
|
|
10.0f, 18.0f, 20.0f, 16.0f,
|
|
38.0f, 40.0f, 54.0f, 30.0f,
|
|
38.0f, 42.0f, 52.0f, 30.0f,
|
|
36.0f, 30.0f, 30.0f, 20.0f,
|
|
// depth: 2
|
|
15.0f, 27.0f, 30.0f, 24.0f,
|
|
57.0f, 60.0f, 81.0f, 45.0f,
|
|
57.0f, 63.0f, 78.0f, 45.0f,
|
|
54.0f, 45.0f, 45.0f, 30.0f,
|
|
// depth: 3
|
|
15.0f, 27.0f, 30.0f, 24.0f,
|
|
57.0f, 60.0f, 81.0f, 45.0f,
|
|
57.0f, 63.0f, 78.0f, 45.0f,
|
|
54.0f, 45.0f, 45.0f, 30.0f,
|
|
// depth: 4
|
|
10.0f, 18.0f, 20.0f, 16.0f,
|
|
38.0f, 40.0f, 54.0f, 30.0f,
|
|
38.0f, 42.0f, 52.0f, 30.0f,
|
|
36.0f, 30.0f, 30.0f, 20.0f};
|
|
|
|
ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
|
|
strides, padding, dilations);
|
|
}
|
|
|
|
NGRAPH_TEST(${BACKEND_NAME}, convolution_3D_1batch_2channel)
|
|
{
|
|
const Strides strides{1, 1, 1};
|
|
const CoordinateDiff padding{0, 0, 0};
|
|
const Strides dilations{1, 1, 1};
|
|
|
|
const Shape inputs_shape{1, 2, 4, 4, 4};
|
|
const std::vector<float> inputs{
|
|
// -- channel 1 --
|
|
// depth: 1
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 2
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 3
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 4
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// -- channel 2 --
|
|
// depth: 1
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 2
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 3
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 4
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f
|
|
};
|
|
|
|
const Shape filter_shape{1, 2, 3, 3, 3};
|
|
const std::vector<float> filters{
|
|
// -- channel 1 --
|
|
// depth: 1
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 2
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 3
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// -- channel 2 --
|
|
// depth: 1
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 2
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 3
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f
|
|
};
|
|
|
|
const Shape outputs_shape{1, 1, 2, 2, 2};
|
|
const std::vector<float> outputs{
|
|
// depth: 1
|
|
138.0f, 132.0f,
|
|
186.0f, 156.0f,
|
|
// depth: 2
|
|
138.0f, 132.0f,
|
|
186.0f, 156.0f};
|
|
|
|
ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
|
|
strides, padding, dilations);
|
|
}
|
|
|
|
NGRAPH_TEST(${BACKEND_NAME}, convolution_3D_1batch_2filter)
|
|
{
|
|
const Strides strides{1, 1, 1};
|
|
const CoordinateDiff padding{0, 0, 0};
|
|
const Strides dilations{1, 1, 1};
|
|
|
|
const Shape inputs_shape{1, 1, 4, 4, 4};
|
|
const std::vector<float> inputs{
|
|
// depth: 1
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 2
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 3
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 4
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f};
|
|
|
|
const Shape filter_shape{2, 1, 3, 3, 3};
|
|
const std::vector<float> filters{
|
|
// -- filter 1 --
|
|
// depth: 1
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 2
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 3
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// -- filter 2 --
|
|
// depth: 1
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 2
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 3
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f
|
|
};
|
|
|
|
const Shape outputs_shape{1, 2, 2, 2, 2};
|
|
const std::vector<float> outputs{
|
|
// -- out 1 --
|
|
// depth: 1
|
|
69.0f, 66.0f,
|
|
93.0f, 78.0f,
|
|
// depth: 2
|
|
69.0f, 66.0f,
|
|
93.0f, 78.0f,
|
|
// -- out 2 --
|
|
// depth: 1
|
|
69.0f, 66.0f,
|
|
93.0f, 78.0f,
|
|
// depth: 2
|
|
69.0f, 66.0f,
|
|
93.0f, 78.0f};
|
|
|
|
ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
|
|
strides, padding, dilations);
|
|
}
|
|
|
|
NGRAPH_TEST(${BACKEND_NAME}, convolution_3D_2batch_1channel)
|
|
{
|
|
const Strides strides{1, 1, 1};
|
|
const CoordinateDiff padding{0, 0, 0};
|
|
const Strides dilations{1, 1, 1};
|
|
|
|
const Shape inputs_shape{2, 1, 4, 4, 4};
|
|
const std::vector<float> inputs{
|
|
// -- batch 1 --
|
|
// depth: 1
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 2
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 3
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 4
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// -- batch 2 --
|
|
// depth: 1
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 2
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 3
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f,
|
|
// depth: 4
|
|
1.0f, 3.0f, 2.0f, 1.0f,
|
|
1.0f, 3.0f, 3.0f, 1.0f,
|
|
2.0f, 1.0f, 1.0f, 3.0f,
|
|
3.0f, 2.0f, 3.0f, 3.0f};
|
|
|
|
const Shape filter_shape{1, 1, 3, 3, 3};
|
|
const std::vector<float> filters{
|
|
// depth: 1
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 2
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f,
|
|
// depth: 3
|
|
1.0f, 2.0f, 3.0f,
|
|
0.0f, 1.0f, 0.0f,
|
|
2.0f, 1.0f, 2.0f};
|
|
|
|
const Shape outputs_shape{2, 1, 2, 2, 2};
|
|
const std::vector<float> outputs{
|
|
// -- batch 1 --
|
|
// depth: 1
|
|
69.0f, 66.0f,
|
|
93.0f, 78.0f,
|
|
// depth: 2
|
|
69.0f, 66.0f,
|
|
93.0f, 78.0f,
|
|
// -- batch 2 --
|
|
// depth: 1
|
|
69.0f, 66.0f,
|
|
93.0f, 78.0f,
|
|
// depth: 2
|
|
69.0f, 66.0f,
|
|
93.0f, 78.0f};
|
|
|
|
ConvolutionTest(inputs, inputs_shape, filters, filter_shape, outputs, outputs_shape,
|
|
strides, padding, dilations);
|
|
}
|
|
// ---------------------- other tests ------------------------------------------
|
|
// clang-format on
|
|
NGRAPH_TEST(${BACKEND_NAME}, convolution_outlining)
|
|
{
|
|
Shape shape_a{1, 2, 2, 2};
|
|
auto A = make_shared<op::Parameter>(element::f32, shape_a);
|
|
Shape shape_b{2, 2, 1, 1};
|
|
auto B = make_shared<op::Parameter>(element::f32, shape_b);
|
|
Shape shape_r{1, 2, 2, 2};
|
|
auto conv1 = make_shared<op::v1::Convolution>(
|
|
A, B, Strides{1, 1}, CoordinateDiff{0, 0}, CoordinateDiff{0, 0}, Strides{1, 1});
|
|
auto conv2 = make_shared<op::v1::Convolution>(
|
|
conv1, B, Strides{1, 1}, CoordinateDiff{0, 0}, CoordinateDiff{0, 0}, Strides{1, 1});
|
|
auto f = make_shared<Function>(conv2, ParameterVector{A, B});
|
|
|
|
auto backend = runtime::Backend::create("${BACKEND_NAME}");
|
|
|
|
// Create some tensors for input/output
|
|
auto a = backend->create_tensor(element::f32, shape_a);
|
|
copy_data(a, vector<float>{1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f});
|
|
auto b = backend->create_tensor(element::f32, shape_b);
|
|
copy_data(b, vector<float>{1.0f, 1.0f, 1.0f, 1.0f});
|
|
auto result = backend->create_tensor(element::f32, shape_r);
|
|
|
|
vector<float> expected_result{4.0f, 4.0f, 4.0f, 4.0f, 4.0f, 4.0f, 4.0f, 4.0f};
|
|
|
|
auto handle = backend->compile(f);
|
|
handle->call_with_validate({result}, {a, b});
|
|
EXPECT_TRUE(test::all_close_f(vector<float>{expected_result}, read_vector<float>(result)));
|
|
}
|
|
|
|
NGRAPH_TEST(${BACKEND_NAME}, convolution_simple)
|
|
{
|
|
Shape shape_a{1, 2, 2, 2};
|
|
auto A = make_shared<op::Parameter>(element::f32, shape_a);
|
|
Shape shape_b{2, 2, 1, 1};
|
|
auto B = make_shared<op::Parameter>(element::f32, shape_b);
|
|
Shape shape_r{1, 2, 2, 2};
|
|
auto conv1 = make_shared<op::v1::Convolution>(
|
|
A, B, Strides{1, 1}, CoordinateDiff{0, 0}, CoordinateDiff{0, 0}, Strides{1, 1});
|
|
|
|
auto f = make_shared<Function>(conv1, ParameterVector{A, B});
|
|
|
|
auto backend = runtime::Backend::create("${BACKEND_NAME}");
|
|
|
|
// Create some tensors for input/output
|
|
auto a = backend->create_tensor(element::f32, shape_a);
|
|
copy_data(a, vector<float>{1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f});
|
|
auto b = backend->create_tensor(element::f32, shape_b);
|
|
copy_data(b, vector<float>{3.0f, 3.0f, 3.0f, 3.0f});
|
|
auto result = backend->create_tensor(element::f32, shape_r);
|
|
|
|
vector<float> expected_result{18.0f, 24.0f, 30.0f, 36.0f, 18.0f, 24.0f, 30.0f, 36.0f};
|
|
|
|
auto handle = backend->compile(f);
|
|
handle->call_with_validate({result}, {a, b});
|
|
EXPECT_TRUE(test::all_close_f(vector<float>{expected_result}, read_vector<float>(result)));
|
|
}
|
|
|
|
NGRAPH_TEST(${BACKEND_NAME}, convolution_simple_padding)
|
|
{
|
|
Shape shape_a{1, 1, 2, 2};
|
|
auto A = make_shared<op::Parameter>(element::f32, shape_a);
|
|
Shape shape_b{1, 1, 1, 1};
|
|
auto B = make_shared<op::Parameter>(element::f32, shape_b);
|
|
Shape shape_r{1, 1, 5, 5};
|
|
auto conv1 = make_shared<op::v1::Convolution>(
|
|
A, B, Strides{1, 1}, CoordinateDiff{1, 1}, CoordinateDiff{2, 2}, Strides{1, 1});
|
|
|
|
auto f = make_shared<Function>(conv1, ParameterVector{A, B});
|
|
|
|
auto backend = runtime::Backend::create("${BACKEND_NAME}");
|
|
|
|
// Create some tensors for input/output
|
|
auto a = backend->create_tensor(element::f32, shape_a);
|
|
copy_data(a, vector<float>{1.0f, 2.0f, 3.0f, 4.0f});
|
|
auto b = backend->create_tensor(element::f32, shape_b);
|
|
copy_data(b, vector<float>{2.0f});
|
|
auto result = backend->create_tensor(element::f32, shape_r);
|
|
// clang-format off
|
|
vector<float> expected_result{0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
|
|
0.0f, 2.0f, 4.0f, 0.0f, 0.0f,
|
|
0.0f, 6.0f, 8.0f, 0.0f, 0.0f,
|
|
0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
|
|
0.0f, 0.0f, 0.0f, 0.0f, 0.0f};
|
|
// clang-format on
|
|
auto handle = backend->compile(f);
|
|
handle->call_with_validate({result}, {a, b});
|
|
EXPECT_TRUE(test::all_close_f(vector<float>{expected_result}, read_vector<float>(result)));
|
|
}
|
|
|
|
// The purpose of this test is to check if we can allow
|
|
// data_batch_shape as a node rather than argument
|
|
NGRAPH_TEST(${BACKEND_NAME}, dyn_convolution_backprop_data)
|
|
{
|
|
Shape shape_filter{6, 3, 3, 3};
|
|
auto filters = make_shared<op::Parameter>(element::f32, PartialShape::dynamic());
|
|
Shape shape_delta{2, 6, 3, 3};
|
|
auto deltas = make_shared<op::Parameter>(element::f32, PartialShape::dynamic());
|
|
Shape shape_data_batch_shape{2, 3, 5, 5};
|
|
auto data_batch_shape =
|
|
make_shared<op::Parameter>(element::i64, PartialShape{Dimension::dynamic()});
|
|
auto strides = Strides{1, 1};
|
|
auto dilations = Strides{1, 1};
|
|
auto padding_begin = CoordinateDiff{0, 0};
|
|
auto padding_end = CoordinateDiff{0, 0};
|
|
|
|
auto conv1 = make_shared<op::v1::ConvolutionBackpropData>(
|
|
deltas, filters, data_batch_shape, strides, padding_begin, padding_end, dilations);
|
|
|
|
auto f = make_shared<Function>(conv1, ParameterVector{deltas, filters, data_batch_shape});
|
|
|
|
auto backend = runtime::Backend::create("${BACKEND_NAME}", true);
|
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auto handle = backend->compile(f);
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auto result = backend->create_dynamic_tensor(element::f32, PartialShape::dynamic());
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vector<float> filter, delta, expected_result;
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for (int i = 0; i < 6 * 3 * 3 * 3; i++)
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filter.emplace_back(i);
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for (int i = 0; i < 2 * 6 * 3 * 3; i++)
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delta.emplace_back(i);
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for (int i = 0; i < 2 * 3 * 5 * 5; i++)
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expected_result.emplace_back(i);
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vector<int64_t> shapes = {5, 5};
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// Create some tensors for input/output
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auto a = backend->create_tensor(element::f32, shape_delta);
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copy_data(a, delta);
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auto b = backend->create_tensor(element::f32, shape_filter);
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copy_data(b, filter);
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auto c = backend->create_tensor(element::i64, Shape{shapes.size()}); // dynamic data batch shape
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copy_data(c, shapes);
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handle->call_with_validate({result}, {a, b, c});
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EXPECT_FALSE(test::all_close_f(vector<float>{expected_result}, read_vector<float>(result)));
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}
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