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chore: import upstream snapshot with attribution

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libnd4j/include/ops/declarable/generic/nn/convo/deconv2d_tf.cpp
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/* ******************************************************************************
*
*
* 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@gmail.com
// @author Yurii Shyrma
//
#include <system/op_boilerplate.h>
#if NOT_EXCLUDED(OP_deconv2d)
#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/helpers/convolutions.h>
namespace sd {
namespace ops {
//////////////////////////////////////////////////////////////////////////
CUSTOM_OP_IMPL(deconv2d_tf, 3, 1, false, 0, 9) {
auto gradO = INPUT_VARIABLE(2); // [bS, oH, oW, oC] (NHWC) or [bS, oC, oH, oW] (NCHW), epsilon_next
auto weights = INPUT_VARIABLE(1); // [kH, kW, iC, oC], [oC, iC, kH, kW], [oC, kH, kW, iC]
auto gradIShape = INPUT_VARIABLE(0); // [4] - shape of input of conv2d (that is shape of gradI)
auto gradI = OUTPUT_NULLIFIED(0); // [bS, iH, iW, iC] (NHWC) or [bS, iC, iH, iW] (NCHW), epsilon
LongType kH = INT_ARG(0) > 0 ? INT_ARG(0) : static_cast<LongType>(weights->sizeAt(0)); // filter(kernel) height
LongType kW = INT_ARG(1) > 0 ? INT_ARG(1) : static_cast<LongType>(weights->sizeAt(1)); // filter(kernel) width
LongType sH = INT_ARG(2); // strides height
LongType sW = INT_ARG(3); // strides width
LongType pH = INT_ARG(4); // paddings height
LongType pW = INT_ARG(5); // paddings width
LongType dH = INT_ARG(6); // dilations height
LongType dW = INT_ARG(7); // dilations width
int isSameMode = INT_ARG(8); // 0-VALID, 1-SAME
int isNCHW = block.getIArguments()->size() > 9 ? !INT_ARG(9) : 1; // INT_ARG(9): 1-NHWC, 0-NCHW
int wFormat = block.getIArguments()->size() > 10
? INT_ARG(10)
: 0; // 0 - [kH, kW, iC, oC], 1 - [oC, iC, kH, kW], 2 - [oC, kH, kW, iC]
const LongType rank = gradO->rankOf();
REQUIRE_TRUE(weights->rankOf() == rank, 0,
"CUSTOM DECONV2D_TF OP: rank of weights array must be equal to 4, but got %i instead !",
weights->rankOf());
REQUIRE_TRUE(gradIShape->rankOf() == 1, 0,
"CUSTOM DECONV2D_TF OP: rank of array with output shape must be equal to 1, but got %i instead !",
gradIShape->rankOf());
REQUIRE_TRUE(gradIShape->lengthOf() == rank, 0,
"CUSTOM DECONV2D_TF OP: length of array with output shape must be equal to 4, but got %i instead !",
gradIShape->lengthOf());
auto nonConst = const_cast<NDArray *>(gradIShape);
std::vector<sd::LongType> gradIShapeVector = nonConst->template asVectorT<sd::LongType>();
// create empty conv2d input array
NDArray input(gradO->ordering(), gradIShapeVector, gradO->dataType(), block.launchContext());
LongType bS, iC, iH, iW, oC, oH,
oW; // batch size, input channels, input height/width, output channels, output height/width;
LongType indIOioC, indIiH, indWoC, indWiC, indWkH, indOoH; // corresponding indexes
ConvolutionUtils::getSizesAndIndexesConv2d(isNCHW, wFormat, input, *gradO, bS, iC, iH, iW, oC, oH, oW, indIOioC,
indIiH, indWiC, indWoC, indWkH, indOoH);
LongType trueoH, trueoW; // true output height, width
ConvolutionUtils::calcOutSizePool2D(trueoH, trueoW, kH, kW, sH, sW, pH, pW, dH, dW, iH, iW, isSameMode);
std::vector<sd::LongType> expectedGradOShape =
ShapeUtils::composeShapeUsingDimsAndIdx({bS, oC, trueoH, trueoW, 0, indIOioC, indOoH, indOoH + 1});
std::vector<sd::LongType> expectedWeightsShape = ConvolutionUtils::expectWeightsShape(wFormat, kH, kW, iC, oC);
REQUIRE_TRUE(gradO->isSameShape(expectedGradOShape), 0,
"CUSTOM DECONV2D_TF OP: wrong shape of input array, basing on array with output shape expected is %s, "
"but got %s instead !",
ShapeUtils::shapeAsString(expectedGradOShape).c_str(), ShapeUtils::shapeAsString(gradO).c_str());
REQUIRE_TRUE(weights->isSameShape(expectedWeightsShape), 0,
"CUSTOM DECONV2D_TF OP: wrong shape of weights array, expected is %s, but got %s instead !",
ShapeUtils::shapeAsString(expectedWeightsShape).c_str(), ShapeUtils::shapeAsString(weights).c_str());
ConvolutionUtils::conv2dBP(block, &input, weights, nullptr, gradO, gradI, nullptr, nullptr, kH, kW, sH, sW, pH, pW,
dH, dW, isSameMode, isNCHW, wFormat);
return sd::Status::OK;
}
DECLARE_TYPES(deconv2d_tf) {
getOpDescriptor()->setAllowedInputTypes(sd::DataType::ANY)->setAllowedOutputTypes({ALL_FLOATS});
}
DECLARE_SHAPE_FN(deconv2d_tf) {
auto gradOShapeInfo = inputShape->at(2); // [bS, oH, oW, oC] (NHWC) or [bS, oC, oH, oW] (NCHW), epsilon_next
auto weightsShapeInfo = inputShape->at(1); // [kH, kW, iC, oC], [oC, iC, kH, kW], [oC, kH, kW, iC]
auto gradIShapeShapeInfo = inputShape->at(0); // [4]
const int rank = 4;
REQUIRE_TRUE(shape::rank(weightsShapeInfo) == rank, 0,
"CUSTOM DECONV2D_TF OP: rank of weights array must be equal to %i, but got %i instead !", rank,
shape::rank(weightsShapeInfo));
REQUIRE_TRUE(shape::rank(gradOShapeInfo) == rank, 0,
"CUSTOM DECONV2D_TF OP: rank of input array must be equal to %i, but got %i instead !", rank,
shape::rank(gradOShapeInfo));
REQUIRE_TRUE(shape::rank(gradIShapeShapeInfo) == 1, 0,
"CUSTOM DECONV2D_TF OP: rank of array with output shape must be equal to %i, but got %i instead !", 1,
shape::rank(gradIShapeShapeInfo));
const LongType kH =
INT_ARG(0) > 0 ? INT_ARG(0) : static_cast<int>(shape::sizeAt(weightsShapeInfo, static_cast<sd::LongType>(0))); // filter(kernel) height
const LongType kW =
INT_ARG(1) > 0 ? INT_ARG(1) : static_cast<int>(shape::sizeAt(weightsShapeInfo, static_cast<sd::LongType>(1))); // filter(kernel) width
const LongType sH = INT_ARG(2); // strides height
const LongType sW = INT_ARG(3); // strides width
const LongType pH = INT_ARG(4); // paddings height
const LongType pW = INT_ARG(5); // paddings width
const LongType dH = INT_ARG(6); // dilations height
const LongType dW = INT_ARG(7); // dilations width
const int isSameMode = INT_ARG(8); // 0-VALID, 1-SAME
const int isNCHW = block.getIArguments()->size() > 9 ? !INT_ARG(9) : 1; // INT_ARG(9): 1-NHWC, 0-NCHW
const int wFormat = block.getIArguments()->size() > 10
? INT_ARG(10)
: 0; // 0 - [kH, kW, iC, oC], 1 - [oC, iC, kH, kW], 2 - [oC, kH, kW, iC]
LongType indIOioC, indIiH, indWoC(0 == wFormat ? 3 : 0), indOoH;
if (!isNCHW) {
indIOioC = 3;
indIiH = 1;
indOoH = 1;
} else {
indIOioC = 1;
indIiH = 2;
indOoH = 2;
}
std::vector<sd::LongType> gradIShape = INPUT_VARIABLE(0)->template asVectorT<sd::LongType>();
const LongType bS = gradIShape[0]; // batch size
const LongType iH = gradIShape[indIiH]; // input height
const LongType iW = gradIShape[indIiH + 1]; // input width
const LongType iC = gradIShape[indIOioC]; // input channels
const LongType oC = weightsShapeInfo[indWoC + 1]; // output channels
const LongType oH = gradOShapeInfo[indOoH + 1]; // input height
const LongType oW = gradOShapeInfo[indOoH + 2]; // input width
LongType trueiH, trueiW; // output height, width
ConvolutionUtils::calcOutSizeDeconv2D(trueiH, trueiW, kH, kW, sH, sW, pH, pW, dH, dW, oH, oW, isSameMode);
std::vector<sd::LongType> expectedGradIShape =
ShapeUtils::composeShapeUsingDimsAndIdx({bS, iC, trueiH, trueiW, 0, indIOioC, indIiH, indIiH + 1});
std::vector<sd::LongType> expectedWeightsShape = ConvolutionUtils::expectWeightsShape(wFormat, kH, kW, iC, oC);
REQUIRE_TRUE(expectedGradIShape == gradIShape, 0,
"CUSTOM DECONV2D_TF OP: wrong shape of array with output shape, expected is %s, but got %s instead !",
ShapeUtils::shapeAsString(expectedGradIShape).c_str(), ShapeUtils::shapeAsString(gradIShape).c_str());
REQUIRE_TRUE(shape::shapeEquals(4, expectedWeightsShape.data(), shape::rank(weightsShapeInfo),
shape::shapeOf(weightsShapeInfo)),
0, "CUSTOM DECONV2D_TF OP: wrong shape of weights array, expected is %s, but got %s instead !",
ShapeUtils::shapeAsString(expectedWeightsShape).c_str(),
ShapeUtils::shapeAsString(weightsShapeInfo).c_str());
sd::LongType shape[4];
shape[0] = bS;
if (isNCHW) {
shape[1] = iC;
shape[2] = iH;
shape[3] = iW;
} else {
shape[1] = iH;
shape[2] = iW;
shape[3] = iC;
}
auto ret = ConstantShapeHelper::getInstance().createShapeInfo(ArrayOptions::dataType(weightsShapeInfo),shape::order(gradOShapeInfo),4,shape,0);
return SHAPELIST(ret);
}
} // namespace ops
} // namespace sd
#endif