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author | Manuel Bottini <manuel.bottini@arm.com> | 2019-08-07 17:04:11 +0100 |
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committer | Manuel Bottini <manuel.bottini@arm.com> | 2019-09-09 15:16:51 +0000 |
commit | 9032ee32da54804806a3f26cbbf5a62b3c764f72 (patch) | |
tree | 6264e3def00f2d044b7c28e5159fe8bedb50653d /tests/benchmark/fixtures/PadLayerFixture.h | |
parent | ffd31defdb84d4ca1e24e9248d628c0075767302 (diff) | |
download | ComputeLibrary-9032ee32da54804806a3f26cbbf5a62b3c764f72.tar.gz |
MLCE-129: NEPad 30x slower than TensorFlow's implementation
Change-Id: I44770e6a3134c70c4bd58f890d06cb43c9bd8bff
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1853
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'tests/benchmark/fixtures/PadLayerFixture.h')
-rw-r--r-- | tests/benchmark/fixtures/PadLayerFixture.h | 109 |
1 files changed, 109 insertions, 0 deletions
diff --git a/tests/benchmark/fixtures/PadLayerFixture.h b/tests/benchmark/fixtures/PadLayerFixture.h new file mode 100644 index 0000000000..2f482a0abf --- /dev/null +++ b/tests/benchmark/fixtures/PadLayerFixture.h @@ -0,0 +1,109 @@ +/* + * Copyright (c) 2019 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_PADLAYERFIXTURE +#define ARM_COMPUTE_TEST_PADLAYERFIXTURE + +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "tests/Globals.h" +#include "tests/Utils.h" +#include "tests/framework/Fixture.h" + +namespace arm_compute +{ +namespace test +{ +namespace benchmark +{ +/** Fixture that can be used for NEON and CL */ + +template <typename TensorType, typename Accessor, typename Function, typename T> +class PaddingFixture : public framework::Fixture +{ +public: + template <typename...> + void setup(TensorShape shape, DataType data_type, const PaddingList &paddings, const PaddingMode mode) + { + PaddingList clamped_padding = paddings; + if(mode != PaddingMode::CONSTANT) + { + // Clamp padding to prevent applying more than is possible. + for(uint32_t i = 0; i < paddings.size(); ++i) + { + if(mode == PaddingMode::REFLECT) + { + clamped_padding[i].first = std::min(static_cast<uint64_t>(paddings[i].first), static_cast<uint64_t>(shape[i] - 1)); + clamped_padding[i].second = std::min(static_cast<uint64_t>(paddings[i].second), static_cast<uint64_t>(shape[i] - 1)); + } + else + { + clamped_padding[i].first = std::min(static_cast<uint64_t>(paddings[i].first), static_cast<uint64_t>(shape[i])); + clamped_padding[i].second = std::min(static_cast<uint64_t>(paddings[i].second), static_cast<uint64_t>(shape[i])); + } + } + } + + const PixelValue const_value = PixelValue(static_cast<T>(0)); + + TensorShape output_shape = arm_compute::misc::shape_calculator::compute_padded_shape(shape, paddings); + + // Create tensors + src = create_tensor<TensorType>(shape, data_type); + dst = create_tensor<TensorType>(output_shape, data_type); + + // Create and configure function + pad_layer.configure(&src, &dst, paddings, const_value, mode); + + // Allocate tensors + src.allocator()->allocate(); + dst.allocator()->allocate(); + } + + void run() + { + pad_layer.run(); + } + + void sync() + { + sync_if_necessary<TensorType>(); + sync_tensor_if_necessary<TensorType>(dst); + } + + void teardown() + { + src.allocator()->free(); + dst.allocator()->free(); + } + +private: + TensorType src{}; + TensorType dst{}; + Function pad_layer{}; +}; +} // namespace benchmark +} // namespace test +} // namespace arm_compute +#endif /* ARM_COMPUTE_TEST_PADLAYERFIXTURE */ |