82 lines
4.0 KiB
C
82 lines
4.0 KiB
C
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/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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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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* 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 Yurii Shyrma (iuriish@yahoo.com), created on 20.04.2018
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//
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#ifndef LIBND4J_TRANSFORMS_H
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#define LIBND4J_TRANSFORMS_H
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#include <ops/declarable/helpers/helpers.h>
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#include <helpers/helper_random.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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void triuBP(nd4j::LaunchContext * context, const NDArray& input, const NDArray& gradO, NDArray& gradI, const int diagonal);
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void trace(nd4j::LaunchContext * context, const NDArray& input, NDArray& output);
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void randomShuffle(nd4j::LaunchContext * context, NDArray& input, NDArray& output, nd4j::random::RandomBuffer& rng, const bool isInplace);
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// auxiliary function which serves for recursion purpose and is used in pad operation
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// void recursiveLoopForPad(const int mode, NDArray& input, const NDArray& paddings, NDArray& output, std::vector<int> dimensions, int dim, int inIdx, int outIdx, NDArray& padValue);
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void pad(nd4j::LaunchContext * context, const int mode, const NDArray& input, const NDArray& paddings, NDArray& output, NDArray const& padValue);
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void invertPermutation(nd4j::LaunchContext * context, const NDArray& input, NDArray& output);
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void gatherND(nd4j::LaunchContext * context, NDArray& input, NDArray& indices, NDArray& output);
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void gather(nd4j::LaunchContext * context, NDArray* input, const NDArray* indices, NDArray* output, const std::vector<int>& intArgs);
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void eye(nd4j::LaunchContext * context, NDArray& output);
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void scatterUpdate(nd4j::LaunchContext * context, NDArray& operand, NDArray& updates, const std::vector<int>* intArgs);
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void scatterSimple(const int opId, NDArray& input, const NDArray& updates, const NDArray& indices, const std::vector<int>& dimensions);
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void mergeMaxIndex(nd4j::LaunchContext * context, const std::vector<NDArray*>& inArrs, NDArray& output);
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void mergeMax(nd4j::LaunchContext * context, const std::vector<NDArray*>& inArrs, NDArray& output);
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void mergeAvg(nd4j::LaunchContext * context, const std::vector<NDArray*>& inArrs, NDArray& output);
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void mergeAdd(nd4j::LaunchContext * context, const std::vector<NDArray*>& inArrs, NDArray& output);
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void clipByNorm(nd4j::LaunchContext * context, NDArray& input, NDArray& output, const std::vector<int>& dimensions, const NDArray& clipNorm, const bool isInplace);
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void clipByGlobalNorm(nd4j::LaunchContext * context, std::vector<NDArray*> const& inputs, double clipNorm, nd4j::memory::Workspace* workspace, std::vector<NDArray*>& outputs, bool isInplace);
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void clipByNormBP(nd4j::LaunchContext * context, const NDArray& input, const NDArray& gradO, NDArray& gradI /*output*/, const std::vector<int>& dimensions, const NDArray& clipNorm);
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void clipByAveraged(nd4j::LaunchContext * context, NDArray& input, NDArray& output, const std::vector<int>& dimensions, const NDArray& clipNorm, const bool isInplace);
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void clipByValue(nd4j::LaunchContext * context, NDArray& input, double leftBound, double rightBound, NDArray& output);
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void mirrorPad(nd4j::LaunchContext * context, const NDArray& input, const NDArray& paddings, NDArray& output, const int mode);
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void concat(nd4j::LaunchContext * context, const std::vector<NDArray*>& inArrs, NDArray& output, const int axis);
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void tileBP(nd4j::LaunchContext * context, const NDArray& gradO /*input*/, NDArray& gradI /*output*/, const std::vector<Nd4jLong> reps);
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}
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}
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}
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#endif //LIBND4J_TRANSFORMS_H
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