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-/*
- * Copyright (c) 2017-2018 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_BATCHNORMALIZATIONLAYERFIXTURE
-#define ARM_COMPUTE_TEST_BATCHNORMALIZATIONLAYERFIXTURE
-
-#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"
-
-namespace arm_compute
-{
-namespace test
-{
-namespace benchmark
-{
-/** Fixture that can be used for NEON and CL */
-template <typename TensorType, typename Function, typename Accessor>
-class BatchNormalizationLayerFixture : public framework::Fixture
-{
-public:
- template <typename...>
- void setup(TensorShape tensor_shape, TensorShape param_shape, float epsilon, bool use_gamma, bool use_beta, ActivationLayerInfo act_info, DataType data_type, DataLayout data_layout, int batches)
- {
- // Set batched in source and destination shapes
-
- tensor_shape.set(tensor_shape.num_dimensions(), batches);
- if(data_layout == DataLayout::NHWC)
- {
- permute(tensor_shape, PermutationVector(2U, 0U, 1U));
- }
-
- // Create tensors
- src = create_tensor<TensorType>(tensor_shape, data_type, 1, QuantizationInfo(), data_layout);
- dst = create_tensor<TensorType>(tensor_shape, data_type, 1, QuantizationInfo(), data_layout);
- mean = create_tensor<TensorType>(param_shape, data_type, 1);
- variance = create_tensor<TensorType>(param_shape, data_type, 1);
- beta = create_tensor<TensorType>(param_shape, data_type, 1);
- gamma = create_tensor<TensorType>(param_shape, data_type, 1);
-
- // Create and configure function
- TensorType *beta_ptr = use_beta ? &beta : nullptr;
- TensorType *gamma_ptr = use_gamma ? &gamma : nullptr;
- batch_norm_layer.configure(&src, &dst, &mean, &variance, beta_ptr, gamma_ptr, epsilon, act_info);
-
- // Allocate tensors
- src.allocator()->allocate();
- dst.allocator()->allocate();
- mean.allocator()->allocate();
- variance.allocator()->allocate();
- beta.allocator()->allocate();
- gamma.allocator()->allocate();
- }
-
- void run()
- {
- batch_norm_layer.run();
- }
-
- void sync()
- {
- sync_if_necessary<TensorType>();
- sync_tensor_if_necessary<TensorType>(dst);
- }
-
- void teardown()
- {
- src.allocator()->free();
- dst.allocator()->free();
- mean.allocator()->free();
- variance.allocator()->free();
- beta.allocator()->free();
- gamma.allocator()->free();
- }
-
-private:
- TensorType src{};
- TensorType dst{};
- TensorType mean{};
- TensorType variance{};
- TensorType beta{};
- TensorType gamma{};
- Function batch_norm_layer{};
-};
-} // namespace benchmark
-} // namespace test
-} // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_BATCHNORMALIZATIONLAYERFIXTURE */