cavis/libnd4j/include/ops/declarable/generic/nn/convo/upsampling2d.cpp

130 lines
5.2 KiB
C++

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