129 lines
4.9 KiB
C++
129 lines
4.9 KiB
C++
/* ******************************************************************************
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*
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* See the NOTICE file distributed with this work for additional
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* information regarding copyright ownership.
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author raver119@gmail.com
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// @author Oleh Semeniv (oleg.semeniv@gmail.com)
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//
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#include <system/op_boilerplate.h>
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#if NOT_EXCLUDED(OP_Pow)
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#include <ops/declarable/generic/helpers/BroadcastHelper.h>
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#include <ops/declarable/CustomOperations.h>
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namespace sd {
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namespace ops {
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BROADCASTABLE_OP_IMPL(Pow, 0, 0) {
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auto x = INPUT_VARIABLE(0);
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auto y = INPUT_VARIABLE(1);
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auto z = OUTPUT_VARIABLE(0);
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BROADCAST_CHECK_EMPTY(x,y,z);
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//REQUIRE_TRUE(!y->isB(), 0, "Pairwise OP: you can't divide by bool array!");
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auto tZ = BroadcastHelper::broadcastApply({scalar::Pow, pairwise::Pow, broadcast::Pow}, x, y, z);
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if (tZ == nullptr)
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return ND4J_STATUS_KERNEL_FAILURE;
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else if (tZ != z) {
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OVERWRITE_RESULT(tZ);
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}
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return Status::OK();
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}
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DECLARE_TYPES(Pow) {
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getOpDescriptor()
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->setAllowedInputTypes(0, {ALL_FLOATS, ALL_INTS})
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->setAllowedInputTypes(1, {ALL_FLOATS, ALL_INTS})
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->setAllowedOutputTypes(0, {ALL_FLOATS, ALL_INTS});
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}
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CUSTOM_OP_IMPL(Pow_bp, 3, 2, false, 0, 0) {
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auto x = INPUT_VARIABLE(0);
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auto y = INPUT_VARIABLE(1);
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auto dLdz = INPUT_VARIABLE(2);
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auto dLdx = OUTPUT_VARIABLE(0);
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auto dLdy = OUTPUT_VARIABLE(1);
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const Nd4jLong* dLdzShapeInfo = nullptr;
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const bool areShapesBroadcastable = ShapeUtils::evalBroadcastShapeInfo(x->shapeInfo(), y->shapeInfo(), true, dLdzShapeInfo, block.getWorkspace());
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REQUIRE_TRUE(areShapesBroadcastable, 0, "POW_BP OP: the shapes of x %s"
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" and y %s are not suitable for broadcast !",
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ShapeUtils::shapeAsString(x).c_str(), ShapeUtils::shapeAsString(y).c_str());
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REQUIRE_TRUE(shape::equalsSoft(dLdz->shapeInfo(), dLdzShapeInfo), 0,
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"POW_BP OP: wrong shape of next epsilon array (dLdOut),"
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" expected is %s, but got %s instead !",
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ShapeUtils::shapeAsString(dLdzShapeInfo).c_str(), ShapeUtils::shapeAsString(dLdz).c_str());
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// dL/dy = x^y * log(x) * dL/dz
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auto temp = x->applyTrueBroadcast(BroadcastOpsTuple::Pow(), *y); // a = x^y
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x->applyTransform(transform::Log, *dLdx); // b = log(x)
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dLdx->applyScalar(sd::scalar::ReplaceNans, 0, *dLdx);
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temp *= *dLdx; // c = b*a
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temp *= *dLdz; // dL/dy = c * dL/dz
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if (dLdy->isSameShape(*dLdz)) {
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dLdy->assign(temp);
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}
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else {
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std::vector<int> axesForY = ShapeUtils::evalBroadcastBackwardAxis(y->shapeInfo(), dLdz->shapeInfo());
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dLdy->assign(temp.reduceAlongDimension(reduce::Sum, axesForY)); // dL/dy = sum(c * dL/dz)
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}
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// dL/dx = y*x^(y-1) * dL/dz
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x->applyTrueBroadcast(BroadcastOpsTuple::PowDerivative(), *y, temp); // a = y*x^(y-1)
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temp *= *dLdz; // dLdx = a*dL/dz
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if (dLdx->isSameShape(*dLdz)) {
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dLdx->assign(temp); // dLdx = a*dL/dz
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}
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else {
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std::vector<int> axesForX = ShapeUtils::evalBroadcastBackwardAxis(x->shapeInfo(), dLdz->shapeInfo());
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dLdx->assign(temp.reduceAlongDimension(reduce::Sum, axesForX)); // dLdx = a*dL/dz
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}
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return Status::OK();
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}
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DECLARE_SHAPE_FN(Pow_bp) {
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auto xShapeInfo = inputShape->at(0);
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auto yShapeInfo = inputShape->at(1);
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Nd4jLong* dLdxShapeInfo = nullptr;
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Nd4jLong* dLdyShapeInfo = nullptr;
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COPY_SHAPE(xShapeInfo, dLdxShapeInfo);
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COPY_SHAPE(yShapeInfo, dLdyShapeInfo);
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return SHAPELIST(CONSTANT(dLdxShapeInfo), CONSTANT(dLdyShapeInfo));
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}
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DECLARE_TYPES(Pow_bp) {
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getOpDescriptor()
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->setAllowedInputTypes({ ALL_FLOATS, ALL_INTS })
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->setAllowedOutputTypes({ ALL_FLOATS });
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}
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}
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}
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#endif |