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