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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_DIRECTCONVOLUTIONLAYERFIXTURE
+#define ARM_COMPUTE_TEST_DIRECTCONVOLUTIONLAYERFIXTURE
+
+#include "arm_compute/core/Error.h"
+#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 DirectConvolutionLayerFixture : public framework::Fixture
+{
+public:
+ template <typename...>
+ void setup(TensorShape src_shape, TensorShape weights_shape, TensorShape biases_shape, TensorShape dst_shape, PadStrideInfo info, Size2D dilation, DataType data_type, int batches)
+ {
+ ARM_COMPUTE_UNUSED(dilation);
+
+ // Set batched in source and destination shapes
+ const unsigned int fixed_point_position = 4;
+ src_shape.set(3 /* batch */, batches);
+ dst_shape.set(3 /* batch */, batches);
+ DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
+
+ // Create tensors
+ src = create_tensor<TensorType>(src_shape, data_type, 1, fixed_point_position);
+ weights = create_tensor<TensorType>(weights_shape, data_type, 1, fixed_point_position);
+ biases = create_tensor<TensorType>(biases_shape, bias_data_type, 1, fixed_point_position);
+ dst = create_tensor<TensorType>(dst_shape, data_type, 1, fixed_point_position);
+
+ // Create and configure function
+ conv_layer.configure(&src, &weights, &biases, &dst, info);
+
+ // Allocate tensors
+ src.allocator()->allocate();
+ weights.allocator()->allocate();
+ biases.allocator()->allocate();
+ dst.allocator()->allocate();
+ }
+
+ void run()
+ {
+ conv_layer.run();
+ }
+
+ void sync()
+ {
+ sync_if_necessary<TensorType>();
+ sync_tensor_if_necessary<TensorType>(dst);
+ }
+
+ void teardown()
+ {
+ src.allocator()->free();
+ weights.allocator()->free();
+ biases.allocator()->free();
+ dst.allocator()->free();
+ }
+
+private:
+ TensorType src{};
+ TensorType weights{};
+ TensorType biases{};
+ TensorType dst{};
+ Function conv_layer{};
+};
+} // namespace benchmark
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_DIRECTCONVOLUTIONLAYERFIXTURE */