libnd4j/include/ops/declarable/generic/nn/pooling/maxpool3d.cpp
/* ******************************************************************************
*
*
* 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 19.02.2018
//
#include <system/op_boilerplate.h>
#if NOT_EXCLUDED(OP_maxpool3dnew)
#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/helpers/convolutions.h>
namespace sd {
namespace ops {
//////////////////////////////////////////////////////////////////////////
CUSTOM_OP_IMPL(maxpool3dnew, 1, 1, false, 0, 14) {
auto input = INPUT_VARIABLE(0); // [bS, iD, iH, iW, iC] (NDHWC) or [bS, iC, iD, iH, iW] (NCDHW)
auto output = OUTPUT_NULLIFIED(0); // [bS, oD, oH, oW, iC] (NDHWC) or [bS, iC, oD, oH, oW] (NCDHW)
LongType kD = INT_ARG(0); // filter(kernel) depth
LongType kH = INT_ARG(1); // filter(kernel) height
LongType kW = INT_ARG(2); // filter(kernel) width
LongType sD = INT_ARG(3); // strides depth
LongType sH = INT_ARG(4); // strides height
LongType sW = INT_ARG(5); // strides width
LongType pD = INT_ARG(6); // paddings depth
LongType pH = INT_ARG(7); // paddings height
LongType pW = INT_ARG(8); // paddings width
LongType dD = INT_ARG(9); // dilations depth
LongType dH = INT_ARG(10); // dilations height
LongType dW = INT_ARG(11); // dilations width
int isSameMode = INT_ARG(12); // 1-SAME, 0-VALID
int extraParam0 = INT_ARG(13); // unnecessary for max case, required only for avg and pnorm cases
int isNCDHW = block.getIArguments()->size() > 14 ? !INT_ARG(14) : 1; // 1-NDHWC, 0-NCDHW
REQUIRE_TRUE(input->rankOf() == 5, 0, "MAXPOOL3DNEW OP: rank of input array must be equal to 5, but got %i instead !",
input->rankOf());
REQUIRE_TRUE(dD != 0 && dH != 0 && dW != 0, 0,
"MAXPOOL3DNEW op: dilation must not be zero, but got instead {%i, %i, %i}", dD, dH, dW);
LongType bS, iC, iD, iH, iW, oC, oD, oH,
oW; // batch size, input channels, input depth/height/width, output channels, output depth/height/width;
LongType indIOioC, indIOioD, indWoC, indWiC, indWkD; // corresponding indexes
ConvolutionUtils::getSizesAndIndexesConv3d(isNCDHW, 0, *input, *output, bS, iC, iD, iH, iW, oC, oD, oH, oW, indIOioC,
indIOioD, indWiC, indWoC, indWkD);
std::vector<sd::LongType> expectedOutputShape =
ShapeUtils::composeShapeUsingDimsAndIdx({bS, iC, oD, oH, oW, 0, indIOioC, indIOioD, indIOioD + 1, indIOioD + 2});
REQUIRE_TRUE(output->isSameShape(expectedOutputShape), 0,
"MAXPOOL3D op: wrong shape of output array, expected is %s, but got %s instead !",
ShapeUtils::shapeAsString(expectedOutputShape).c_str(), ShapeUtils::shapeAsString(output).c_str());
// REQUIRE_TRUE(iD >= kD && iH >= kH && iW >= kW, 0, "MAXPOOL3D OP: the input depth/height/width must be greater
// or equal to kernel(filter) depth/height/width, but got [%i, %i, %i] and [%i, %i, %i] correspondingly !", iD,iH,iW,
// kD,kH,kW); REQUIRE_TRUE(kD/2 >= pD && kH/2 >= pH && kW/2 >= pW, 0, "MAXPOOL3D OP: pad depth/height/width must not
// be greater than half of kernel depth/height/width, but got [%i, %i, %i] and [%i, %i, %i] correspondingly !",
// pD,pH,pW, kD,kH,kW);
if (!isNCDHW) {
input = new NDArray(input->permute({0, 4, 1, 2, 3})); // [bS, iD, iH, iW, iC] -> [bS, iC, iD, iH, iW]
output = new NDArray(output->permute({0, 4, 1, 2, 3})); // [bS, oD, oH, oW, iC] -> [bS, iC, oD, oH, oW]
}
if (isSameMode) // SAME
ConvolutionUtils::calcPadding3D(pD, pH, pW, oD, oH, oW, iD, iH, iW, kD, kH, kW, sD, sH, sW, dD, dH, dW);
ConvolutionUtils::pooling3d(block, *input, *output, kD, kH, kW, sD, sH, sW, pD, pH, pW, dD, dH, dW, 0, 1);
if (!isNCDHW) {
delete input;
delete output;
}
return sd::Status::OK;
}
DECLARE_TYPES(maxpool3dnew) { getOpDescriptor()->setAllowedInputTypes(sd::DataType::ANY)->setSameMode(true); }
DECLARE_SHAPE_FN(maxpool3dnew) {
LongType kD = INT_ARG(0); // filter(kernel) depth
LongType kH = INT_ARG(1); // filter(kernel) height
LongType kW = INT_ARG(2); // filter(kernel) width
LongType sD = INT_ARG(3); // strides depth
LongType sH = INT_ARG(4); // strides height
LongType sW = INT_ARG(5); // strides width
LongType pD = INT_ARG(6); // paddings depth
LongType pH = INT_ARG(7); // paddings height
LongType pW = INT_ARG(8); // paddings width
LongType dD = INT_ARG(9); // dilations depth
LongType dH = INT_ARG(10); // dilations height
LongType dW = INT_ARG(11); // dilations width
int isSameMode = INT_ARG(12); // 1-SAME, 0-VALID
// int extraParam0 = INT_ARG(13);
int isNCDHW = block.getIArguments()->size() > 14 ? !INT_ARG(14) : 1; // 1-NDHWC, 0-NCDHW
REQUIRE_TRUE(dD != 0 && dH != 0 && dW != 0, 0,
"MAXPOOL3DNEW op: dilation must not be zero, but got instead {%i, %i, %i}", dD, dH, dW);
auto inputShapeInfo = inputShape->at(0);
LongType idxID, idxIC;
if (isNCDHW) {
idxID = 2;
idxIC = 1;
} else {
idxID = 1;
idxIC = 4;
}
LongType bS = inputShapeInfo[1]; // batch size
LongType iC = inputShapeInfo[idxIC + 1]; // input channels
LongType iD = inputShapeInfo[idxID + 1]; // input depth
LongType iH = inputShapeInfo[idxID + 2]; // input height
LongType iW = inputShapeInfo[idxID + 3]; // input width
LongType oD, oH, oW; // output depth, height, width
ConvolutionUtils::calcOutSizePool3D(oD, oH, oW, kD, kH, kW, sD, sH, sW, pD, pH, pW, dD, dH, dW, iD, iH, iW,
isSameMode);
sd::LongType outputShape[5];
outputShape[0] = bS;
if (isNCDHW) {
outputShape[1] = iC;
outputShape[2] = oD;
outputShape[3] = oH;
outputShape[4] = oW;
} else {
outputShape[1] = oD;
outputShape[2] = oH;
outputShape[3] = oW;
outputShape[4] = iC;
}
auto desc = new ShapeDescriptor(ArrayOptions::dataType(inputShapeInfo), shape::order(inputShapeInfo), outputShape, 5);
auto ret = SHAPELIST(ConstantShapeHelper::getInstance().createShapeInfo(desc));
delete desc;
return ret;
}
DECLARE_TYPES(maxpool3dnew_bp) {
getOpDescriptor()->setAllowedInputTypes(sd::DataType::ANY)->setAllowedOutputTypes({ALL_FLOATS});
}
//////////////////////////////////////////////////////////////////////////
CUSTOM_OP_IMPL(maxpool3dnew_bp, 2, 1, false, 0, 14) {
auto input = INPUT_VARIABLE(0); // [bS, iD, iH, iW, iC] (NDHWC) or [bS, iC, iD, iH, iW] (NCDHW)
auto gradO = INPUT_VARIABLE(1); // [bS, oD, oH, oW, oC] (NDHWC) or [bS, oC, oD, oH, oW] (NCDHW), epsilon_next
auto gradI = OUTPUT_NULLIFIED(0); // [bS, iD, iH, iW, iC] (NDHWC) or [bS, iC, iD, iH, iW] (NCDHW), epsilon
const LongType kD = INT_ARG(0); // filter(kernel) depth
const LongType kH = INT_ARG(1); // filter(kernel) height
const LongType kW = INT_ARG(2); // filter(kernel) width
const LongType sD = INT_ARG(3); // strides depth
const LongType sH = INT_ARG(4); // strides height
const LongType sW = INT_ARG(5); // strides width
LongType pD = INT_ARG(6); // paddings depth
LongType pH = INT_ARG(7); // paddings height
LongType pW = INT_ARG(8); // paddings width
const LongType dD = INT_ARG(9); // dilations depth
const LongType dH = INT_ARG(10); // dilations height
const LongType dW = INT_ARG(11); // dilations width
const int isSameMode = INT_ARG(12); // 1-SAME, 0-VALID
int extraParam0 = INT_ARG(13); // unnecessary for max case, required only for avg and pnorm cases
int isNCDHW = block.getIArguments()->size() > 14 ? !INT_ARG(14) : 1; // 1-NDHWC, 0-NCDHW
REQUIRE_TRUE(input->rankOf() == 5, 0, "MAXPOOL3DNEW_BP op: input should have rank of 5, but got %i instead",
input->rankOf());
REQUIRE_TRUE(dD != 0 && dH != 0 && dW != 0, 0,
"MAXPOOL3DNEW_BP op: dilation must not be zero, but got instead {%i, %i, %i}", dD, dH, dW);
LongType bS, iC, iD, iH, iW, oC, oD, oH,
oW; // batch size, input channels, input depth/height/width, output channels, output depth/height/width;
LongType indIOioC, indIOioD, indWoC, indWiC, indWkD; // corresponding indexes
ConvolutionUtils::getSizesAndIndexesConv3d(isNCDHW, 0, *input, *gradO, bS, iC, iD, iH, iW, oC, oD, oH, oW, indIOioC,
indIOioD, indWiC, indWoC, indWkD);
std::vector<sd::LongType> expectedGradOShape =
ShapeUtils::composeShapeUsingDimsAndIdx({bS, iC, oD, oH, oW, 0, indIOioC, indIOioD, indIOioD + 1, indIOioD + 2});
std::vector<sd::LongType> expectedGradIShape =
ShapeUtils::composeShapeUsingDimsAndIdx({bS, iC, iD, iH, iW, 0, indIOioC, indIOioD, indIOioD + 1, indIOioD + 2});
REQUIRE_TRUE(gradO->isSameShape(expectedGradOShape), 0,
"MAXPOOL3DNEW_BP op: wrong shape of output's gradients array (next epsilon), expected is %s, but got %s "
"instead !",
ShapeUtils::shapeAsString(expectedGradOShape).c_str(), ShapeUtils::shapeAsString(gradO).c_str());
REQUIRE_TRUE(
gradI->isSameShape(expectedGradIShape), 0,
"MAXPOOL3DNEW_BP op: wrong shape of input's gradients array (epsilon), expected is %s, but got %s instead !",
ShapeUtils::shapeAsString(expectedGradIShape).c_str(), ShapeUtils::shapeAsString(gradI).c_str());
if (!isNCDHW) {
input = new NDArray(input->permute({0, 4, 1, 2, 3})); // [bS, iD, iH, iW, iC] -> [bS, iC, iD, iH, iW]
gradI = new NDArray(gradI->permute({0, 4, 1, 2, 3})); // [bS, iD, iH, iW, iC] -> [bS, iC, iD, iH, iW]
gradO = new NDArray(gradO->permute({0, 4, 1, 2, 3})); // [bS, oD, oH, oW, iC] -> [bS, iC, oD, oH, oW]
}
if (isSameMode) // SAME
ConvolutionUtils::calcPadding3D(pD, pH, pW, oD, oH, oW, iD, iH, iW, kD, kH, kW, sD, sH, sW, dD, dH, dW);
// [bS, iC, kD, kH, kW, oD, oH, oW] is de-convoluted to [bS, iC, iD, iH, iW]
// 0,1 - kernel Height/Width; 2,3 - stride Height/Width; 4,5 - pad Height/Width; 6,7 - dilation Height/Width; 8 -
// poolingMode; 9 - unnecessary;
ConvolutionUtils::pooling3dBP(block, *input, *gradO, *gradI, kD, kH, kW, sD, sH, sW, pD, pH, pW, dD, dH, dW, 0, 1);
if (!isNCDHW) {
delete input;
delete gradI;
delete gradO;
}
return sd::Status::OK;
}
DECLARE_SHAPE_FN(maxpool3dnew_bp) {
auto desc = new ShapeDescriptor(inputShape->at(0), ArrayOptions::dataType(inputShape->at(1)));
return SHAPELIST(ConstantShapeHelper::getInstance().createShapeInfo(desc));
}
} // namespace ops
} // namespace sd
#endif