/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/operators/math/vol2col.h" #include #include template void testVol2col() { paddle::framework::Tensor input; paddle::framework::Tensor input_tmp; paddle::framework::Tensor output; paddle::framework::Tensor output_tmp; auto* place = new Place(); paddle::platform::DeviceContext* context; if (paddle::platform::is_cpu_place(*place)) { context = new paddle::platform::CPUDeviceContext(paddle::platform::CPUPlace()); } else { #ifdef PADDLE_WITH_CUDA context = new paddle::platform::CUDADeviceContext(paddle::platform::GPUPlace()); #else PADDLE_THROW("no GPU support"); #endif // PADDLE_WITH_CUDA } /** * input = [[0, 1, 2, * 3, 4, 5] * [6, 7, 8, * 9, 10, 11]] * * output = [0, 1 * 1, 2 * 3, 4 * 4, 5 * 6, 7 * 7, 8 * 9, 10 * 10, 11] * * col2vol = [[0, 2, 2, * 3, 8, 5] * [6, 14, 8, * 9, 20, 11]] * */ int input_depth = 2; int input_height = 2; int input_width = 3; int filter_size = 2; std::vector strides({1, 1, 1}); std::vector paddings({0, 0, 0}); std::vector dilations({1, 1, 1}); int output_depth = (input_depth - filter_size + 2 * paddings[0]) / strides[0] + 1; int output_height = (input_height - filter_size + 2 * paddings[1]) / strides[1] + 1; int output_width = (input_width - filter_size + 2 * paddings[2]) / strides[2] + 1; // Vol2Col test float* input_ptr = input_tmp.mutable_data({1, input_depth, input_height, input_width}, paddle::platform::CPUPlace()); float arr[12] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}; memcpy(input_ptr, arr, 12 * sizeof(float)); if (paddle::platform::is_cpu_place(*place)) { input = input_tmp; } else { input.CopyFrom(input_tmp, *place, *context); } output.mutable_data({1, filter_size, filter_size, filter_size, output_depth, output_height, output_width}, *place); paddle::operators::math::Vol2ColFunctor vol2col; vol2col(*context, input, dilations, strides, paddings, &output); float vol_2_col[] = {0, 1, 1, 2, 3, 4, 4, 5, 6, 7, 7, 8, 9, 10, 10, 11}; float* out_cfo_ptr; if (paddle::platform::is_cpu_place(*place)) { out_cfo_ptr = output.data(); } else { output_tmp.CopyFrom(output, paddle::platform::CPUPlace(), *context); out_cfo_ptr = output_tmp.data(); } for (int i = 0; i < 16; ++i) { EXPECT_EQ(out_cfo_ptr[i], vol_2_col[i]); } // Col2Vol test float col_2_vol[] = {0, 2, 2, 3, 8, 5, 6, 14, 8, 9, 20, 11}; memset(input_ptr, 0, 12 * sizeof(float)); if (paddle::platform::is_cpu_place(*place)) { input = input_tmp; } else { input.CopyFrom(input_tmp, *place, *context); } paddle::operators::math::Col2VolFunctor col2vol; col2vol(*context, output, dilations, strides, paddings, &input); float* in_ptr; if (paddle::platform::is_cpu_place(*place)) { in_ptr = input.data(); } else { input_tmp.CopyFrom(input, paddle::platform::CPUPlace(), *context); in_ptr = input_tmp.data(); } for (int i = 0; i < 12; ++i) { EXPECT_EQ(in_ptr[i], col_2_vol[i]); } } TEST(math, vol2col) { testVol2col(); #ifdef PADDLE_WITH_CUDA testVol2col(); #endif // PADDLE_WITH_CUDA }