/* ****************************************************************************** * * * 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 sgazeos@gmail.com // #include #include namespace sd { namespace ops { namespace helpers { template void applyGradientDescent_(LaunchContext* context, NDArray* input, NDArray* step, double weight, NDArray* output) { // classic one auto lambda = LAMBDA_TT(_x, _y, weight) { return _x - (_y * weight); }; input->applyPairwiseLambda(*step, lambda, *output); } void applyGradientDescent(sd::LaunchContext* context, NDArray* input, NDArray* step, double weight, NDArray* output) { BUILD_SINGLE_SELECTOR(input->dataType(), applyGradientDescent_, (context, input, step, weight, output), FLOAT_TYPES); } BUILD_SINGLE_TEMPLATE(template void applyGradientDescent_, (LaunchContext* context, NDArray* input, NDArray* step, double weight, NDArray* output), FLOAT_TYPES); } } }