COMPMID-1017: Implement dilated convolution in NEON, OpenCL, and GC
Change-Id: If4626ec9e215e14dffe22e80812da5bac84a52e2
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/125734
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/CL/DilatedConvolutionLayer.cpp b/tests/validation/CL/DilatedConvolutionLayer.cpp
new file mode 100644
index 0000000..dadae22
--- /dev/null
+++ b/tests/validation/CL/DilatedConvolutionLayer.cpp
@@ -0,0 +1,289 @@
+/*
+ * Copyright (c) 2018 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 CONCLCTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/CL/CLTensor.h"
+#include "arm_compute/runtime/CL/CLTensorAllocator.h"
+#include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h"
+#include "arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h"
+#include "tests/CL/CLAccessor.h"
+#include "tests/PaddingCalculator.h"
+#include "tests/datasets/DilatedConvolutionLayerDataset.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/ConvolutionLayerFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+RelativeTolerance<float> tolerance_f32(0.05f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
+RelativeTolerance<half_float::half> tolerance_f16(half_float::half(0.2)); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
+constexpr AbsoluteTolerance<float> tolerance_fixed(1.0f); /**< Tolerance value for comparing reference's output against implementation's output for fixed point data types */
+constexpr AbsoluteTolerance<float> tolerance_qasymm8(0.0); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */
+constexpr float tolerance_num = 0.07f; /**< Tolerance number */
+
+/** CNN data types */
+const auto CNNDataTypes = framework::dataset::make("DataType",
+{
+ DataType::F16,
+ DataType::F32,
+ DataType::QS8,
+ DataType::QS16,
+ DataType::QASYMM8,
+});
+} // namespace
+
+TEST_SUITE(CL)
+TEST_SUITE(DilatedConvolutionLayer)
+
+DATA_TEST_CASE(ValidateConvolutionMethod, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 2U, 1U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32, 0)
+ }),
+ framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(5U, 5U, 2U, 19U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16, 0)
+ })),
+ framework::dataset::make("BiasesInfo", { TensorInfo(TensorShape(19U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(19U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(16U), 1, DataType::F32, 0)
+ })),
+ framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 25U, 21U), 1, DataType::F32, 0),
+ TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32, 0)
+ })),
+ framework::dataset::make("ConvInfo", { PadStrideInfo(1, 2, 1, 1),
+ PadStrideInfo(1, 2, 1, 1),
+ PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(2, 1, 0, 0),
+ PadStrideInfo(3, 2, 1, 0)
+ })),
+ framework::dataset::make("GpuTarget", { GPUTarget::BIFROST,
+ GPUTarget::MIDGARD,
+ GPUTarget::G71,
+ GPUTarget::MIDGARD,
+ GPUTarget::BIFROST
+ })),
+ framework::dataset::make("Dilation", { Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(1U, 1U),
+ Size2D(2U, 2U),
+ Size2D(3U, 3U)
+ })),
+
+ framework::dataset::make("Expected", { ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM, ConvolutionMethod::GEMM })),
+ input_info, weights_info, biases_info, output_info, conv_info, gpu_target, dilation, expected)
+{
+ ConvolutionMethod is_valid = CLConvolutionLayer::get_convolution_method(&input_info.clone()->set_is_resizable(false),
+ &weights_info.clone()->set_is_resizable(false),
+ &biases_info.clone()->set_is_resizable(false),
+ &output_info.clone()->set_is_resizable(false), conv_info, WeightsInfo(), gpu_target, dilation);
+ ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+TEST_SUITE_END()
+
+TEST_SUITE(GEMMDilatedConvolutionLayer)
+
+DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallDilatedConvolutionLayerDataset(), datasets::LargeDilatedConvolutionLayerDataset()),
+ CNNDataTypes),
+ input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type)
+{
+ // Set fixed point position data type allowed
+ int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0;
+
+ auto bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
+
+ // Create tensors
+ CLTensor src = create_tensor<CLTensor>(input_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor weights = create_tensor<CLTensor>(weights_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor bias = create_tensor<CLTensor>(bias_shape, bias_data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
+ CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1, fixed_point_position, QuantizationInfo(2.f / 255.f, 127));
+
+ ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ const QuantizationInfo src_quantization_info = src.info()->quantization_info();
+ const QuantizationInfo weights_quantization_info = weights.info()->quantization_info();
+
+ // Create and configure function
+ CLGEMMConvolutionLayer conv;
+ conv.configure(&src, &weights, &bias, &dst, info, WeightsInfo(), dilation);
+
+ // Validate valid region
+ const ValidRegion src_valid_region = shape_to_valid_region(input_shape);
+ const ValidRegion weights_valid_region = shape_to_valid_region(weights_shape);
+ const ValidRegion bias_valid_region = shape_to_valid_region(bias_shape);
+ const ValidRegion dst_valid_region = shape_to_valid_region(output_shape);
+
+ validate(src.info()->valid_region(), src_valid_region);
+ validate(weights.info()->valid_region(), weights_valid_region);
+ validate(bias.info()->valid_region(), bias_valid_region);
+ validate(dst.info()->valid_region(), dst_valid_region);
+
+ // Validate QuantizationInfo
+ ARM_COMPUTE_EXPECT(src.info()->quantization_info() == src_quantization_info, framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(weights.info()->quantization_info() == weights_quantization_info, framework::LogLevel::ERRORS);
+
+ // Validate padding
+ //TODO(COMPMID-415) Need to validate padding?
+}
+
+template <typename T>
+using CLGEMMDilatedConvolutionLayerFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallDilatedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType",
+ DataType::F16)))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMDilatedConvolutionLayerFixture<half>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeDilatedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType",
+ DataType::F16)))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f16, tolerance_num);
+}
+TEST_SUITE_END()
+
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallDilatedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType",
+ DataType::F32)))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMDilatedConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeDilatedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType",
+ DataType::F32)))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_f32);
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+
+template <typename T>
+using CLGEMMDilatedConvolutionLayerFixedPointFixture = ConvolutionValidationFixedPointFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>;
+
+TEST_SUITE(FixedPoint)
+TEST_SUITE(QS8)
+// We test for fixed point precision [4,6]
+FIXTURE_DATA_TEST_CASE(RunTiny, CLGEMMDilatedConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::TinyDilatedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType",
+ DataType::QS8)),
+ framework::dataset::make("FractionalBits", 4, 7)))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_fixed);
+}
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType",
+ DataType::QS8)),
+ framework::dataset::make("FractionalBits", 4, 7)))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_fixed);
+}
+TEST_SUITE_END()
+
+TEST_SUITE(QS16)
+// Testing for fixed point position [1,14)
+FIXTURE_DATA_TEST_CASE(RunTiny, CLGEMMDilatedConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::TinyDilatedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType",
+ DataType::QS16)),
+ framework::dataset::make("FractionalBits", 1, 14)))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_fixed);
+}
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType",
+ DataType::QS16)),
+ framework::dataset::make("FractionalBits", 1, 14)))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_fixed);
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+
+template <typename T>
+using CLGEMMDilatedConvolutionLayerQuantizedFixture = ConvolutionValidationQuantizedFixture<CLTensor, CLAccessor, CLGEMMConvolutionLayer, T>;
+
+TEST_SUITE(Quantized)
+TEST_SUITE(QASYMM8)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::SmallDilatedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 10) })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+FIXTURE_DATA_TEST_CASE(RunLarge, CLGEMMDilatedConvolutionLayerQuantizedFixture<uint8_t>, framework::DatasetMode::NIGHTLY, combine(combine(combine(datasets::LargeDilatedConvolutionLayerDataset(),
+ framework::dataset::make("ReshapeWeights", { true })),
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("QuantizationInfo", { QuantizationInfo(2.f / 255.f, 0) })))
+{
+ // Validate output
+ validate(CLAccessor(_target), _reference, tolerance_qasymm8);
+}
+TEST_SUITE_END()
+TEST_SUITE_END()
+
+TEST_SUITE_END()
+TEST_SUITE_END()
+} // namespace validation
+} // namespace test
+} // namespace arm_compute