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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)
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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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											2020-03-02 12:49:41 +03:00
										 
									 
								 
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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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