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-rw-r--r--tests/validation/CL/Convolution3D.cpp300
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diff --git a/tests/validation/CL/Convolution3D.cpp b/tests/validation/CL/Convolution3D.cpp
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+/*
+ * Copyright (c) 2021, 2023 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/runtime/CL/CLTensor.h"
+#include "arm_compute/runtime/CL/functions/CLConv3D.h"
+#include "arm_compute/runtime/FunctionDescriptors.h"
+#include "tests/CL/CLAccessor.h"
+#include "tests/framework/Macros.h"
+#include "tests/framework/datasets/Datasets.h"
+#include "tests/validation/Validation.h"
+#include "tests/validation/fixtures/DirectConvolution3DFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+const RelativeTolerance<half> rel_tolerance_fp16(half(0.2)); /**< Relative tolerance for FP16 tests */
+constexpr float abs_tolerance_fp16(0.05f); /**< Absolute tolerance for FP16 tests */
+constexpr RelativeTolerance<float> rel_tolerance_fp32(0.05f); /**< Relative tolerance for FP32 tests */
+constexpr float abs_tolerance_fp32(0.0001f); /**< Absolute tolerance for FP32 tests*/
+constexpr AbsoluteTolerance<uint8_t> abs_tolerance_qasymm8(1); /**< Absolute tolerance for quantized tests */
+constexpr float tolerance_num = 0.07f; /**< Tolerance number */
+} // namespace
+
+TEST_SUITE(CL)
+TEST_SUITE(DirectConvolution3D)
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(27U, 13U, 5U, 3U), // Unsupported data layout
+ TensorShape(27U, 13U, 5U, 3U), // Unsupported activation enabled
+ TensorShape(27U, 13U, 5U, 3U), // Mismatching data type
+ TensorShape(27U, 13U, 5U, 3U), // Unsupported data type
+ TensorShape(27U, 13U, 5U, 3U), // Mismatching input feature maps
+ TensorShape(27U, 13U, 5U, 3U), // Mismatching output feature maps
+ TensorShape(27U, 13U, 5U, 3U), // Mismatching bias shape
+ TensorShape(27U, 13U, 5U, 3U), // Unsupported number of weights dimensions
+ TensorShape(27U, 13U, 5U, 3U), // Unsupported number of biases dimensions
+ TensorShape(27U, 13U, 5U, 3U), // Mismatching output shape
+ TensorShape(27U, 13U, 5U, 3U)
+ }),
+ framework::dataset::make("WeightsShape", { TensorShape(4U, 27U, 3U, 3U, 3U),
+ TensorShape(4U, 27U, 3U, 3U, 3U),
+ TensorShape(4U, 27U, 3U, 3U, 3U),
+ TensorShape(4U, 27U, 3U, 3U, 3U),
+ TensorShape(4U, 32U, 3U, 3U, 3U),
+ TensorShape(8U, 27U, 3U, 3U, 3U),
+ TensorShape(4U, 27U, 3U, 3U, 3U),
+ TensorShape(4U, 27U, 3U, 3U, 3U, 2U),
+ TensorShape(4U, 27U, 3U, 3U, 3U),
+ TensorShape(4U, 27U, 3U, 3U, 3U),
+ TensorShape(4U, 27U, 3U, 3U, 3U)
+ })),
+ framework::dataset::make("BiasesShape", { TensorShape(4U),
+ TensorShape(4U),
+ TensorShape(4U),
+ TensorShape(4U),
+ TensorShape(4U),
+ TensorShape(4U),
+ TensorShape(8U),
+ TensorShape(4U),
+ TensorShape(4U),
+ TensorShape(4U),
+ TensorShape(4U)
+ })),
+ framework::dataset::make("OutputShape", { TensorShape(4U, 13U, 5U, 3U),
+ TensorShape(4U, 13U, 5U, 3U),
+ TensorShape(4U, 13U, 5U, 3U),
+ TensorShape(4U, 13U, 5U, 3U),
+ TensorShape(4U, 13U, 5U, 3U),
+ TensorShape(4U, 13U, 5U, 3U),
+ TensorShape(4U, 13U, 5U, 3U),
+ TensorShape(4U, 13U, 5U, 3U),
+ TensorShape(4U, 13U, 5U, 3U, 2U),
+ TensorShape(4U, 11U, 5U, 3U),
+ TensorShape(4U, 13U, 5U, 3U)
+ })),
+ framework::dataset::make("Conv3dInfo", { Conv3dInfo(Size3D(1U, 1U, 1U), Padding3D(1U, 1U, 1U), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false),
+ Conv3dInfo(Size3D(1U, 1U, 1U), Padding3D(1U, 1U, 1U), ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false),
+ Conv3dInfo(Size3D(1U, 1U, 1U), Padding3D(1U, 1U, 1U), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false),
+ Conv3dInfo(Size3D(1U, 1U, 1U), Padding3D(1U, 1U, 1U), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false),
+ Conv3dInfo(Size3D(1U, 1U, 1U), Padding3D(1U, 1U, 1U), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false),
+ Conv3dInfo(Size3D(1U, 1U, 1U), Padding3D(1U, 1U, 1U), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false),
+ Conv3dInfo(Size3D(1U, 1U, 1U), Padding3D(1U, 1U, 1U), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false),
+ Conv3dInfo(Size3D(1U, 1U, 1U), Padding3D(1U, 1U, 1U), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false),
+ Conv3dInfo(Size3D(1U, 1U, 1U), Padding3D(1U, 1U, 1U), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false),
+ Conv3dInfo(Size3D(1U, 1U, 1U), Padding3D(1U, 1U, 1U), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false),
+ Conv3dInfo(Size3D(1U, 1U, 1U), Padding3D(1U, 1U, 1U), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false)
+ })),
+ framework::dataset::make("SrcDataType", { DataType::F32,
+ DataType::F32,
+ DataType::F32,
+ DataType::U32,
+ DataType::F32,
+ DataType::F32,
+ DataType::F32,
+ DataType::F32,
+ DataType::F32,
+ DataType::F32,
+ DataType::F32
+ })),
+ framework::dataset::make("WeightsDataType", { DataType::F32,
+ DataType::F32,
+ DataType::F16,
+ DataType::U32,
+ DataType::F32,
+ DataType::F32,
+ DataType::F32,
+ DataType::F32,
+ DataType::F32,
+ DataType::F32,
+ DataType::F32
+ })),
+ framework::dataset::make("DataLayout", { DataLayout::NCDHW,
+ DataLayout::NDHWC,
+ DataLayout::NDHWC,
+ DataLayout::NDHWC,
+ DataLayout::NDHWC,
+ DataLayout::NDHWC,
+ DataLayout::NDHWC,
+ DataLayout::NDHWC,
+ DataLayout::NDHWC,
+ DataLayout::NDHWC,
+ DataLayout::NDHWC
+ })),
+ framework::dataset::make("Expected", { false, false, false, false, false, false, false, false, false, false, true })),
+ input_shape, weights_shape, biases_shape, output_shape, conv3d_info, src_data_type, weights_data_type, data_layout, expected)
+{
+ TensorInfo input_info = TensorInfo(input_shape, 1, src_data_type);
+ TensorInfo weights_info = TensorInfo(weights_shape, 1, weights_data_type);
+ TensorInfo biases_info = TensorInfo(biases_shape, 1, src_data_type);
+ TensorInfo output_info = TensorInfo(output_shape, 1, src_data_type);
+
+ input_info.set_data_layout(data_layout);
+ weights_info.set_data_layout(data_layout);
+ biases_info.set_data_layout(data_layout);
+ output_info.set_data_layout(data_layout);
+
+ bool is_valid = bool(CLConv3D::validate(&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), conv3d_info));
+ ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
+}
+
+template <typename T>
+using CLDirectConvolution3DFixture = DirectConvolution3DValidationFixture<CLTensor, CLAccessor, CLConv3D, T>;
+template <typename T>
+using CLDirectConvolution3DQuantizedFixture = DirectConvolution3DValidationQuantizedFixture<CLTensor, CLAccessor, CLConv3D, T>;
+
+TEST_SUITE(NDHWC)
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolution3DFixture<half>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(7U, 5U, 3U, 13U, 3U),
+ TensorShape(15U, 7U, 11U, 7U),
+ TensorShape(19U, 5U, 16U, 4U),
+ TensorShape(13U, 5U, 17U, 2U)
+ }),
+ framework::dataset::make("StrideX", { 1, 3, 2, 1 })),
+ framework::dataset::make("StrideY", { 2, 1, 3, 1 })),
+ framework::dataset::make("StrideZ", { 3, 2, 1, 1 })),
+ framework::dataset::make("PadX", { 0, 2, 1, 0 })),
+ framework::dataset::make("PadY", { 1, 0, 2, 0 })),
+ framework::dataset::make("PadZ", { 2, 1, 0, 0 })),
+ framework::dataset::make("KernelWidth", { 3, 7, 5, 1 })),
+ framework::dataset::make("KernelHeight", { 5, 3, 7, 1 })),
+ framework::dataset::make("KernelDepth", { 7, 5, 3, 1 })),
+ framework::dataset::make("NumKernels", { 5, 3, 1, 11 })),
+ framework::dataset::make("HasBias", { true, true, true, false })),
+ framework::dataset::make("Activation", ActivationLayerInfo())),
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", DataLayout::NDHWC)))
+{
+ validate(CLAccessor(_target), _reference, rel_tolerance_fp16, tolerance_num, abs_tolerance_fp16);
+}
+
+TEST_SUITE_END() // FP16
+
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolution3DFixture<float>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(7U, 5U, 3U, 13U, 3U),
+ TensorShape(15U, 7U, 11U, 7U),
+ TensorShape(19U, 5U, 16U, 4U),
+ TensorShape(13U, 5U, 17U, 2U)
+ }),
+ framework::dataset::make("StrideX", { 1, 3, 2, 1 })),
+ framework::dataset::make("StrideY", { 2, 1, 3, 1 })),
+ framework::dataset::make("StrideZ", { 3, 2, 1, 1 })),
+ framework::dataset::make("PadX", { 0, 2, 1, 0 })),
+ framework::dataset::make("PadY", { 1, 0, 2, 0 })),
+ framework::dataset::make("PadZ", { 2, 1, 0, 0 })),
+ framework::dataset::make("KernelWidth", { 3, 7, 5, 1 })),
+ framework::dataset::make("KernelHeight", { 5, 3, 7, 1 })),
+ framework::dataset::make("KernelDepth", { 7, 5, 3, 1 })),
+ framework::dataset::make("NumKernels", { 5, 3, 1, 11 })),
+ framework::dataset::make("HasBias", { true, true, true, false })),
+ framework::dataset::make("Activation", ActivationLayerInfo())),
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", DataLayout::NDHWC)))
+{
+ validate(CLAccessor(_target), _reference, rel_tolerance_fp32, 0.0, abs_tolerance_fp32);
+}
+
+// clang-format on
+// *INDENT-ON*
+TEST_SUITE_END() // FP32
+
+TEST_SUITE(QASYMM8)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolution3DQuantizedFixture<uint8_t>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(combine(combine(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(7U, 5U, 3U, 13U, 3U),
+ TensorShape(15U, 7U, 11U, 7U),
+ TensorShape(19U, 5U, 16U, 4U),
+ TensorShape(13U, 5U, 17U, 2U)
+ }),
+ framework::dataset::make("StrideX", { 1, 3, 2, 1 })),
+ framework::dataset::make("StrideY", { 2, 1, 3, 1 })),
+ framework::dataset::make("StrideZ", { 3, 2, 1, 1 })),
+ framework::dataset::make("PadX", { 0, 2, 1, 0 })),
+ framework::dataset::make("PadY", { 1, 0, 2, 0 })),
+ framework::dataset::make("PadZ", { 2, 1, 0, 0 })),
+ framework::dataset::make("KernelWidth", { 3, 7, 5, 1 })),
+ framework::dataset::make("KernelHeight", { 5, 3, 7, 1 })),
+ framework::dataset::make("KernelDepth", { 7, 5, 3, 1 })),
+ framework::dataset::make("NumKernels", { 5, 3, 1, 11 })),
+ framework::dataset::make("HasBias", { true, true, true, false })),
+ framework::dataset::make("Activation", ActivationLayerInfo())),
+ framework::dataset::make("DataType", DataType::QASYMM8)),
+ framework::dataset::make("DataLayout", DataLayout::NDHWC)),
+ framework::dataset::make("SrcQuantizationInfo", QuantizationInfo(0.1f, 10))),
+ framework::dataset::make("WeightsQuantizationInfo", QuantizationInfo(0.3f, 20))),
+ framework::dataset::make("DstQuantizationInfo", QuantizationInfo(0.2f, 5))))
+{
+ validate(CLAccessor(_target), _reference, abs_tolerance_qasymm8);
+}
+
+TEST_SUITE_END() // QASYMM8
+
+TEST_SUITE(QASYMM8_SIGNED)
+FIXTURE_DATA_TEST_CASE(RunSmall, CLDirectConvolution3DQuantizedFixture<int8_t>, framework::DatasetMode::PRECOMMIT,
+ combine(combine(combine(combine(combine(combine(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip(
+ framework::dataset::make("InputShape", { TensorShape(7U, 5U, 3U, 13U, 3U),
+ TensorShape(15U, 7U, 11U, 7U),
+ TensorShape(19U, 5U, 16U, 4U),
+ TensorShape(13U, 5U, 17U, 2U)
+ }),
+ framework::dataset::make("StrideX", { 1, 3, 2, 1 })),
+ framework::dataset::make("StrideY", { 2, 1, 3, 1 })),
+ framework::dataset::make("StrideZ", { 3, 2, 1, 1 })),
+ framework::dataset::make("PadX", { 0, 2, 1, 0 })),
+ framework::dataset::make("PadY", { 1, 0, 2, 0 })),
+ framework::dataset::make("PadZ", { 2, 1, 0, 0 })),
+ framework::dataset::make("KernelWidth", { 3, 7, 5, 1 })),
+ framework::dataset::make("KernelHeight", { 5, 3, 7, 1 })),
+ framework::dataset::make("KernelDepth", { 7, 5, 3, 1 })),
+ framework::dataset::make("NumKernels", { 5, 3, 1, 11 })),
+ framework::dataset::make("HasBias", { true, true, true, false })),
+ framework::dataset::make("Activation", ActivationLayerInfo())),
+ framework::dataset::make("DataType", DataType::QASYMM8_SIGNED)),
+ framework::dataset::make("DataLayout", DataLayout::NDHWC)),
+ framework::dataset::make("SrcQuantizationInfo", QuantizationInfo(0.1f, 10))),
+ framework::dataset::make("WeightsQuantizationInfo", QuantizationInfo(0.3f, 20))),
+ framework::dataset::make("DstQuantizationInfo", QuantizationInfo(0.2f, 5))))
+{
+ validate(CLAccessor(_target), _reference, abs_tolerance_qasymm8);
+}
+
+TEST_SUITE_END() // QASYMM8_SIGNED
+
+TEST_SUITE_END() // NDHWC
+TEST_SUITE_END() // DirectConvolution3D
+TEST_SUITE_END() // CL
+
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
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