From f727ef49e2109bdac105dd6575d2e336adf780a3 Mon Sep 17 00:00:00 2001 From: Freddie Liardet Date: Mon, 18 Oct 2021 13:28:57 +0100 Subject: Add uint8/int8 support to cpu conv3d Add support for qasymm8/qasymm8_signed in cpu conv3d. Resolves: COMPMID-4665 Signed-off-by: Freddie Liardet Change-Id: I2450bb6f24969745c8b936f4b657bd406b788c57 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6478 Tested-by: Arm Jenkins Reviewed-by: Giorgio Arena Comments-Addressed: Arm Jenkins --- tests/validation/NEON/Convolution3D.cpp | 224 ++++++++++++++++++++++++++++++++ 1 file changed, 224 insertions(+) create mode 100644 tests/validation/NEON/Convolution3D.cpp (limited to 'tests/validation/NEON/Convolution3D.cpp') diff --git a/tests/validation/NEON/Convolution3D.cpp b/tests/validation/NEON/Convolution3D.cpp new file mode 100644 index 0000000000..1bfac900c0 --- /dev/null +++ b/tests/validation/NEON/Convolution3D.cpp @@ -0,0 +1,224 @@ +/* + * 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 rel_tolerance_f16(half_float::half(0.2f)); /**< Relative tolerance value for FP16 types */ +const AbsoluteTolerance 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 tolerance_fp32(0.001f); /**< Tolerance for floating point tests */ +constexpr AbsoluteTolerance 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 + }), + 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), + })), + 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), + })), + 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), + })), + framework::dataset::make("Expected", { 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 +using NEDirectConvolution3DFixture = DirectConvolution3DValidationFixture; + +TEST_SUITE(Float) +TEST_SUITE(FP32) +FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DFixture, 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, 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 +using NEDirectConvolution3DQuantizedFixture = DirectConvolution3DValidationQuantizedFixture; + +TEST_SUITE(Quantized) +TEST_SUITE(QASYMM8) +FIXTURE_DATA_TEST_CASE(RunSmall, NEDirectConvolution3DQuantizedFixture, 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, 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 -- cgit v1.2.1