cavis/libnd4j/include/ops/declarable/helpers/lstmLayer.h

118 lines
4.4 KiB
C++

/*******************************************************************************
* 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 <ops/declarable/helpers/helpers.h>
#include <ops/declarable/helpers/activations.h>
namespace sd {
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<float>& 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<float>& 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<NDArray&>(x)).applyTransform(transform::Tanh, z);
break;
case 1:
(const_cast<NDArray&>(x)).applyScalar<float>(scalar::RELU, 0, z);
break;
case 2:
(const_cast<NDArray&>(x)).applyTransform(transform::Sigmoid, z);
break;
case 3: {
ExtraArguments args({ static_cast<double>(alpha), static_cast<double>(beta)});
(const_cast<NDArray&>(x)).applyTransform(transform::Affine, z, &args);
break;
}
case 4:
(const_cast<NDArray&>(x)).applyScalar<float>(scalar::LeakyRELU, alpha, z);
break;
case 5:
helpers::thresholdRelu(x.getContext(), x, alpha, z);
break;
case 6: {
ExtraArguments args({ static_cast<double>(alpha), static_cast<double>(beta)});
(const_cast<NDArray&>(x)).applyTransform(transform::ScaledTanh, z, &args);
break;
}
case 7:
(const_cast<NDArray&>(x)).applyTransform(transform::HardSigmoid, z);
break;
case 8:
(const_cast<NDArray&>(x)).applyScalar<float>(scalar::ELU, alpha, z);
break;
case 9:
(const_cast<NDArray&>(x)).applyTransform(transform::SoftSign, z);
break;
case 10:
(const_cast<NDArray&>(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