/******************************************************************************* * Copyright (c) 2015-2018 Skymind, Inc. * * 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. * * 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 Yurii Shyrma (iuriish@yahoo.com), created on 19.04.2018 // #ifndef LIBND4J_ACTIVATIONS_H #define LIBND4J_ACTIVATIONS_H #include namespace nd4j { namespace ops { namespace helpers { void softMaxForVector(nd4j::LaunchContext * context, const NDArray &input, NDArray &output); void logSoftMaxForVector(nd4j::LaunchContext * context, const NDArray &input, NDArray &output); void softmax(nd4j::LaunchContext * context, const NDArray &input, NDArray &output, const int dimension); void logSoftmax(nd4j::LaunchContext * context, const NDArray &input, NDArray &output, const int dimension); void softmaxDerivative(nd4j::LaunchContext * context, const NDArray& input, NDArray& output, const int dimension); void prelu(nd4j::LaunchContext * context, const NDArray &input, const NDArray &alpha, NDArray &output); void preluBP(nd4j::LaunchContext * context, const NDArray &input, const NDArray &alpha, const NDArray &dLdO, NDArray &dLdI, NDArray &dLdA); void thresholdRelu(nd4j::LaunchContext * context, const NDArray &input, double threshold, NDArray &output); void thresholdReluDerivative(nd4j::LaunchContext * context, NDArray *input, double threshold, NDArray* dLdO, NDArray *output); } } } #endif //LIBND4J_ACTIVATIONS_H