/******************************************************************************* * 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) // #ifndef LIBND4J_LSTMLAYER_H #define LIBND4J_LSTMLAYER_H #include #include namespace nd4j { namespace ops { namespace helpers { ////////////////////////////////////////////////////////////////////////// void ND4J_EXPORT lstmLayerCell(const NDArray* x, const NDArray* Wx, const NDArray* Wr, const NDArray* b, const NDArray* hI, const NDArray* cI, const NDArray* Wp, const std::vector& params, NDArray* h, NDArray* c); ////////////////////////////////////////////////////////////////////////// void ND4J_EXPORT lstmLayerTimeLoop(const NDArray* x, const NDArray* Wx, const NDArray* Wr, const NDArray* b, const NDArray* seqLen, const NDArray* hI, const NDArray* cI, const NDArray* Wp, const std::vector& params, const bool forward, NDArray* h, NDArray* hL, NDArray* cL); ////////////////////////////////////////////////////////////////////////// static FORCEINLINE void applyActivation(NDArray& x, const int opId, const float alpha, const float beta, NDArray& z) { switch (opId) { case 0: (const_cast(x)).applyTransform(transform::Tanh, &z); break; case 1: (const_cast(x)).applyScalar(scalar::RELU, 0, &z); break; case 2: (const_cast(x)).applyTransform(transform::Sigmoid, &z); break; case 3: { ExtraArguments args({ static_cast(alpha), static_cast(beta)}); (const_cast(x)).applyTransform(transform::Affine, &z, &args); break; } case 4: (const_cast(x)).applyScalar(scalar::LeakyRELU, alpha, &z); break; case 5: helpers::thresholdRelu(x.getContext(), x, alpha, z); break; case 6: { ExtraArguments args({ static_cast(alpha), static_cast(beta)}); (const_cast(x)).applyTransform(transform::ScaledTanh, &z, &args); break; } case 7: (const_cast(x)).applyTransform(transform::HardSigmoid, &z); break; case 8: (const_cast(x)).applyScalar(scalar::ELU, alpha, &z); break; case 9: (const_cast(x)).applyTransform(transform::SoftSign, &z); break; case 10: (const_cast(x)).applyTransform(transform::SoftPlus, &z); break; default: throw std::invalid_argument("LSTM_LAYER operation: wrong id number of activation !"); } } ////////////////////////////////////////////////////////////////////////// static FORCEINLINE NDArray tensorAlongTimeBatchDims(const NDArray& arr, const int dataFormat, const int t1, const int t2, const int b1, const int b2) { if(dataFormat == 0 || dataFormat == 3) return arr({t1,t2, b1,b2, 0,0}); // TNS: [sL, bS, nIn] if(dataFormat == 1) return arr({b1,b2, t1,t2, 0,0}); // NTS: [bS, sL ,nIn] return arr({b1,b2, 0,0, t1,t2}); // NST: [bS, nIn, sL] } ////////////////////////////////////////////////////////////////////////// static FORCEINLINE int getBatchTimeTotalIndex(const int dataFormat, const int sL, const int bS, const int t, const int b) { if(dataFormat == 0 || dataFormat == 3) return t * bS + b; // TNS: shape [sL, bS, nIn] return b * sL + t; // NTS, NST: shape [bS, sL, nIn], [bS, nIn, sL] } } } } #endif //LIBND4J_LSTMLAYER_H