130 lines
5.2 KiB
C++
130 lines
5.2 KiB
C++
/* ******************************************************************************
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*
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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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* See the NOTICE file distributed with this work for additional
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* information regarding copyright ownership.
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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 raver119, created on 29/10/17.
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// @author Yurii Shyrma (iuriish@yahoo.com), changed on 03.05.2018
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//
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#include <system/op_boilerplate.h>
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#if NOT_EXCLUDED(OP_upsampling2d)
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#include <ops/declarable/CustomOperations.h>
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#include <ops/declarable/helpers/convolutions.h>
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namespace sd {
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namespace ops {
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//////////////////////////////////////////////////////////////////////
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CUSTOM_OP_IMPL(upsampling2d, 1, 1, false, 0, 2) {
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auto input = INPUT_VARIABLE(0); // [bS, iC, iH, iW] (NCHW) or [bS, iH, iW, iC] (NHWC)
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auto output = OUTPUT_NULLIFIED(0); // [bS, iC, factorH*iH, factorW*iW ] (NCHW) or [bS, factorH*iH, factorW*iW, iC] (NHWC)
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const int factorH = INT_ARG(0);
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const int factorW = INT_ARG(1);
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const int isNCHW = block.getIArguments()->size() > 2 ? INT_ARG(2) : 0; // INT_ARG(2): 0-NCHW, 1-NHWC
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REQUIRE_TRUE(input->rankOf() == 4, 0, "UPSAMPLING2D op: input should be 4D, but got %i instead!", input->rankOf());
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REQUIRE_TRUE(output->rankOf() == 4, 0, "UPSAMPLING2D op: output should be 4D, but got %i instead!", output->rankOf());
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ConvolutionUtils::upsampling2d(block, *input, *output, factorH, factorW, (bool)isNCHW);
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return Status::OK();
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}
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DECLARE_SYN(upsampling, upsampling2d);
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DECLARE_TYPES(upsampling2d) {
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getOpDescriptor()
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->setAllowedInputTypes(sd::DataType::ANY)
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->setAllowedOutputTypes({ALL_FLOATS});
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}
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DECLARE_SHAPE_FN(upsampling2d) {
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auto inputShapeInfo = inputShape->at(0);
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REQUIRE_TRUE(inputShapeInfo[0] == 4, 0, "UPSAMPLING2D op: input should be 4D, but got %i instead!", inputShapeInfo[0]);
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const int factorH = INT_ARG(0);
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const int factorW = INT_ARG(1);
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const int isNCHW = block.getIArguments()->size() > 2 ? INT_ARG(2) : 0; // INT_ARG(2): 0-NCHW, 1-NHWC
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Nd4jLong *outputShapeInfo = nullptr;
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ALLOCATE(outputShapeInfo, block.getWorkspace(), shape::shapeInfoLength(inputShapeInfo[0]), Nd4jLong);
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outputShapeInfo[0] = inputShapeInfo[0];
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outputShapeInfo[1] = inputShapeInfo[1];
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if(isNCHW) {
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outputShapeInfo[2] = inputShapeInfo[2];
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outputShapeInfo[3] = inputShapeInfo[3] * factorH;
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outputShapeInfo[4] = inputShapeInfo[4] * factorW;
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}
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else {
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outputShapeInfo[2] = inputShapeInfo[2] * factorH;
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outputShapeInfo[3] = inputShapeInfo[3] * factorW;
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outputShapeInfo[4] = inputShapeInfo[4];
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}
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ShapeUtils::updateStridesAndType(outputShapeInfo, inputShapeInfo, shape::order(inputShapeInfo));
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return SHAPELIST(CONSTANT(outputShapeInfo));
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}
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DECLARE_TYPES(upsampling2d_bp) {
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getOpDescriptor()
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->setAllowedInputTypes(sd::DataType::ANY)
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->setAllowedOutputTypes({ALL_FLOATS});
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}
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//////////////////////////////////////////////////////////////////////
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CUSTOM_OP_IMPL(upsampling2d_bp, 2, 1, false, 0, 0) {
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// NDArray<T>* input = INPUT_VARIABLE(0); // [bS, iC, iH, iW] (NCHW) or [bS, iH, iW, iC] (NHWC)
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auto gradO = INPUT_VARIABLE(1); // [bS, iC, factorH*iH, factorW*iW ] (NCHW) or [bS, factorH*iH, factorW*iW, iC] (NHWC)
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auto gradI = OUTPUT_NULLIFIED(0); // [bS, iC, iH, iW] (NCHW) or [bS, iH, iW, iC] (NHWC)
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const int isNCHW = block.getIArguments()->size() > 0 ? INT_ARG(0) : 0; // INT_ARG(0): 0-NCHW, 1-NHWC
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// REQUIRE_TRUE(input->rankOf() == 4, 0, "UPSAMPLING2D_BP op: input array must be 4D, but got %i instead!", input->rankOf());
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REQUIRE_TRUE(gradO->rankOf() == 4, 0, "UPSAMPLING2D_BP op: output's gradient array must be 4D, but got %i instead!", gradO->rankOf());
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REQUIRE_TRUE(gradI->rankOf() == 4, 0, "UPSAMPLING2D_BP op: input's gradient array must be 4D, but got %i instead!", gradI->rankOf());
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ConvolutionUtils::upsampling2dBP(block, *gradO, *gradI, (bool)isNCHW);
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return Status::OK();
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}
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DECLARE_SYN(upsampling_bp, upsampling2d_bp);
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DECLARE_SHAPE_FN(upsampling2d_bp) {
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REQUIRE_TRUE(inputShape->at(0)[0] == 4, 0, "UPSAMPLING2D_BP op: input array must be 4D, but got %i instead!", inputShape->at(0)[0]);
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REQUIRE_TRUE(inputShape->at(1)[0] == 4, 0, "UPSAMPLING2D_BP op: output's gradient array must be 4D, but got %i instead!", inputShape->at(1)[0]);
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auto gradIShapeInfo = ShapeBuilders::copyShapeInfoAndType(inputShape->at(0), inputShape->at(1), false, block.getWorkspace());
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return SHAPELIST(CONSTANT(gradIShapeInfo));
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}
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}
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}
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#endif |