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Diffstat (limited to 'tests/benchmark/fixtures/ROIPoolingLayerFixture.h')
| -rw-r--r-- | tests/benchmark/fixtures/ROIPoolingLayerFixture.h | 145 |
1 files changed, 0 insertions, 145 deletions
diff --git a/tests/benchmark/fixtures/ROIPoolingLayerFixture.h b/tests/benchmark/fixtures/ROIPoolingLayerFixture.h deleted file mode 100644 index 2c828272de..0000000000 --- a/tests/benchmark/fixtures/ROIPoolingLayerFixture.h +++ /dev/null @@ -1,145 +0,0 @@ -/* - * Copyright (c) 2017-2019 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_ROIPOOLINGLAYERFIXTURE -#define ARM_COMPUTE_TEST_ROIPOOLINGLAYERFIXTURE - -#include "arm_compute/core/TensorShape.h" -#include "arm_compute/core/Types.h" -#include "tests/Globals.h" -#include "tests/Utils.h" -#include "tests/framework/Fixture.h" - -#include <vector> - -namespace arm_compute -{ -namespace test -{ -namespace benchmark -{ -/** Fixture that can be used for NEON and CL */ -template <typename TensorType, typename Function, typename AccessorType, typename T> -class ROIPoolingLayerFixture : public framework::Fixture -{ -public: - template <typename...> - void setup(TensorShape input_shape, const ROIPoolingLayerInfo pool_info, TensorShape rois_shape, DataType data_type, int batches) - { - // Set batched in source and destination shapes - - TensorShape shape_dst; - rois_tensor = create_tensor<TensorType>(rois_shape, DataType::U16); - - input_shape.set(input_shape.num_dimensions(), batches); - shape_dst.set(0, pool_info.pooled_width()); - shape_dst.set(1, pool_info.pooled_height()); - shape_dst.set(2, input_shape.z()); - shape_dst.set(3, rois_shape[1]); - - // Create tensors - src = create_tensor<TensorType>(input_shape, data_type, 1); - dst = create_tensor<TensorType>(shape_dst, data_type, 1); - - // Create and configure function - roi_pool.configure(&src, &rois_tensor, &dst, pool_info); - - // Allocate tensors - rois_tensor.allocator()->allocate(); - src.allocator()->allocate(); - dst.allocator()->allocate(); - - // Create random ROIs - generate_rois(AccessorType(rois_tensor), input_shape, pool_info, rois_shape); - } - - void run() - { - roi_pool.run(); - } - - void sync() - { - sync_if_necessary<TensorType>(); - sync_tensor_if_necessary<TensorType>(dst); - } - - void teardown() - { - src.allocator()->free(); - dst.allocator()->free(); - } - -protected: - template <typename U> - void generate_rois(U &&rois, const TensorShape &shape, const ROIPoolingLayerInfo &pool_info, TensorShape rois_shape) - { - const size_t values_per_roi = rois_shape.x(); - const size_t num_rois = rois_shape.y(); - - std::mt19937 gen(library->seed()); - uint16_t *rois_ptr = static_cast<uint16_t *>(rois.data()); - - const float pool_width = pool_info.pooled_width(); - const float pool_height = pool_info.pooled_height(); - const float roi_scale = pool_info.spatial_scale(); - - // Calculate distribution bounds - const auto scaled_width = static_cast<uint16_t>((shape.x() / roi_scale) / pool_width); - const auto scaled_height = static_cast<uint16_t>((shape.y() / roi_scale) / pool_height); - const auto min_width = static_cast<uint16_t>(pool_width / roi_scale); - const auto min_height = static_cast<uint16_t>(pool_height / roi_scale); - - // Create distributions - std::uniform_int_distribution<int> dist_batch(0, shape[3] - 1); - std::uniform_int_distribution<uint16_t> dist_x1(0, scaled_width); - std::uniform_int_distribution<uint16_t> dist_y1(0, scaled_height); - std::uniform_int_distribution<uint16_t> dist_w(min_width, std::max(float(min_width), (pool_width - 2) * scaled_width)); - std::uniform_int_distribution<uint16_t> dist_h(min_height, std::max(float(min_height), (pool_height - 2) * scaled_height)); - - for(unsigned int pw = 0; pw < num_rois; ++pw) - { - const auto batch_idx = dist_batch(gen); - const auto x1 = dist_x1(gen); - const auto y1 = dist_y1(gen); - const auto x2 = x1 + dist_w(gen); - const auto y2 = y1 + dist_h(gen); - - rois_ptr[values_per_roi * pw] = batch_idx; - rois_ptr[values_per_roi * pw + 1] = x1; - rois_ptr[values_per_roi * pw + 2] = y1; - rois_ptr[values_per_roi * pw + 3] = x2; - rois_ptr[values_per_roi * pw + 4] = y2; - } - } - -private: - TensorType src{}; - TensorType dst{}; - TensorType rois_tensor{}; - Function roi_pool{}; -}; -} // namespace benchmark -} // namespace test -} // namespace arm_compute -#endif /* ARM_COMPUTE_TEST_ROIPOOLINGLAYERFIXTURE */ |