/* ****************************************************************************** * * * 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 // #include #if NOT_EXCLUDED(OP_reversesubtract) #include #include namespace sd { namespace ops { BROADCASTABLE_OP_IMPL(reversesubtract, 0, 0) { auto x = INPUT_VARIABLE(0); auto y = INPUT_VARIABLE(1); auto z = OUTPUT_VARIABLE(0); BROADCAST_CHECK_EMPTY(x,y,z); auto tZ = BroadcastHelper::broadcastApply(BROADCAST(ReverseSubtract), x, y, z); if (tZ == nullptr) return ND4J_STATUS_KERNEL_FAILURE; else if (tZ != z) { OVERWRITE_RESULT(tZ); } return Status::OK(); } DECLARE_SYN(RSub, reversesubtract); DECLARE_TYPES(reversesubtract) { getOpDescriptor() ->setAllowedInputTypes(0, DataType::ANY) ->setAllowedInputTypes(1, DataType::ANY) ->setAllowedOutputTypes(0, DataType::INHERIT); } CUSTOM_OP_IMPL(reversesubtract_bp, 3, 2, false, 0, 0) { auto x = INPUT_VARIABLE(0); auto y = INPUT_VARIABLE(1); auto epsNext = INPUT_VARIABLE(2); auto gradX = OUTPUT_VARIABLE(0); auto gradY = OUTPUT_VARIABLE(1); if (x->isSameShape(y)) { // PWT case case epsNext->applyTransform(transform::Neg, *gradX); gradY->assign(epsNext); } else if (y->isScalar()) { // scalar case auto tmp = epsNext->reduceNumber(reduce::Sum); gradY->assign(tmp); epsNext->applyTransform(transform::Neg, *gradX); } else { // broadcastable auto axisX = ShapeUtils::evalBroadcastBackwardAxis(x->shapeInfo(), epsNext->shapeInfo()); auto axisY = ShapeUtils::evalBroadcastBackwardAxis(y->shapeInfo(), epsNext->shapeInfo()); if (axisX.size() > 0) { auto sum = epsNext->reduceAlongDimension(reduce::Sum, axisX); sum.applyTransform(transform::Neg, *gradX); } else { epsNext->applyTransform(transform::Neg, *gradX); } if (axisY.size() > 0) { auto sum = epsNext->reduceAlongDimension(reduce::Sum, axisY); gradY->assign(sum); } else { gradY->assign(epsNext); } } return Status::OK(); } DECLARE_SHAPE_FN(reversesubtract_bp) { auto x = inputShape->at(0); auto y = inputShape->at(1); auto e = inputShape->at(2); // eps always has shape of x // grad always has shape of y Nd4jLong *shapeE; Nd4jLong *shapeG; COPY_SHAPE(x, shapeE); COPY_SHAPE(y, shapeG); auto shapeList = SHAPELIST(CONSTANT(shapeE), CONSTANT(shapeG)); return shapeList; } DECLARE_TYPES(reversesubtract_bp) { getOpDescriptor() ->setAllowedInputTypes(DataType::ANY) ->setAllowedOutputTypes({ALL_FLOATS}); } } } #endif