diff options
author | Moritz Pflanzer <moritz.pflanzer@arm.com> | 2017-07-26 11:49:37 +0100 |
---|---|---|
committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-09-17 14:16:42 +0100 |
commit | b3d2579b567eabd98fdb4861bf1380fefa18c9aa (patch) | |
tree | ec684767bf8e445162abb2b372cce46dc6d16443 /tests/validation_new | |
parent | 8594b1139fd72e541e725296bd8bb625496f3381 (diff) | |
download | ComputeLibrary-b3d2579b567eabd98fdb4861bf1380fefa18c9aa.tar.gz |
COMPMID-415: Move ConvolutionLayer to new validation
Change-Id: I1f40dff43142c4e2c096122bfa1ca08241ff80ff
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/81952
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'tests/validation_new')
-rw-r--r-- | tests/validation_new/CL/ConvolutionLayer.cpp | 186 | ||||
-rw-r--r-- | tests/validation_new/CL/DirectConvolutionLayer.cpp | 92 | ||||
-rw-r--r-- | tests/validation_new/CPP/ConvolutionLayer.cpp | 205 | ||||
-rw-r--r-- | tests/validation_new/CPP/ConvolutionLayer.h | 44 | ||||
-rw-r--r-- | tests/validation_new/NEON/ConvolutionLayer.cpp | 192 | ||||
-rw-r--r-- | tests/validation_new/NEON/DirectConvolutionLayer.cpp | 131 | ||||
-rw-r--r-- | tests/validation_new/fixtures/ConvolutionLayerFixture.h | 152 | ||||
-rw-r--r-- | tests/validation_new/fixtures/DirectConvolutionLayerFixture.h | 86 |
8 files changed, 1088 insertions, 0 deletions
diff --git a/tests/validation_new/CL/ConvolutionLayer.cpp b/tests/validation_new/CL/ConvolutionLayer.cpp new file mode 100644 index 0000000000..398feb7966 --- /dev/null +++ b/tests/validation_new/CL/ConvolutionLayer.cpp @@ -0,0 +1,186 @@ +/* + * Copyright (c) 2017 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 "framework/Asserts.h" +#include "framework/Macros.h" +#include "framework/datasets/Datasets.h" +#include "tests/CL/CLAccessor.h" +#include "tests/PaddingCalculator.h" +#include "tests/datasets_new/LargeConvolutionLayerDataset.h" +#include "tests/datasets_new/SmallConvolutionLayerDataset.h" +#include "tests/validation_new/Validation.h" +#include "tests/validation_new/fixtures/ConvolutionLayerFixture.h" +#include "tests/validation_new/half.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +constexpr float tolerance_f32 = 1e-03f; /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */ +constexpr float tolerance_f16 = 0.1f; /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */ +constexpr float tolerance_q = 1.0f; /**< Tolerance value for comparing reference's output against implementation's output for fixed point data types */ + +/** CNN data types */ +const auto CNNDataTypes = framework::dataset::make("DataType", +{ + DataType::F16, + DataType::F32, + DataType::QS8, + DataType::QS16, +}); +} // namespace + +TEST_SUITE(CL) +TEST_SUITE(ConvolutionLayer) + +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallConvolutionLayerDataset(), datasets::LargeConvolutionLayerDataset()), CNNDataTypes), + input_shape, weights_shape, bias_shape, output_shape, info, data_type) +{ + // Set fixed point position data type allowed + int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0; + + // Create tensors + CLTensor src = create_tensor<CLTensor>(input_shape, data_type, 1, fixed_point_position); + CLTensor weights = create_tensor<CLTensor>(weights_shape, data_type, 1, fixed_point_position); + CLTensor bias = create_tensor<CLTensor>(bias_shape, data_type, 1, fixed_point_position); + CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1, fixed_point_position); + + 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); + + // Create and configure function + CLConvolutionLayer conv; + conv.configure(&src, &weights, &bias, &dst, info); + + // 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 padding + //TODO(COMPMID-415) Need to validate padding? +} + +template <typename T> +using CLConvolutionLayerFixture = ConvolutionValidationFixture<CLTensor, CLAccessor, CLConvolutionLayer, T>; + +TEST_SUITE(Float) +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionLayerFixture<half_float::half>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("DataType", + DataType::F16))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f16); +} +FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionLayerFixture<half_float::half>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeConvolutionLayerDataset(), + framework::dataset::make("DataType", + DataType::F16))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f16); +} +TEST_SUITE_END() + +TEST_SUITE(FP32) +FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("DataType", + DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f32); +} +FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeConvolutionLayerDataset(), framework::dataset::make("DataType", + DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_f32); +} +TEST_SUITE_END() +TEST_SUITE_END() + +template <typename T> +using CLConvolutionLayerFixedPointFixture = ConvolutionValidationFixedPointFixture<CLTensor, CLAccessor, CLConvolutionLayer, T>; + +TEST_SUITE(Quantized) +TEST_SUITE(QS8) +// We test for fixed point precision [4,6] +FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("DataType", + DataType::QS8)), + framework::dataset::make("FractionalBits", 4, 7))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_q); +} +FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeConvolutionLayerDataset(), + framework::dataset::make("DataType", + DataType::QS8)), + framework::dataset::make("FractionalBits", 4, 7))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_q); +} +TEST_SUITE_END() + +TEST_SUITE(QS16) +// Testing for fixed point position [1,14) +FIXTURE_DATA_TEST_CASE(RunSmall, CLConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("DataType", + DataType::QS16)), + framework::dataset::make("FractionalBits", 1, 14))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_q); +} +FIXTURE_DATA_TEST_CASE(RunLarge, CLConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeConvolutionLayerDataset(), + framework::dataset::make("DataType", + DataType::QS16)), + framework::dataset::make("FractionalBits", 1, 14))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_q); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE_END() +TEST_SUITE_END() +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation_new/CL/DirectConvolutionLayer.cpp b/tests/validation_new/CL/DirectConvolutionLayer.cpp new file mode 100644 index 0000000000..9cffabae42 --- /dev/null +++ b/tests/validation_new/CL/DirectConvolutionLayer.cpp @@ -0,0 +1,92 @@ +/* + * Copyright (c) 2017 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/Types.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/CL/CLTensorAllocator.h" +#include "arm_compute/runtime/CL/functions/CLDirectConvolutionLayer.h" +#include "framework/Asserts.h" +#include "framework/Macros.h" +#include "framework/datasets/Datasets.h" +#include "tests/CL/CLAccessor.h" +#include "tests/PaddingCalculator.h" +#include "tests/datasets_new/ShapeDatasets.h" +#include "tests/validation_new/Validation.h" +#include "tests/validation_new/fixtures/DirectConvolutionLayerFixture.h" +#include "tests/validation_new/half.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +constexpr float tolerance_fp16 = 0.1f; /**< Tolerance for floating point tests */ +constexpr float tolerance_fp32 = 0.001f; /**< Tolerance for floating point tests */ + +/** Direct convolution data set. */ +const auto data = combine(datasets::SmallDirectConvolutionShapes(), + combine(framework::dataset::make("StrideX", 1, 3), + combine(framework::dataset::make("StrideY", 1, 3), + combine(concat(combine(framework::dataset::make("PadX", 0), + combine(framework::dataset::make("PadY", 0), + framework::dataset::make("KernelSize", 1))), + combine(framework::dataset::make("PadX", 0, 2), + combine(framework::dataset::make("PadY", 0, 2), + framework::dataset::make("KernelSize", 3)))), + framework::dataset::make("NumKernels", { 1, 4, 8, 16 }))))); +} // namespace + +TEST_SUITE(CL) +TEST_SUITE(DirectConvolutionLayer) + +//TODO(COMPMID-415): Configuration tests? + +template <typename T> +using CLDirectConvolutionLayerFixture = DirectConvolutionValidationFixture<CLTensor, CLAccessor, CLDirectConvolutionLayer, T>; + +TEST_SUITE(Float) +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerFixture<half_float::half>, framework::DatasetMode::ALL, combine(data, framework::dataset::make("DataType", DataType::F16))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp16); +} +TEST_SUITE_END() + +TEST_SUITE(FP32) +FIXTURE_DATA_TEST_CASE(Run, CLDirectConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(data, framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(CLAccessor(_target), _reference, tolerance_fp32); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE_END() +TEST_SUITE_END() +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation_new/CPP/ConvolutionLayer.cpp b/tests/validation_new/CPP/ConvolutionLayer.cpp new file mode 100644 index 0000000000..a24621a3f2 --- /dev/null +++ b/tests/validation_new/CPP/ConvolutionLayer.cpp @@ -0,0 +1,205 @@ +/* + * Copyright (c) 2017 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 "ConvolutionLayer.h" + +#include "tests/validation_new/FixedPoint.h" +#include "tests/validation_new/Helpers.h" +#include "tests/validation_new/half.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace reference +{ +namespace +{ +inline bool is_valid_pixel(int i, int min, int max) +{ + return (i >= min && i < max); +} + +// 3D convolution for floating point type +template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type = 0> +void convolution3d(const T *in, const T *weights, const T *bias, T *out, int xi, int yi, int width_in, int height_in, int depth_in, int width_weights, int height_weights, int fixed_point_position) +{ + ARM_COMPUTE_UNUSED(fixed_point_position); + + const int half_width_weights = width_weights / 2; + const int half_height_weights = height_weights / 2; + + // Reset accumulator + T acc(0); + + // Compute a 2D convolution for each IFM and accumulate the result + for(int ifm = 0; ifm < depth_in; ++ifm) + { + // Compute the offset for the input slice + const int offset_slice_in = xi + yi * width_in + ifm * width_in * height_in; + + // Compute 2D convolution + for(int yk = -half_height_weights; yk <= half_height_weights; ++yk) + { + for(int xk = -half_width_weights; xk <= half_width_weights; ++xk) + { + // Check if the pixel is out-of-bound + if(is_valid_pixel(xi + xk, 0, width_in) && is_valid_pixel(yi + yk, 0, height_in)) + { + const int idx = xk + half_width_weights; + const int idy = yk + half_height_weights; + + const T i_value = in[offset_slice_in + xk + yk * width_in]; + const T w_value = weights[idx + idy * width_weights + ifm * width_weights * height_weights]; + + acc += i_value * w_value; + } + } + } + } + + // Accumulate the bias and store the result + *out = acc + (*bias); +} + +// 3D convolution for fixed point type +template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type = 0> +void convolution3d(const T *in, const T *weights, const T *bias, T *out, int xi, int yi, int width_in, int height_in, int depth_in, int width_weights, int height_weights, + int fixed_point_position) +{ + const int half_width_weights = width_weights / 2; + const int half_height_weights = height_weights / 2; + + using namespace fixed_point_arithmetic; + using promoted_type = fixed_point_arithmetic::traits::promote_t<T>; + + // Reset accumulator + fixed_point<promoted_type> acc(0, fixed_point_position); + + // Compute a 2D convolution for each IFM and accumulate the result + for(int ifm = 0; ifm < depth_in; ++ifm) + { + // Compute the offset for the input slice + const int offset_slice_in = xi + yi * width_in + ifm * width_in * height_in; + + // Compute 2D convolution + for(int yk = -half_height_weights; yk <= half_height_weights; ++yk) + { + for(int xk = -half_width_weights; xk <= half_width_weights; ++xk) + { + // Check if the pixel is out-of-bound + if(is_valid_pixel(xi + xk, 0, width_in) && is_valid_pixel(yi + yk, 0, height_in)) + { + const int idx = xk + half_width_weights; + const int idy = yk + half_height_weights; + + const fixed_point<promoted_type> i_value(in[offset_slice_in + xk + yk * width_in], fixed_point_position, true); + const fixed_point<promoted_type> w_value(weights[idx + idy * width_weights + ifm * width_weights * height_weights], fixed_point_position, true); + const fixed_point<promoted_type> iw = i_value * w_value; + acc = iw + acc; + } + } + } + } + + // Get the bias + const fixed_point<promoted_type> b(*bias, fixed_point_position, true); + + // Accumulate the bias and covert back + acc = acc + b; + fixed_point<T> res(acc); + *out = res.raw(); +} +} // namespace + +template <typename T> +SimpleTensor<T> convolution_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<T> &bias, const TensorShape &output_shape, const PadStrideInfo &info) +{ + // Create reference + SimpleTensor<T> dst{ output_shape, src.data_type(), 1, src.fixed_point_position() }; + + // Compute reference + const int width_in = src.shape().x(); + const int height_in = src.shape().y(); + const int depth_in = src.shape().z(); + const int width_out = dst.shape().x(); + const int height_out = dst.shape().y(); + const int depth_out = dst.shape().z(); + const int width_weights = weights.shape().x(); + const int height_weights = weights.shape().y(); + const int depth_weights = weights.shape().z(); + const int pad_xi = std::min(static_cast<int>(info.pad().first), width_weights / 2); + const int pad_yi = std::min(static_cast<int>(info.pad().second), height_weights / 2); + const int start_xi = width_weights / 2 - pad_xi; + const int start_yi = height_weights / 2 - pad_yi; + const int end_xi = width_in - start_xi; + const int end_yi = height_in - start_yi; + const int stride_xi = info.stride().first; + const int stride_yi = info.stride().second; + const int num_batches = src.shape().total_size() / (width_in * height_in * depth_in); + + for(int r = 0; r < num_batches; ++r) + { + for(int yi = start_yi; yi < end_yi; yi += stride_yi) + { + for(int xi = start_xi; xi < end_xi; xi += stride_xi) + { + for(int ofm = 0; ofm < depth_out; ++ofm) + { + // Compute input and output offsets + const int offset_in = r * width_in * height_in * depth_in; + const int xo = (xi - start_xi) / stride_xi; + const int yo = (yi - start_yi) / stride_yi; + const int offset_out = xo + yo * width_out + ofm * width_out * height_out + r * width_out * height_out * depth_out; + + // Compute 3D convolution + convolution3d(src.data() + offset_in, + weights.data() + ofm * width_weights * height_weights * depth_weights, + bias.data() + ofm, + dst.data() + offset_out, + xi, yi, + width_in, height_in, depth_in, + width_weights, height_weights, + src.fixed_point_position()); + } + } + } + } + + return dst; +} + +template SimpleTensor<float> convolution_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &weights, const SimpleTensor<float> &bias, const TensorShape &output_shape, + const PadStrideInfo &info); +template SimpleTensor<half_float::half> convolution_layer(const SimpleTensor<half_float::half> &src, const SimpleTensor<half_float::half> &weights, const SimpleTensor<half_float::half> &bias, + const TensorShape &output_shape, const PadStrideInfo &info); +template SimpleTensor<qint8_t> convolution_layer(const SimpleTensor<qint8_t> &src, const SimpleTensor<qint8_t> &weights, const SimpleTensor<qint8_t> &bias, const TensorShape &output_shape, + const PadStrideInfo &info); +template SimpleTensor<qint16_t> convolution_layer(const SimpleTensor<qint16_t> &src, const SimpleTensor<qint16_t> &weights, const SimpleTensor<qint16_t> &bias, const TensorShape &output_shape, + const PadStrideInfo &info); +} // namespace reference +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation_new/CPP/ConvolutionLayer.h b/tests/validation_new/CPP/ConvolutionLayer.h new file mode 100644 index 0000000000..fd46567910 --- /dev/null +++ b/tests/validation_new/CPP/ConvolutionLayer.h @@ -0,0 +1,44 @@ +/* + * Copyright (c) 2017 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. + */ +#ifndef __ARM_COMPUTE_TEST_CONVOLUTION_LAYER_H__ +#define __ARM_COMPUTE_TEST_CONVOLUTION_LAYER_H__ + +#include "tests/validation_new/Helpers.h" +#include "tests/validation_new/SimpleTensor.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace reference +{ +template <typename T> +SimpleTensor<T> convolution_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<T> &bias, const TensorShape &output_shape, const PadStrideInfo &info); +} // namespace reference +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* __ARM_COMPUTE_TEST_CONVOLUTION_LAYER_H__ */ diff --git a/tests/validation_new/NEON/ConvolutionLayer.cpp b/tests/validation_new/NEON/ConvolutionLayer.cpp new file mode 100644 index 0000000000..af33cc0707 --- /dev/null +++ b/tests/validation_new/NEON/ConvolutionLayer.cpp @@ -0,0 +1,192 @@ +/* + * Copyright (c) 2017 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/Types.h" +#include "arm_compute/runtime/NEON/functions/NEConvolutionLayer.h" +#include "arm_compute/runtime/Tensor.h" +#include "arm_compute/runtime/TensorAllocator.h" +#include "framework/Asserts.h" +#include "framework/Macros.h" +#include "framework/datasets/Datasets.h" +#include "tests/NEON/Accessor.h" +#include "tests/PaddingCalculator.h" +#include "tests/datasets_new/LargeConvolutionLayerDataset.h" +#include "tests/datasets_new/SmallConvolutionLayerDataset.h" +#include "tests/validation_new/Validation.h" +#include "tests/validation_new/fixtures/ConvolutionLayerFixture.h" +#include "tests/validation_new/half.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +const float tolerance_f32 = 1e-03f; /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */ +#ifdef ARM_COMPUTE_ENABLE_FP16 +const float tolerance_f16 = 0.01f; /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */ +#endif /* ARM_COMPUTE_ENABLE_FP16 */ +const float tolerance_q = 1.0f; /**< Tolerance value for comparing reference's output against implementation's output for fixed point data types */ + +/** CNN data types */ +const auto CNNDataTypes = framework::dataset::make("DataType", +{ +#ifdef ARM_COMPUTE_ENABLE_FP16 + DataType::F16, +#endif /* ARM_COMPUTE_ENABLE_FP16 */ + DataType::F32, + DataType::QS8, + DataType::QS16, +}); +} // namespace + +TEST_SUITE(NEON) +TEST_SUITE(ConvolutionLayer) + +DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallConvolutionLayerDataset(), datasets::LargeConvolutionLayerDataset()), CNNDataTypes), + input_shape, weights_shape, bias_shape, output_shape, info, data_type) +{ + // Set fixed point position data type allowed + int fixed_point_position = is_data_type_fixed_point(data_type) ? 3 : 0; + + // Create tensors + Tensor src = create_tensor<Tensor>(input_shape, data_type, 1, fixed_point_position); + Tensor weights = create_tensor<Tensor>(weights_shape, data_type, 1, fixed_point_position); + Tensor bias = create_tensor<Tensor>(bias_shape, data_type, 1, fixed_point_position); + Tensor dst = create_tensor<Tensor>(output_shape, data_type, 1, fixed_point_position); + + 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); + + // Create and configure function + NEConvolutionLayer conv; + conv.configure(&src, &weights, &bias, &dst, info); + + // 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 padding + //TODO(COMPMID-415) Need to validate padding? +} + +template <typename T> +using NEConvolutionLayerFixture = ConvolutionValidationFixture<Tensor, Accessor, NEConvolutionLayer, T>; + +TEST_SUITE(Float) +#ifdef ARM_COMPUTE_ENABLE_FP16 +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionLayerFixture<half_float::half>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("DataType", + DataType::F16))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_f16); +} +FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionLayerFixture<half_float::half>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeConvolutionLayerDataset(), + framework::dataset::make("DataType", + DataType::F16))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_f16); +} +TEST_SUITE_END() +#endif /* ARM_COMPUTE_ENABLE_FP16 */ + +TEST_SUITE(FP32) +FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::SmallConvolutionLayerDataset(), framework::dataset::make("DataType", + DataType::F32))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_f32); +} +FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionLayerFixture<float>, framework::DatasetMode::NIGHTLY, combine(datasets::LargeConvolutionLayerDataset(), framework::dataset::make("DataType", + DataType::F32))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_f32); +} +TEST_SUITE_END() +TEST_SUITE_END() + +template <typename T> +using NEConvolutionLayerFixedPointFixture = ConvolutionValidationFixedPointFixture<Tensor, Accessor, NEConvolutionLayer, T>; + +TEST_SUITE(Quantized) +TEST_SUITE(QS8) +// We test for fixed point precision [4,6] +FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("DataType", + DataType::QS8)), + framework::dataset::make("FractionalBits", 4, 7))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_q); +} +FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeConvolutionLayerDataset(), + framework::dataset::make("DataType", + DataType::QS8)), + framework::dataset::make("FractionalBits", 4, 7))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_q); +} +TEST_SUITE_END() + +TEST_SUITE(QS16) +// Testing for fixed point position [1,14) +FIXTURE_DATA_TEST_CASE(RunSmall, NEConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallConvolutionLayerDataset(), + framework::dataset::make("DataType", + DataType::QS16)), + framework::dataset::make("FractionalBits", 1, 14))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_q); +} +FIXTURE_DATA_TEST_CASE(RunLarge, NEConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeConvolutionLayerDataset(), + framework::dataset::make("DataType", + DataType::QS16)), + framework::dataset::make("FractionalBits", 1, 14))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_q); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE_END() +TEST_SUITE_END() +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation_new/NEON/DirectConvolutionLayer.cpp b/tests/validation_new/NEON/DirectConvolutionLayer.cpp new file mode 100644 index 0000000000..a46f5a5dcc --- /dev/null +++ b/tests/validation_new/NEON/DirectConvolutionLayer.cpp @@ -0,0 +1,131 @@ +/* + * Copyright (c) 2017 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/Types.h" +#include "arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h" +#include "arm_compute/runtime/Tensor.h" +#include "arm_compute/runtime/TensorAllocator.h" +#include "framework/Asserts.h" +#include "framework/Macros.h" +#include "framework/datasets/Datasets.h" +#include "tests/NEON/Accessor.h" +#include "tests/PaddingCalculator.h" +#include "tests/datasets_new/ShapeDatasets.h" +#include "tests/validation_new/Validation.h" +#include "tests/validation_new/fixtures/DirectConvolutionLayerFixture.h" +#include "tests/validation_new/half.h" + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +namespace +{ +constexpr float tolerance_qs = 1.f; /**< Tolerance for fixed point tests */ +#ifdef ARM_COMPUTE_ENABLE_FP16 +constexpr float tolerance_fp16 = 0.01f; /**< Tolerance for half precision floating point tests */ +#endif /* ARM_COMPUTE_ENABLE_FP16 */ +constexpr float tolerance_fp32 = 0.001f; /**< Tolerance for floating point tests */ + +/** Direct convolution data set. */ +const auto data = combine(datasets::SmallDirectConvolutionShapes(), + combine(framework::dataset::make("StrideX", 1, 3), + combine(framework::dataset::make("StrideY", 1, 3), + combine(concat(combine(framework::dataset::make("PadX", 0), + combine(framework::dataset::make("PadY", 0), + framework::dataset::make("KernelSize", 1))), + combine(framework::dataset::make("PadX", 0, 2), + combine(framework::dataset::make("PadY", 0, 2), + framework::dataset::make("KernelSize", 3)))), + framework::dataset::make("NumKernels", { 1, 4, 8, 16 }))))); + +/** Direct convolution QS16 data set. */ +const auto data_qs16 = combine(datasets::SmallDirectConvolutionShapes(), + combine(framework::dataset::make("StrideX", 1, 3), + combine(framework::dataset::make("StrideY", 1, 3), + combine(framework::dataset::make("PadX", 0), + combine(framework::dataset::make("PadY", 0), + combine(framework::dataset::make("KernelSize", 1), + framework::dataset::make("NumKernels", { 1, 4, 8, 16 }))))))); +} // namespace + +TEST_SUITE(NEON) +TEST_SUITE(DirectConvolutionLayer) + +//TODO(COMPMID-415): Configuration tests? + +template <typename T> +using NEDirectConvolutionLayerFixture = DirectConvolutionValidationFixture<Tensor, Accessor, NEDirectConvolutionLayer, T>; + +TEST_SUITE(Float) +#ifdef ARM_COMPUTE_ENABLE_FP16 +TEST_SUITE(FP16) +FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixture<half_float::half>, framework::DatasetMode::ALL, combine(data, framework::dataset::make("DataType", DataType::F16))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp16); +} +TEST_SUITE_END() +#endif /* ARM_COMPUTE_ENABLE_FP16 */ + +TEST_SUITE(FP32) +FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixture<float>, framework::DatasetMode::ALL, combine(data, framework::dataset::make("DataType", DataType::F32))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_fp32); +} +TEST_SUITE_END() +TEST_SUITE_END() + +template <typename T> +using NEDirectConvolutionLayerFixedPointFixture = DirectConvolutionValidationFixedPointFixture<Tensor, Accessor, NEDirectConvolutionLayer, T>; + +TEST_SUITE(Quantized) +TEST_SUITE(QS8) +// We test for fixed point precision [4,6] +FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixedPointFixture<int8_t>, framework::DatasetMode::ALL, combine(combine(data, framework::dataset::make("DataType", DataType::QS8)), + framework::dataset::make("FractionalBits", 4, 7))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qs); +} +TEST_SUITE_END() + +TEST_SUITE(QS16) +// We test for fixed point precision [4,13] +FIXTURE_DATA_TEST_CASE(Run, NEDirectConvolutionLayerFixedPointFixture<int16_t>, framework::DatasetMode::ALL, combine(combine(data_qs16, framework::dataset::make("DataType", DataType::QS16)), + framework::dataset::make("FractionalBits", 4, 14))) +{ + // Validate output + validate(Accessor(_target), _reference, tolerance_qs); +} +TEST_SUITE_END() +TEST_SUITE_END() + +TEST_SUITE_END() +TEST_SUITE_END() +} // namespace validation +} // namespace test +} // namespace arm_compute diff --git a/tests/validation_new/fixtures/ConvolutionLayerFixture.h b/tests/validation_new/fixtures/ConvolutionLayerFixture.h new file mode 100644 index 0000000000..25a53d0c1d --- /dev/null +++ b/tests/validation_new/fixtures/ConvolutionLayerFixture.h @@ -0,0 +1,152 @@ +/* + * Copyright (c) 2017 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. + */ +#ifndef ARM_COMPUTE_TEST_CONVOLUTION_LAYER_FIXTURE +#define ARM_COMPUTE_TEST_CONVOLUTION_LAYER_FIXTURE + +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "framework/Asserts.h" +#include "framework/Fixture.h" +#include "tests/AssetsLibrary.h" +#include "tests/Globals.h" +#include "tests/IAccessor.h" +#include "tests/validation_new/CPP/ConvolutionLayer.h" +#include "tests/validation_new/Helpers.h" + +#include <random> + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ConvolutionValidationFixedPointFixture : public framework::Fixture +{ +public: + template <typename...> + void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, DataType data_type, int fractional_bits) + { + _fractional_bits = fractional_bits; + _data_type = data_type; + + _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, fractional_bits); + _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, fractional_bits); + } + +protected: + template <typename U> + void fill(U &&tensor, int i) + { + switch(tensor.data_type()) + { + case DataType::F16: + case DataType::F32: + { + std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + library->fill(tensor, distribution, i); + break; + } + default: + library->fill_tensor_uniform(tensor, i); + } + } + + TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, + DataType data_type, int fixed_point_position) + { + // Create tensors + TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, fixed_point_position); + TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, fixed_point_position); + TensorType bias = create_tensor<TensorType>(bias_shape, data_type, 1, fixed_point_position); + TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, fixed_point_position); + + // Create and configure function + FunctionType conv; + conv.configure(&src, &weights, &bias, &dst, info); + + 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); + + // Allocate tensors + src.allocator()->allocate(); + weights.allocator()->allocate(); + bias.allocator()->allocate(); + dst.allocator()->allocate(); + + 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); + + // Fill tensors + fill(AccessorType(src), 0); + fill(AccessorType(weights), 1); + fill(AccessorType(bias), 2); + + // Compute NEConvolutionLayer function + conv.run(); + + return dst; + } + + SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info, + DataType data_type, int fixed_point_position) + { + // Create reference + SimpleTensor<T> src{ input_shape, data_type, 1, fixed_point_position }; + SimpleTensor<T> weights{ weights_shape, data_type, 1, fixed_point_position }; + SimpleTensor<T> bias{ bias_shape, data_type, 1, fixed_point_position }; + + // Fill reference + fill(src, 0); + fill(weights, 1); + fill(bias, 2); + + return reference::convolution_layer<T>(src, weights, bias, output_shape, info); + } + + TensorType _target{}; + SimpleTensor<T> _reference{}; + int _fractional_bits{}; + DataType _data_type{}; +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class ConvolutionValidationFixture : public ConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, DataType data_type) + { + ConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, data_type, 0); + } +}; +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_CONVOLUTION_LAYER_FIXTURE */ diff --git a/tests/validation_new/fixtures/DirectConvolutionLayerFixture.h b/tests/validation_new/fixtures/DirectConvolutionLayerFixture.h new file mode 100644 index 0000000000..0d138b47d9 --- /dev/null +++ b/tests/validation_new/fixtures/DirectConvolutionLayerFixture.h @@ -0,0 +1,86 @@ +/* + * Copyright (c) 2017 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/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "framework/Asserts.h" +#include "framework/Fixture.h" +#include "tests/AssetsLibrary.h" +#include "tests/Globals.h" +#include "tests/IAccessor.h" +#include "tests/validation_new/CPP/ConvolutionLayer.h" +#include "tests/validation_new/Helpers.h" +#include "tests/validation_new/fixtures/ConvolutionLayerFixture.h" + +#include <random> + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class DirectConvolutionValidationFixedPointFixture : public ConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, int fractional_bits) + { + const TensorShape weights_shape(kernel_size, kernel_size, input_shape.z(), num_kernels); + const TensorShape bias_shape(num_kernels); + const PadStrideInfo info(stride_x, stride_y, pad_x, pad_y, DimensionRoundingType::FLOOR); + const TensorShape output_shape = get_output_shape(input_shape, weights_shape, info); + + ConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, data_type, fractional_bits); + } + +private: + TensorShape get_output_shape(TensorShape in_shape, TensorShape kernel_shape, const PadStrideInfo &info) + { + TensorShape out_shape(in_shape); + const std::pair<unsigned int, unsigned int> scaled_dims = scaled_dimensions(in_shape.x(), + in_shape.y(), + kernel_shape.x(), + kernel_shape.y(), + info); + out_shape.set(0, scaled_dims.first); + out_shape.set(1, scaled_dims.second); + out_shape.set(2, kernel_shape[3]); + return out_shape; + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class DirectConvolutionValidationFixture : public DirectConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type) + { + DirectConvolutionValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0); + } +}; +} // namespace validation +} // namespace test +} // namespace arm_compute |