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-rw-r--r--tests/validation/NEON/Convolution3D.cpp228
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diff --git a/tests/validation/NEON/Convolution3D.cpp b/tests/validation/NEON/Convolution3D.cpp
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+/*
+ * Copyright (c) 2021 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/Helpers.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/NEON/functions/NEConv3D.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "arm_compute/runtime/TensorAllocator.h"
+#include "tests/NEON/Accessor.h"
+#include "tests/PaddingCalculator.h"
+#include "tests/datasets/ShapeDatasets.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/DirectConvolution3DFixture.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+const RelativeTolerance<half_float::half> rel_tolerance_f16(half_float::half(0.2f)); /**< Relative tolerance value for FP16 types */
+const AbsoluteTolerance<float> abs_tolerance_f16(0.2f); /**< Absolute tolerance for FP16 types */
+constexpr float tolerance_num = 0.07f; /**< Tolerance number for the FP16 implementation */
+#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+constexpr AbsoluteTolerance<float> tolerance_fp32(0.001f); /**< Tolerance for floating point tests */
+constexpr AbsoluteTolerance<uint8_t> tolerance_qasymm8(1); /**< Tolerance for quantized tests */
+
+/** Activation function Dataset*/
+const auto ActivationFunctionsDataset = framework::dataset::make("ActivationInfo",
+{
+ ActivationLayerInfo(),
+ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 0.5f)
+});
+
+const auto data_precommit = combine(combine(zip(zip(zip(zip(zip(zip(zip(zip(zip(zip(
+ datasets::SmallDirectConv3DShapes(),
+ framework::dataset::make("StrideX", { 1, 5, 8 })),
+ framework::dataset::make("StrideY", { 1, 2, 3 })),
+ framework::dataset::make("StrideZ", { 1, 2, 1 })),
+ framework::dataset::make("PadX", { 0, 1, 2 })),
+ framework::dataset::make("PadY", { 0, 2, 1 })),
+ framework::dataset::make("PadZ", { 0, 3, 5 })),
+ framework::dataset::make("KernelWidth", { 3, 5, 9 })),
+ framework::dataset::make("KernelHeight", { 2, 1, 3 })),
+ framework::dataset::make("KernelDepth", { 1, 2, 3 })),
+ framework::dataset::make("NumKernels", { 2, 3, 8 })),
+ framework::dataset::make("HasBias", { true, false })),
+ ActivationFunctionsDataset);
+} // namespace
+
+TEST_SUITE(NEON)
+TEST_SUITE(Convolution3D)
+
+// *INDENT-OFF*
+// clang-format off
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
+ framework::dataset::make("InputInfo", { TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Mismatching data type input/weights
+ TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Mismatching input feature maps
+ TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid weights dimensions
+ TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NHWC), // Invalid data layout
+ TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid biases size
+ TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid biases dimensions
+ TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::F32, DataLayout::NDHWC), // Invalid output size
+ TensorInfo(TensorShape(27U, 13U, 2U, 4U), 1U, DataType::U32, DataLayout::NDHWC), // Invalid data type
+ }),
+ framework::dataset::make("WeightsInfo",{ TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F16),
+ TensorInfo(TensorShape(4U, 3U, 3U, 3U, 3U), 1U, DataType::F32),
+ TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U, 3U), 1U, DataType::F32),
+ TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32),
+ TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32),
+ TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32),
+ TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::F32),
+ TensorInfo(TensorShape(4U, 3U, 3U, 3U, 2U), 1U, DataType::U32),
+ })),
+ framework::dataset::make("BiasesInfo",{ TensorInfo(TensorShape(4U), 1U, DataType::F32),
+ TensorInfo(TensorShape(4U), 1U, DataType::F32),
+ TensorInfo(TensorShape(4U), 1U, DataType::F32),
+ TensorInfo(TensorShape(4U), 1U, DataType::F32),
+ TensorInfo(TensorShape(3U), 1U, DataType::F32),
+ TensorInfo(TensorShape(4U, 2U), 1U, DataType::F32),
+ TensorInfo(TensorShape(4U), 1U, DataType::F32),
+ TensorInfo(TensorShape(4U), 1U, DataType::F32),
+ })),
+ framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32),
+ TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32),
+ TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32),
+ TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32),
+ TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32),
+ TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::F32),
+ TensorInfo(TensorShape(26U, 11U, 4U), 1U, DataType::F32),
+ TensorInfo(TensorShape(25U, 11U, 4U), 1U, DataType::U32),
+ })),
+ framework::dataset::make("Expected", { false, false, false, false, false, false, false, false})),
+ input_info, weights_info, biases_info, output_info, expected)
+{
+ const Conv3dInfo conv3d_info(Size3D(1, 1, 1), Padding3D(0, 0, 0), ActivationLayerInfo(), Size3D(1U, 1U, 1U), DimensionRoundingType::FLOOR, false);
+ bool is_valid = bool(NEConv3D::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);
+}
+// clang-format on
+// *INDENT-ON*
+
+template <typename T>
+using NEDirectConvolution3DFixture = DirectConvolution3DValidationFixture<Tensor, Accessor, NEConv3D, T>;
+
+TEST_SUITE(Float)
+TEST_SUITE(FP32)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(data_precommit,
+ framework::dataset::make("DataType", DataType::F32)),
+ framework::dataset::make("DataLayout", { DataLayout::NDHWC })))
+{
+ // Validate output
+ validate(Accessor(_target), _reference, tolerance_fp32);
+}
+TEST_SUITE_END() // FP32
+
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+TEST_SUITE(FP16)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(data_precommit,
+ framework::dataset::make("DataType", DataType::F16)),
+ framework::dataset::make("DataLayout", { DataLayout::NDHWC })))
+{
+ // Validate output
+ validate(Accessor(_target), _reference, rel_tolerance_f16, tolerance_num, abs_tolerance_f16);
+}
+TEST_SUITE_END() // FP16
+#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+
+TEST_SUITE_END() // Float
+
+template <typename T>
+using NEDirectConvolution3DQuantizedFixture = DirectConvolution3DValidationQuantizedFixture<Tensor, Accessor, NEConv3D, T>;
+
+TEST_SUITE(Quantized)
+TEST_SUITE(QASYMM8)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DQuantizedFixture<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(Accessor(_target), _reference, tolerance_qasymm8);
+}
+
+TEST_SUITE_END() // QASYMM8
+
+TEST_SUITE(QASYMM8_SIGNED)
+FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DQuantizedFixture<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(Accessor(_target), _reference, tolerance_qasymm8);
+}
+
+TEST_SUITE_END() // QASYMM8_SIGNED
+TEST_SUITE_END() // Quantized
+
+TEST_SUITE_END() // Convolution3D
+TEST_SUITE_END() // Neon
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
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