| /* |
| * 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_GC |
| #error "This example needs to be built with -DARM_COMPUTE_GC" |
| #endif /* ARM_COMPUTE_GC */ |
| |
| #include "arm_compute/runtime/GLES_COMPUTE/GCFunctions.h" |
| #include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h" |
| #include "half/half.hpp" |
| #include "utils/Utils.h" |
| |
| using namespace arm_compute; |
| using namespace utils; |
| |
| class GCDCExample : public Example |
| { |
| public: |
| bool do_setup(int argc, char **argv) override |
| { |
| ARM_COMPUTE_UNUSED(argc); |
| ARM_COMPUTE_UNUSED(argv); |
| |
| // init instance |
| GCScheduler::get().default_init(); |
| |
| const TensorShape src_shape = TensorShape{ 11U /* W */, 13U /* H */, 4U /* C */, 3U /* N */ }; |
| const unsigned int kernel_size = 3; |
| const int stride_x = 1; |
| const int stride_y = 1; |
| const int pad_x = 0; |
| const int pad_y = 0; |
| const unsigned int num_kernels = 256; |
| const DataType data_type = DataType::F16; |
| |
| // generate shape |
| const TensorShape weights_shape(kernel_size, kernel_size, src_shape.z(), num_kernels); |
| const TensorShape bias_shape(num_kernels); |
| const PadStrideInfo pad_info(stride_x, stride_y, pad_x, pad_y, DimensionRoundingType::FLOOR); |
| |
| // output shape should be 9*11*256*3 (W*H*C*N) |
| const TensorShape dst_shape = get_output_shape(src_shape, weights_shape, pad_info); |
| |
| // create tensors |
| src.allocator()->init(TensorInfo(src_shape, 1, data_type)); |
| weights.allocator()->init(TensorInfo(weights_shape, 1, data_type)); |
| bias.allocator()->init(TensorInfo(bias_shape, 1, data_type)); |
| dst.allocator()->init(TensorInfo(dst_shape, 1, data_type)); |
| |
| // configure layer |
| conv.configure(&src, &weights, &bias, &dst, pad_info); |
| |
| // allocate tensors |
| src.allocator()->allocate(); |
| weights.allocator()->allocate(); |
| bias.allocator()->allocate(); |
| dst.allocator()->allocate(); |
| |
| // To demonstrate how to fill tensor with some values... |
| src.map(); |
| Window window; |
| window.use_tensor_dimensions(src_shape); |
| Iterator it(&src, window); |
| execute_window_loop(window, [&](const Coordinates &) |
| { |
| *reinterpret_cast<half_float::half *>(it.ptr()) = half_float::half(1.f); |
| }); |
| src.unmap(); |
| |
| return true; |
| } |
| void do_run() override |
| { |
| // run the layer |
| conv.run(); |
| } |
| void do_teardown() override |
| { |
| // check result |
| dst.map(); |
| // do something |
| dst.unmap(); |
| } |
| |
| private: |
| GCTensor src{}, weights{}, bias{}, dst{}; |
| GCDirectConvolutionLayer conv{}; |
| |
| TensorShape get_output_shape(TensorShape in_shape, TensorShape kernel_shape, const PadStrideInfo &info) |
| { |
| TensorShape out_shape(in_shape); |
| const std::pair<unsigned int, unsigned int> scaled_dims = scaled_dimensions(in_shape.x(), |
| in_shape.y(), |
| kernel_shape.x(), |
| kernel_shape.y(), |
| info); |
| out_shape.set(0, scaled_dims.first); |
| out_shape.set(1, scaled_dims.second); |
| out_shape.set(2, kernel_shape[3]); |
| return out_shape; |
| } |
| }; |
| |
| /** Main program for directconvolution test |
| * |
| * @param[in] argc Number of arguments |
| * @param[in] argv Arguments |
| */ |
| int main(int argc, char **argv) |
| { |
| return utils::run_example<GCDCExample>(argc, argv); |
| } |