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deeplearning4j--deeplearning4j/libnd4j/include/ops/declarable/generic/broadcastable/pow.cpp
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2026-07-13 12:47:05 +08:00

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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 Oleh Semeniv (oleg.semeniv@gmail.com)
//
#include <system/op_boilerplate.h>
#if NOT_EXCLUDED(OP_Pow)
#include <ops/declarable/CustomOperations.h>
#include <ops/declarable/generic/helpers/BroadcastHelper.h>
namespace sd {
namespace ops {
BROADCASTABLE_OP_IMPL(Pow, 0, 0) {
auto x = INPUT_VARIABLE(0);
auto y = INPUT_VARIABLE(1);
auto z = OUTPUT_VARIABLE(0);
BROADCAST_CHECK_EMPTY(x, y, z);
// REQUIRE_TRUE(!y->isB(), 0, "Pairwise OP: you can't divide by bool array!");
auto tZ = BroadcastHelper::broadcastApply({scalar::Pow, pairwise::Pow, broadcast::Pow}, x, y, z);
if (tZ == nullptr)
return Status::KERNEL_FAILURE;
else if (tZ != z) {
OVERWRITE_RESULT(tZ);
}
return Status::OK;
}
DECLARE_TYPES(Pow) {
getOpDescriptor()
->setAllowedInputTypes(0, {ALL_FLOATS, ALL_INTS})
->setAllowedInputTypes(1, {ALL_FLOATS, ALL_INTS})
->setAllowedOutputTypes(0, {ALL_FLOATS, ALL_INTS});
}
CUSTOM_OP_IMPL(Pow_bp, 3, 2, false, 0, 0) {
auto x = INPUT_VARIABLE(0);
auto y = INPUT_VARIABLE(1);
auto dLdz = INPUT_VARIABLE(2);
auto dLdx = OUTPUT_VARIABLE(0);
auto dLdy = OUTPUT_VARIABLE(1);
LongType* dLdzShapeInfo = nullptr;
const bool areShapesBroadcastable =
ShapeUtils::evalBroadcastShapeInfo(x->shapeInfo(), y->shapeInfo(), true, dLdzShapeInfo, block.getWorkspace());
REQUIRE_TRUE(areShapesBroadcastable, 0,
"POW_BP OP: the shapes of x %s"
" and y %s are not suitable for broadcast !",
ShapeUtils::shapeAsString(x).c_str(), ShapeUtils::shapeAsString(y).c_str());
REQUIRE_TRUE(shape::equalsSoft(dLdz->shapeInfo(), dLdzShapeInfo), 0,
"POW_BP OP: wrong shape of next epsilon array (dLdOut),"
" expected is %s, but got %s instead !",
ShapeUtils::shapeAsString(dLdzShapeInfo).c_str(), ShapeUtils::shapeAsString(dLdz).c_str());
// dL/dy = x^y * log(x) * dL/dz
auto temp = x->applyTrueBroadcast(BroadcastOpsTuple::Pow(), y); // a = x^y
x->applyTransform(transform::Log, dLdx); // b = log(x)
dLdx->applyScalar(scalar::ReplaceNans, 0, dLdx);
*temp *= *dLdx; // c = b*a
*temp *= *dLdz; // dL/dy = c * dL/dz
if (dLdy->isSameShape(*dLdz)) {
dLdy->assign(temp);
} else {
std::vector<LongType> axesForY = ShapeUtils::evalBroadcastBackwardAxis(y->shapeInfo(), dLdz->shapeInfo());
NDArray *dLdyTemp = temp->reduceAlongDimension(reduce::Sum, &axesForY);
dLdy->assign(dLdyTemp); // dL/dy = sum(c * dL/dz)
delete dLdyTemp;
}
// dL/dx = y*x^(y-1) * dL/dz
x->applyTrueBroadcast(BroadcastOpsTuple::PowDerivative(), y, temp); // a = y*x^(y-1)
*temp *= *dLdz; // dLdx = a*dL/dz
if (dLdx->isSameShape(*dLdz)) {
dLdx->assign(temp); // dLdx = a*dL/dz
} else {
std::vector<LongType> axesForX = ShapeUtils::evalBroadcastBackwardAxis(x->shapeInfo(), dLdz->shapeInfo());
NDArray *dLdxTemp = temp->reduceAlongDimension(reduce::Sum, &axesForX);
dLdx->assign(dLdxTemp); // dLdx = a*dL/dz
delete dLdxTemp;
}
return Status::OK;
}
DECLARE_SHAPE_FN(Pow_bp) {
auto xShapeInfo = inputShape->at(0);
auto yShapeInfo = inputShape->at(1);
return SHAPELIST(CONSTANT(xShapeInfo), CONSTANT(yShapeInfo));
}
DECLARE_TYPES(Pow_bp) {
getOpDescriptor()->setAllowedInputTypes({ALL_FLOATS, ALL_INTS})->setAllowedOutputTypes({ALL_FLOATS});
}
} // namespace ops
} // namespace sd
#endif