/******************************************************************************* * 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 20.04.2018 // #ifndef LIBND4J_TRANSFORMS_H #define LIBND4J_TRANSFORMS_H #include #include namespace nd4j { namespace ops { namespace helpers { void triuBP(nd4j::LaunchContext * context, const NDArray& input, const NDArray& gradO, NDArray& gradI, const int diagonal); void trace(nd4j::LaunchContext * context, const NDArray& input, NDArray& output); void randomShuffle(nd4j::LaunchContext * context, NDArray& input, NDArray& output, nd4j::random::RandomBuffer& rng, const bool isInplace); // auxiliary function which serves for recursion purpose and is used in pad operation // void recursiveLoopForPad(const int mode, NDArray& input, const NDArray& paddings, NDArray& output, std::vector dimensions, int dim, int inIdx, int outIdx, NDArray& padValue); void pad(nd4j::LaunchContext * context, const int mode, const NDArray& input, const NDArray& paddings, NDArray& output, NDArray const& padValue); void invertPermutation(nd4j::LaunchContext * context, const NDArray& input, NDArray& output); void gatherND(nd4j::LaunchContext * context, NDArray& input, NDArray& indices, NDArray& output); void gather(nd4j::LaunchContext * context, NDArray* input, const NDArray* indices, NDArray* output, const std::vector& intArgs); void eye(nd4j::LaunchContext * context, NDArray& output); void scatterUpdate(nd4j::LaunchContext * context, NDArray& operand, NDArray& updates, const std::vector* intArgs); void scatterSimple(const int opId, NDArray& input, const NDArray& updates, const NDArray& indices, const std::vector& dimensions); void mergeMaxIndex(nd4j::LaunchContext * context, const std::vector& inArrs, NDArray& output); void mergeMax(nd4j::LaunchContext * context, const std::vector& inArrs, NDArray& output); void mergeAvg(nd4j::LaunchContext * context, const std::vector& inArrs, NDArray& output); void mergeAdd(nd4j::LaunchContext * context, const std::vector& inArrs, NDArray& output); void clipByNorm(nd4j::LaunchContext * context, NDArray& input, NDArray& output, const std::vector& dimensions, const NDArray& clipNorm, const bool isInplace); void clipByGlobalNorm(nd4j::LaunchContext * context, std::vector const& inputs, double clipNorm, nd4j::memory::Workspace* workspace, std::vector& outputs, bool isInplace); void clipByNormBP(nd4j::LaunchContext * context, const NDArray& input, const NDArray& gradO, NDArray& gradI /*output*/, const std::vector& dimensions, const NDArray& clipNorm); void clipByAveraged(nd4j::LaunchContext * context, NDArray& input, NDArray& output, const std::vector& dimensions, const NDArray& clipNorm, const bool isInplace); void clipByValue(nd4j::LaunchContext * context, NDArray& input, double leftBound, double rightBound, NDArray& output); void mirrorPad(nd4j::LaunchContext * context, const NDArray& input, const NDArray& paddings, NDArray& output, const int mode); void concat(nd4j::LaunchContext * context, const std::vector& inArrs, NDArray& output, const int axis); void tileBP(nd4j::LaunchContext * context, const NDArray& gradO /*input*/, NDArray& gradI /*output*/, const std::vector reps); } } } #endif //LIBND4J_TRANSFORMS_H