/* ****************************************************************************** * * * This program and the accompanying materials are made available under the * terms of the Apache License, Version 2.0 which is available at * https://www.apache.org/licenses/LICENSE-2.0. * * See the NOTICE file distributed with this work for additional * information regarding copyright ownership. * 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. * * SPDX-License-Identifier: Apache-2.0 ******************************************************************************/ // // @author Yurii Shyrma (iuriish@yahoo.com), created on 18.09.2018 // #include #include namespace sd { namespace ops { ////////////////////////////////////////////////////////////////////////// template static void upsampling3dBP_(const NDArray& gradO, NDArray& gradI, const bool isNCDHW) { // input has shape [bS, iC, iD, iH, iW] (NCDHW) or [bS, iD, iH, iW, iC] (NDHWC) // output has shape [bS, iC, factorD*iD, factorH*iH, factorW*iW ] (NCDHW) or [bS, factorD*iD, factorH*iH, factorW*iW, iC] (NDHWC) const T* x = gradO.bufferAsT(); T* z = gradI.bufferAsT(); const uint dimID = isNCDHW ? 2 : 1; const uint dimIC = isNCDHW ? 1 : 4; const uint bS = gradI.sizeAt(0); const uint iC = gradI.sizeAt(dimIC); const uint iD = gradI.sizeAt(dimID); const uint iH = gradI.sizeAt(dimID + 1); const uint iW = gradI.sizeAt(dimID + 2); const uint factorD = gradO.sizeAt(dimID) / iD; const uint factorH = gradO.sizeAt(dimID + 1) / iH; const uint factorW = gradO.sizeAt(dimID + 2) / iW; const Nd4jLong xStride0 = gradO.stridesOf()[0]; const Nd4jLong xStride1 = gradO.stridesOf()[dimIC]; const Nd4jLong xStride2 = gradO.stridesOf()[dimID]; const Nd4jLong xStride3 = gradO.stridesOf()[dimID + 1]; const Nd4jLong xStride4 = gradO.stridesOf()[dimID + 2]; const Nd4jLong zStride0 = gradI.stridesOf()[0]; const Nd4jLong zStride1 = gradI.stridesOf()[dimIC]; const Nd4jLong zStride2 = gradI.stridesOf()[dimID]; const Nd4jLong zStride3 = gradI.stridesOf()[dimID + 1]; const Nd4jLong zStride4 = gradI.stridesOf()[dimID + 2]; // loop through output array auto func = PRAGMA_THREADS_FOR_3D { for (uint b = start_x; b < stop_x; b += inc_x) { for (uint c = start_y; c < stop_y; c += inc_y) { for (uint d = start_z; d < stop_z; d += inc_z) { for (uint h = 0; h < iH; ++h) { for (uint w = 0; w < iW; ++w) { const auto zOffset = b * zStride0 + c * zStride1 + d * zStride2 + h * zStride3 + w * zStride4; z[zOffset] = 0; for (uint xd = d * factorD; xd < d * factorD + factorD; ++xd) for (uint xh = h * factorH; xh < h * factorH + factorH; ++xh) for (uint xw = w * factorW; xw < w * factorW + factorW; ++xw) z[zOffset] += x[b * xStride0 + c * xStride1 + xd * xStride2 + xh * xStride3 + xw * xStride4]; } } } } } }; samediff::Threads::parallel_for(func, 0, bS, 1, 0, iC, 1, 0, iD, 1); } void ConvolutionUtils::upsampling3dBP(sd::graph::Context& block, const NDArray& gradO, NDArray& gradI, const bool isNCHW) { BUILD_SINGLE_SELECTOR(gradO.dataType(), upsampling3dBP_, (gradO, gradI, isNCHW), FLOAT_TYPES); } } }