87 lines
3.6 KiB
C++
87 lines
3.6 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author Yurii Shyrma (iuriish@yahoo.com), created on 18.09.2018
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//
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#include <ops/declarable/helpers/convolutions.h>
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#include <execution/Threads.h>
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namespace sd {
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namespace ops {
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//////////////////////////////////////////////////////////////////////////
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template <typename T>
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static void upsampling2dBP_(const NDArray& gradO, NDArray& gradI, const bool isNCHW) {
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// gradO has shape [bS, iC, factorH*iH, factorW*iW ] (NCHW) or [bS, factorH*iH, factorW*iW, iC] (NHWC)
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// gradI has shape [bS, iC, iH, iW] (NCHW) or [bS, iH, iW, iC] (NHWC)
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const T* x = gradO.bufferAsT<T>();
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T* z = gradI.bufferAsT<T>();
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const uint dimIH = isNCHW ? 2 : 1;
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const uint dimIC = isNCHW ? 1 : 3;
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const uint bS = gradI.sizeAt(0);
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const uint iC = gradI.sizeAt(dimIC);
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const uint iH = gradI.sizeAt(dimIH);
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const uint iW = gradI.sizeAt(dimIH + 1);
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const uint factorH = gradO.sizeAt(dimIH) / iH;
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const uint factorW = gradO.sizeAt(dimIH + 1) / iW;
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const Nd4jLong xStride0 = gradO.stridesOf()[0];
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const Nd4jLong xStride1 = gradO.stridesOf()[dimIC];
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const Nd4jLong xStride2 = gradO.stridesOf()[dimIH];
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const Nd4jLong xStride3 = gradO.stridesOf()[dimIH + 1];
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const Nd4jLong zStride0 = gradI.stridesOf()[0];
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const Nd4jLong zStride1 = gradI.stridesOf()[dimIC];
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const Nd4jLong zStride2 = gradI.stridesOf()[dimIH];
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const Nd4jLong zStride3 = gradI.stridesOf()[dimIH + 1];
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// loop through output array
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auto func = PRAGMA_THREADS_FOR_3D {
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for (uint b = start_x; b < stop_x; b += inc_x) {
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for (uint c = start_y; c < stop_y; c += inc_y) {
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for (uint h = start_z; h < stop_z; h += inc_z) {
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for (uint w = 0; w < iW; ++w) {
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const auto zOffset = b * zStride0 + c * zStride1 + h * zStride2 + w * zStride3;
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z[zOffset] = 0;
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for (uint xh = h * factorH; xh < h * factorH + factorH; ++xh)
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for (uint xw = w * factorW; xw < w * factorW + factorW; ++xw)
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z[zOffset] += x[b * xStride0 + c * xStride1 + xh * xStride2 + xw * xStride3];
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}
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}
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}
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}
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};
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samediff::Threads::parallel_for(func, 0, bS, 1, 0, iC, 1, 0, iH, 1);
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}
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void ConvolutionUtils::upsampling2dBP(sd::graph::Context& block, const NDArray& gradO, NDArray& gradI, const bool isNCHW) {
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BUILD_SINGLE_SELECTOR(gradO.dataType(), upsampling2dBP_, (gradO, gradI, isNCHW), FLOAT_TYPES);
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}
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}
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}
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