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-rw-r--r--tests/validation/NEON/DepthwiseConvolutionLayerKernel.cpp180
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diff --git a/tests/validation/NEON/DepthwiseConvolutionLayerKernel.cpp b/tests/validation/NEON/DepthwiseConvolutionLayerKernel.cpp
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+/*
+ * Copyright (c) 2019 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/core/NEON/kernels/NEDepthwiseConvolutionLayerKernel.h"
+#include "tests/NEON/Accessor.h"
+#include "tests/NEON/Helper.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+using namespace arm_compute::misc::shape_calculator;
+
+// Create function for NEDepthwiseConvolutionLayerKernel
+using NEDepthwiseConvolutionLayer = NESynthetizeFunctionWithZeroConstantKernelBorder<NEDepthwiseConvolutionLayerKernel>;
+
+// Fixture for NEDepthwiseConvolutionLayerKernel
+template <typename T>
+using NEDepthwiseConvolutionLayerKernelFixture = DepthwiseConvolutionLayerKernelValidationFixture<Tensor, Accessor, NEDepthwiseConvolutionLayer, T>;
+
+namespace
+{
+// *INDENT-OFF*
+// clang-format off
+RelativeTolerance<float> rel_tolerance_f32(0.001f);
+constexpr float abs_tolerance_f32(0.0001f);
+
+/** Width values to test - Precommit */
+const auto width_values = framework::dataset::make("width", { 17U, 47U } );
+
+/** Height values to test - Precommit */
+const auto height_values = framework::dataset::make("height", { 19U, 43U } );
+
+/** Channel values to test - Precommit */
+const auto channel_values = framework::dataset::make("channels", { 32U, 128U });
+
+/** Batch values to test - Precommit */
+const auto batch_values = framework::dataset::make("batch", { 1U, 3U });
+
+/** Kernel size values to test - Precommit */
+const auto kernel_sz_values = framework::dataset::make("kernel_size", { Size2D(3U, 5U), Size2D(5U, 3U) });
+
+/** Depth multiplier values to test - Precommit */
+const auto depth_multiplier_values = framework::dataset::make("depth_multiplier", { 1U, 3U });
+
+/** Dilation values to test - Precommit */
+const auto dilation_values = framework::dataset::make("dilation", { Size2D(1U, 1U), Size2D(3U, 3U) });
+
+/** Stride values to test - All */
+const auto stride_values = framework::dataset::make("stride", { Size2D(1U, 1U), Size2D(3U, 2U) });
+
+/** Padding values to test - All */
+const auto padding_valid_values = framework::dataset::make("padding_valid", { true, false });
+
+/** Data type values to test - All */
+const auto data_type_values = framework::dataset::make("data_type", { DataType::F32 });
+
+/** Data layout values to test - All */
+const auto data_layout_values = framework::dataset::make("data_layout", { DataLayout::NHWC });
+
+/** Configuration test */
+void validate_configuration(size_t width_value, size_t height_value, size_t channel_value, size_t batch_value, Size2D kernel_sz_value, size_t depth_multiplier_value, Size2D dilation_value, Size2D stride_value, bool padding_valid_value, DataType data_type_value, DataLayout data_layout_value)
+{
+ TensorShape src_shape(width_value, height_value, channel_value, batch_value);
+ TensorShape weights_shape(kernel_sz_value.width, kernel_sz_value.height, channel_value * depth_multiplier_value);
+ TensorShape biases_shape(channel_value * depth_multiplier_value);
+
+ if(data_layout_value == DataLayout::NHWC)
+ {
+ permute(src_shape, PermutationVector(2U, 0U, 1U, 3U));
+ permute(weights_shape, PermutationVector(2U, 0U, 1U));
+ }
+
+ TensorInfo src_info(src_shape, 1, data_type_value);
+ TensorInfo weights_info(weights_shape, 1, data_type_value);
+ TensorInfo biases_info(biases_shape, 1, data_type_value);
+
+ src_info.set_data_layout(data_layout_value);
+ weights_info.set_data_layout(data_layout_value);
+ biases_info.set_data_layout(data_layout_value);
+
+ PadStrideInfo conv_info;
+ if(padding_valid_value)
+ {
+ conv_info = PadStrideInfo();
+ }
+ else
+ {
+ conv_info = calculate_same_pad(src_shape, weights_shape, PadStrideInfo(stride_value.width, stride_value.height), data_layout_value, dilation_value);
+ }
+
+ const TensorShape dst_shape = compute_depthwise_convolution_shape(src_info, weights_info, conv_info, depth_multiplier_value, dilation_value);
+
+ // Create tensors
+ Tensor src = create_tensor<Tensor>(src_shape, data_type_value, 1, QuantizationInfo(), data_layout_value);
+ Tensor weights = create_tensor<Tensor>(weights_shape, data_type_value, 1, QuantizationInfo(), data_layout_value);
+ Tensor biases = create_tensor<Tensor>(biases_shape, data_type_value, 1, QuantizationInfo(), data_layout_value);
+ Tensor dst = create_tensor<Tensor>(dst_shape, data_type_value, 1, QuantizationInfo(), data_layout_value);
+
+ ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(biases.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Create and configure function
+ NEDepthwiseConvolutionLayer dwc;
+ dwc.configure(&src, &weights, &biases, &dst, conv_info, depth_multiplier_value, dilation_value);
+}
+} // namespace
+
+TEST_SUITE(NEON)
+TEST_SUITE(DepthwiseConvolutionLayer)
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(width_values,
+ height_values),
+ channel_values),
+ batch_values),
+ kernel_sz_values),
+ depth_multiplier_values),
+ dilation_values),
+ stride_values),
+ padding_valid_values),
+ data_type_values),
+ data_layout_values),
+width_value, height_value, channel_value, batch_value, kernel_sz_value, depth_multiplier_value, dilation_value, stride_value, padding_valid_value, data_type_value, data_layout_value)
+{
+ validate_configuration(width_value, height_value, channel_value, batch_value, kernel_sz_value, depth_multiplier_value, dilation_value, stride_value, padding_valid_value, data_type_value, data_layout_value);
+}
+
+FIXTURE_DATA_TEST_CASE(RunSmall, NEDepthwiseConvolutionLayerKernelFixture<float>, framework::DatasetMode::ALL,
+ combine(combine(combine(combine(combine(combine(combine(combine(combine(combine(width_values,
+ height_values),
+ channel_values),
+ batch_values),
+ kernel_sz_values),
+ depth_multiplier_values),
+ dilation_values),
+ stride_values),
+ padding_valid_values),
+ data_type_values),
+ data_layout_values))
+{
+ // Validate output
+ validate(Accessor(_target), _reference, rel_tolerance_f32, 0.f, abs_tolerance_f32);
+}
+
+TEST_SUITE_END() // FP32
+TEST_SUITE_END() // Float
+TEST_SUITE_END() // DepthwiseConvolutionLayer
+TEST_SUITE_END() // NEON
+} // namespace validation
+} // namespace test
+} // namespace arm_compute \ No newline at end of file