cavis/libnd4j/include/ops/declarable/generic/convo/upsampling3d.cpp

127 lines
5.3 KiB
C++

/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* 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.
*
* 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 04.05.2018
//
#include <op_boilerplate.h>
#if NOT_EXCLUDED(OP_upsampling3d)
#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/helpers/convolutions.h>
namespace nd4j {
namespace ops {
//////////////////////////////////////////////////////////////////////
CUSTOM_OP_IMPL(upsampling3d, 1, 1, false, 0, 3) {
auto input = INPUT_VARIABLE(0); // [bS, iC, iD, iH, iW] (NCDHW) or [bS, iD, iH, iW, iC] (NDHWC)
auto output = OUTPUT_VARIABLE(0); // [bS, iC, factorD*iD, factorH*iH, factorW*iW ] (NCDHW) or [bS, factorD*iD, factorH*iH, factorW*iW, iC] (NDHWC)
const int factorD = INT_ARG(0);
const int factorH = INT_ARG(1);
const int factorW = INT_ARG(2);
const int isNCDHW = block.getIArguments()->size() > 3 ? INT_ARG(3) : 0; // INT_ARG(3): 0-NCDHW, 1-NDHWC
REQUIRE_TRUE(input->rankOf() == 5, 0, "UPSAMPLING3D op: input should be 5D, but got %i instead!", input->rankOf());
REQUIRE_TRUE(output->rankOf() == 5, 0, "UPSAMPLING3D op: output should be 5D, but got %i instead!", output->rankOf());
ConvolutionUtils::upsampling3d(block, *input, *output, factorD, factorH, factorW, (bool)isNCDHW);
return Status::OK();
}
DECLARE_TYPES(upsampling3d) {
getOpDescriptor()
->setAllowedInputTypes(nd4j::DataType::ANY)
->setAllowedOutputTypes({ALL_FLOATS});
}
DECLARE_SHAPE_FN(upsampling3d) {
auto inputShapeInfo = inputShape->at(0);
REQUIRE_TRUE(inputShapeInfo[0] == 5, 0, "UPSAMPLING2D op: input should be 5D, but got %i instead!", inputShapeInfo[0]);
const int factorD = INT_ARG(0);
const int factorH = INT_ARG(1);
const int factorW = INT_ARG(2);
const int isNCDHW = block.getIArguments()->size() > 3 ? INT_ARG(3) : 0; // INT_ARG(3): 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(isNCDHW) {
outputShapeInfo[2] = inputShapeInfo[2];
outputShapeInfo[3] = inputShapeInfo[3] * factorD;
outputShapeInfo[4] = inputShapeInfo[4] * factorH;
outputShapeInfo[5] = inputShapeInfo[5] * factorW;
}
else {
outputShapeInfo[2] = inputShapeInfo[2] * factorD;
outputShapeInfo[3] = inputShapeInfo[3] * factorH;
outputShapeInfo[4] = inputShapeInfo[4] * factorW;
outputShapeInfo[5] = inputShapeInfo[5];
}
ShapeUtils::updateStridesAndType(outputShapeInfo, inputShapeInfo, shape::order(inputShapeInfo));
return SHAPELIST(CONSTANT(outputShapeInfo));
}
DECLARE_TYPES(upsampling3d_bp) {
getOpDescriptor()
->setAllowedInputTypes(nd4j::DataType::ANY)
->setAllowedOutputTypes({ALL_FLOATS});
}
//////////////////////////////////////////////////////////////////////
CUSTOM_OP_IMPL(upsampling3d_bp, 2, 1, false, 0, 0) {
// NDArray<T>* input = INPUT_VARIABLE(0); // [bS, iC, iD, iH, iW] (NCDHW) or [bS, iD, iH, iW, iC] (NDHWC)
auto gradO = INPUT_VARIABLE(1); // [bS, iC, factorD*iD, factorH*iH, factorW*iW ] (NCDHW) or [bS, factorD*iD, factorH*iH, factorW*iW, iC] (NDHWC)
auto gradI = OUTPUT_VARIABLE(0); // [bS, iC, iD, iH, iW] (NCDHW) or [bS, iD, iH, iW, iC] (NDHWC)
const int isNCDHW = block.getIArguments()->size() > 0 ? INT_ARG(0) : 0; // INT_ARG(0): 0-NCHW, 1-NHWC
// REQUIRE_TRUE(input->rankOf() == 5, 0, "UPSAMPLING3D_BP op: input array must be 4D, but got %i instead!", input->rankOf());
REQUIRE_TRUE(gradO->rankOf() == 5, 0, "UPSAMPLING3D_BP op: output's gradient array must be 4D, but got %i instead!", gradO->rankOf());
REQUIRE_TRUE(gradI->rankOf() == 5, 0, "UPSAMPLING3D_BP op: input's gradient array must be 4D, but got %i instead!", gradI->rankOf());
ConvolutionUtils::upsampling3dBP(block, *gradO, *gradI, (bool)isNCDHW);
return Status::OK();
}
DECLARE_SHAPE_FN(upsampling3d_bp) {
REQUIRE_TRUE(inputShape->at(0)[0] == 5, 0, "UPSAMPLING3D_BP op: input array must be 4D, but got %i instead!", inputShape->at(0)[0]);
REQUIRE_TRUE(inputShape->at(1)[0] == 5, 0, "UPSAMPLING3D_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