/* * 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_DEPTHWISESEPARABLECONVOLUTIONLAYERFIXTURE #define ARM_COMPUTE_TEST_DEPTHWISESEPARABLECONVOLUTIONLAYERFIXTURE #include "arm_compute/core/TensorShape.h" #include "arm_compute/core/Types.h" #include "framework/Fixture.h" #include "tests/Globals.h" #include "tests/Utils.h" namespace arm_compute { namespace test { /** Fixture that can be used for NEON and CL */ template class DepthwiseSeparableConvolutionLayerFixture : public framework::Fixture { public: template void setup(TensorShape src_shape, TensorShape depthwise_weights_shape, TensorShape depthwise_out_shape, TensorShape pointwise_weights_shape, TensorShape biases_shape, TensorShape dst_shape, PadStrideInfo pad_stride_depthwise_info, PadStrideInfo pad_stride_pointwise_info, DataType data_type, int batches) { // Set batched in source and destination shapes const unsigned int fixed_point_position = 4; src_shape.set(3 /* batch */, batches); depthwise_out_shape.set(3 /* batch */, batches); dst_shape.set(3 /* batch */, batches); src = create_tensor(src_shape, data_type, 1, fixed_point_position); depthwise_weights = create_tensor(depthwise_weights_shape, data_type, 1, fixed_point_position); depthwise_out = create_tensor(depthwise_out_shape, data_type, 1, fixed_point_position); pointwise_weights = create_tensor(pointwise_weights_shape, data_type, 1, fixed_point_position); biases = create_tensor(biases_shape, data_type, 1, fixed_point_position); dst = create_tensor(dst_shape, data_type, 1, fixed_point_position); // Create and configure function depth_sep_conv_layer.configure(&src, &depthwise_weights, &depthwise_out, &pointwise_weights, &biases, &dst, pad_stride_depthwise_info, pad_stride_pointwise_info); // Allocate tensors src.allocator()->allocate(); depthwise_weights.allocator()->allocate(); depthwise_out.allocator()->allocate(); pointwise_weights.allocator()->allocate(); biases.allocator()->allocate(); dst.allocator()->allocate(); // Fill tensors library->fill_tensor_uniform(Accessor(src), 0); library->fill_tensor_uniform(Accessor(depthwise_weights), 1); library->fill_tensor_uniform(Accessor(pointwise_weights), 2); library->fill_tensor_uniform(Accessor(biases), 3); } void run() { depth_sep_conv_layer.run(); } void teardown() { src.allocator()->free(); depthwise_weights.allocator()->free(); depthwise_out.allocator()->free(); pointwise_weights.allocator()->free(); biases.allocator()->free(); dst.allocator()->free(); } private: TensorType src{}; TensorType depthwise_weights{}; TensorType depthwise_out{}; TensorType pointwise_weights{}; TensorType biases{}; TensorType dst{}; Function depth_sep_conv_layer{}; }; } // namespace test } // namespace arm_compute #endif /* ARM_COMPUTE_TEST_DEPTHWISESEPARABLECONVOLUTIONLAYERFIXTURE */