Implement FP32/16 Depthwise Conv2d operator in dynamic fusion
This patch adds Depthwise Conv2d operator into dynamic fusion interface and adds the associated tests.
Resolves: COMPMID-5517
Change-Id: I385c94dff7fd40c72b8337ef797e508df4499a82
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8678
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/dynamic_fusion/gpu/cl/DepthwiseConv2d.cpp b/tests/validation/dynamic_fusion/gpu/cl/DepthwiseConv2d.cpp
new file mode 100644
index 0000000..f08cc60
--- /dev/null
+++ b/tests/validation/dynamic_fusion/gpu/cl/DepthwiseConv2d.cpp
@@ -0,0 +1,477 @@
+/*
+ * Copyright (c) 2022 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/dynamic_fusion/sketch/gpu/operators/GpuDepthwiseConv2d.h"
+
+#include "tests/CL/CLAccessor.h"
+#include "tests/datasets/DepthwiseConvolutionLayerDataset.h"
+#include "tests/datasets/DilatedDepthwiseConvolutionLayerDataset.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/dynamic_fusion/gpu/cl/DepthwiseConv2dFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+const auto depth_multipliers = framework::dataset::make("DepthMultiplier", { 1U, 4U });
+const auto large_depth_multipliers = framework::dataset::make("DepthMultiplier", { 1, 2, 5, 8 });
+
+TEST_SUITE(CL)
+TEST_SUITE(DYNAMIC_FUSION)
+TEST_SUITE(DEPTHWISE_CONV2D)
+
+RelativeTolerance<float> tolerance_f32(0.01f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+RelativeTolerance<half_float::half> tolerance_f16(half_float::half(0.1)); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
+constexpr float tolerance_num = 0.02f; /**< Tolerance number */
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Mismatching data type input/weights
+ TensorInfo(TensorShape(3U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Mismatching input feature maps
+ TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Mismatching depth multiplier
+ TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid biases size
+ TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid biases dimensions
+ TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // Invalid output size
+ TensorInfo(TensorShape(8U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // patch size bigger than input width
+ TensorInfo(TensorShape(8U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC), // dilation < 1
+ TensorInfo(TensorShape(8U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(8U, 32U, 13U), 1, DataType::QASYMM8, DataLayout::NHWC), // Unsupported data type
+ TensorInfo(TensorShape(8U, 32U, 13U), 1, DataType::QASYMM8_SIGNED, DataLayout::NHWC), // Unsupported data type
+ TensorInfo(TensorShape(8U, 32U, 13U), 1, DataType::QSYMM16, DataLayout::NHWC), // Unsupported data type
+ TensorInfo(TensorShape(8U, 32U, 13U), 1, DataType::QSYMM8, DataLayout::NHWC), // Unsupported data type
+ TensorInfo(TensorShape(8U, 32U, 13U), 1, DataType::QSYMM8_PER_CHANNEL, DataLayout::NHWC), // Unsupported data type
+ TensorInfo(TensorShape(8U, 32U, 13U), 1, DataType::QASYMM16, DataLayout::NHWC), // Unsupported data type
+ TensorInfo(TensorShape(8U, 32U, 13U), 1, DataType::U8, DataLayout::NHWC), // Unsupported data type
+ TensorInfo(TensorShape(8U, 32U, 13U), 1, DataType::S8, DataLayout::NHWC), // Unsupported data type
+ TensorInfo(TensorShape(8U, 32U, 13U), 1, DataType::U16, DataLayout::NHWC), // Unsupported data type
+ TensorInfo(TensorShape(8U, 32U, 13U), 1, DataType::S16, DataLayout::NHWC), // Unsupported data type
+ TensorInfo(TensorShape(8U, 32U, 13U), 1, DataType::U32, DataLayout::NHWC), // Unsupported data type
+ TensorInfo(TensorShape(8U, 32U, 13U), 1, DataType::S32, DataLayout::NHWC), // Unsupported data type
+ TensorInfo(TensorShape(32U, 13U, 8U), 1, DataType::F32, DataLayout::NCHW), // Unsupported data layout
+ TensorInfo(TensorShape(8U, 32U, 13U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(8U, 32U, 13U, 4U), 1, DataType::F32, DataLayout::NHWC), // weight dimension > 3
+ TensorInfo(TensorShape(8U, 32U, 13U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(8U, 32U, 13U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(8U, 32U, 13U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ }),
+ framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(2U, 3U, 3U, 2U), 1, DataType::F16, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 3U, 3U, 2U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 3U, 3U, 2U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 3U, 3U, 2U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 3U, 3U, 2U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 3U, 3U, 2U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(16U, 3U, 3U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(16U, 3U, 3U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(16U, 3U, 3U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::QASYMM8, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::QASYMM8_SIGNED, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::QSYMM16, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::QSYMM8, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::QSYMM8_PER_CHANNEL, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::QASYMM16, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::U8, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::S8, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::U16, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::S16, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::U32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(3U, 3U, 24U), 1, DataType::F32, DataLayout::NCHW),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U, 5U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 3U, 3U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 4U, 3U), 1, DataType::F32, DataLayout::NHWC),
+ })),
+ framework::dataset::make("BiasesInfo", { TensorInfo(TensorShape(2U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 2U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(16U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(16U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(16U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::S32, DataLayout::NCHW),
+ TensorInfo(TensorShape(24U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U), 1, DataType::F32, DataLayout::NHWC),
+ })),
+ framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(2U, 25U, 11U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 25U, 11U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 25U, 11U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 25U, 11U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 25U, 11U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(2U, 27U, 13U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(16U, 25U, 11U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(16U, 25U, 11U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(16U, 25U, 11U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 32U, 11U), 1, DataType::QASYMM8, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 32U, 11U), 1, DataType::QASYMM8_SIGNED, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 32U, 11U), 1, DataType::QSYMM16, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 32U, 11U), 1, DataType::QSYMM8, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 32U, 11U), 1, DataType::QSYMM8_PER_CHANNEL, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 32U, 11U), 1, DataType::QASYMM16, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 32U, 11U), 1, DataType::U8, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 32U, 11U), 1, DataType::S8, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 32U, 11U), 1, DataType::U16, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 32U, 11U), 1, DataType::S16, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 32U, 11U), 1, DataType::U32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 32U, 11U), 1, DataType::S32, DataLayout::NHWC),
+ TensorInfo(TensorShape(32U, 11U, 24U), 1, DataType::F32, DataLayout::NCHW),
+ TensorInfo(TensorShape(24U, 32U, 11U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 32U, 11U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 33U, 14U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 17U, 5U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ TensorInfo(TensorShape(24U, 15U, 4U, 4U), 1, DataType::F32, DataLayout::NHWC),
+ })),
+ framework::dataset::make("Padding", { Padding2D(0, 0, 0, 0),
+ Padding2D(0, 0, 0, 0),
+ Padding2D(0, 0, 0, 0),
+ Padding2D(0, 0, 0, 0),
+ Padding2D(0, 0, 0, 0),
+ Padding2D(0, 0, 0, 0),
+ Padding2D(0, 0, 0, 0),
+ Padding2D(0, 0, 0, 0),
+ Padding2D(0, 0, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(1, 1, 0, 0),
+ Padding2D(2, 1, 2, 1),
+ Padding2D(2, 1, 2, 1),
+ Padding2D(2, 1, 2, 1),
+ })),
+ framework::dataset::make("Stride", { Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(1, 1),
+ Size2D(2, 3),
+ Size2D(2, 3),
+ })),
+ framework::dataset::make("DepthMultiplier", { 1,
+ 1,
+ 3,
+ 1,
+ 1,
+ 1,
+ 2,
+ 2,
+ 2,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ 3,
+ })),
+ framework::dataset::make("Dilation", { Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(20U, 1U),
+ Size2D(0U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(2U, 3U),
+ })),
+ framework::dataset::make("Expected", { false, false, false, false, false, false, false, false, true, false,
+ false, false, false, false, false, false, false, false, false, false,
+ false, false, true, false, true, true, true })),
+ input_info, weights_info, biases_info, output_info, padding, stride, depth_multiplier, dilation, expected)
+{
+ CLCompileContext cl_compile_ctx = CLKernelLibrary::get().get_compile_context();
+ GpuWorkloadContext gpu_ctx = GpuWorkloadContext{ &cl_compile_ctx };
+ GpuWorkloadSketch sketch{ &gpu_ctx };
+
+ const TensorInfo sketch_input_info = sketch.create_tensor_info(input_info);
+ const TensorInfo sketch_weights_info = sketch.create_tensor_info(weights_info);
+ const TensorInfo sketch_biases_info = sketch.create_tensor_info(biases_info);
+ const TensorInfo sketch_output_info = sketch.create_tensor_info(output_info);
+
+ DepthwiseConv2dAttributes attributes {};
+ attributes.pad(padding)
+ .stride(stride)
+ .dilation(dilation)
+ .depth_multiplier(depth_multiplier);
+
+ const Status status = GpuDepthwiseConv2d::validate_op(sketch, &sketch_input_info, &sketch_weights_info, &sketch_biases_info, &sketch_output_info, attributes);
+ const bool res = bool(status);
+ ARM_COMPUTE_EXPECT(res == expected, framework::LogLevel::ERRORS);
+}
+// clang-format on
+// *INDENT-ON*
+
+template <typename T>
+using DynamicFusionGpuDepthwiseConv2dFixture = DynamicFusionGpuDepthwiseConv2dValidationFixture<CLTensor, CLAccessor, GpuDepthwiseConv2d, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP16)
+TEST_SUITE(W3x3)
+FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuDepthwiseConv2dFixture<half>, framework::DatasetMode::ALL,
+ combine(combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset3x3(),
+ depth_multipliers),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f16);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuDepthwiseConv2dFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset3x3(),
+ large_depth_multipliers),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f16);
+}
+TEST_SUITE(Dilation)
+FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuDepthwiseConv2dFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(datasets::SmallDepthwiseDilatedConvolutionLayerDataset3x3(),
+ depth_multipliers),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NHWC })))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f16);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuDepthwiseConv2dFixture<half>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(datasets::LargeDepthwiseDilatedConvolutionLayerDataset3x3(),
+ large_depth_multipliers),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NHWC })))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f16);
+}
+TEST_SUITE_END() // Dilation
+TEST_SUITE_END() // W3x3
+
+TEST_SUITE(Generic)
+FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuDepthwiseConv2dFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset(),
+ depth_multipliers),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NHWC })))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuDepthwiseConv2dFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset(),
+ large_depth_multipliers),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NHWC })))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
+}
+
+TEST_SUITE(Dilation)
+FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuDepthwiseConv2dFixture<half>, framework::DatasetMode::ALL, combine(combine(combine(datasets::SmallDepthwiseDilatedConvolutionLayerDataset(),
+ depth_multipliers),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NHWC })))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuDepthwiseConv2dFixture<half>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(datasets::LargeDepthwiseDilatedConvolutionLayerDataset(),
+ large_depth_multipliers),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NHWC })))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
+}
+TEST_SUITE_END() // Dilation
+TEST_SUITE_END() // Generic
+TEST_SUITE_END() // FP16
+
+TEST_SUITE(FP32)
+TEST_SUITE(W3x3)
+FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuDepthwiseConv2dFixture<float>, framework::DatasetMode::ALL,
+ combine(combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset3x3(),
+ depth_multipliers),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuDepthwiseConv2dFixture<float>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset3x3(),
+ large_depth_multipliers),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+
+TEST_SUITE(Dilation)
+
+FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuDepthwiseConv2dFixture<float>, framework::DatasetMode::ALL,
+ combine(combine(combine(datasets::SmallDepthwiseDilatedConvolutionLayerDataset3x3(),
+ depth_multipliers),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuDepthwiseConv2dFixture<float>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(datasets::LargeDepthwiseDilatedConvolutionLayerDataset3x3(),
+ large_depth_multipliers),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", DataLayout::NHWC)))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+TEST_SUITE_END() // Dilation
+TEST_SUITE_END() // W3x3
+
+TEST_SUITE(Generic)
+FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuDepthwiseConv2dFixture<float>, framework::DatasetMode::ALL,
+ combine(combine(combine(datasets::SmallDepthwiseConvolutionLayerDataset(),
+ depth_multipliers),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NHWC })))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuDepthwiseConv2dFixture<float>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(datasets::LargeDepthwiseConvolutionLayerDataset(),
+ large_depth_multipliers),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NHWC })))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+
+FIXTURE_DATA_TEST_CASE(RunLargeKernelSize, DynamicFusionGpuDepthwiseConv2dFixture<float>, framework::DatasetMode::ALL,
+ combine(combine(combine(datasets::LargeKernelSizeDepthwiseConvolutionLayerNHWCDataset(),
+ framework::dataset::make("DepthMultiplier", { 1 })),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NHWC })))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+
+TEST_SUITE(Dilation)
+FIXTURE_DATA_TEST_CASE(RunSmall, DynamicFusionGpuDepthwiseConv2dFixture<float>, framework::DatasetMode::ALL, combine(combine(combine(datasets::SmallDepthwiseDilatedConvolutionLayerDataset(),
+ depth_multipliers),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NHWC })))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, DynamicFusionGpuDepthwiseConv2dFixture<float>, framework::DatasetMode::NIGHTLY,
+ combine(combine(combine(datasets::LargeDepthwiseDilatedConvolutionLayerDataset3x3(),
+ large_depth_multipliers),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NHWC })))
+{
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+TEST_SUITE_END() // Dilation
+TEST_SUITE_END() // Generic
+TEST_SUITE_END() // FP32
+TEST_SUITE_END() // Float
+TEST_SUITE_END() // DEPTHWISE_CONV2D
+TEST_SUITE_END() // DYNAMIC_FUSION
+TEST_SUITE_END() // CL
+} // namespace validation
+} // namespace test
+} // namespace arm_compute