cavis/libnd4j/include/ops/declarable/generic/nn/recurrent/lstmBlock.cpp

129 lines
5.9 KiB
C++

/*
* ******************************************************************************
* *
* *
* * 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.
* *
* * See the NOTICE file distributed with this work for additional
* * information regarding copyright ownership.
* * 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
* *****************************************************************************
*/
// lstmBlock: Full LSTM layer in one op
// @author Alex Black
//
#include <system/op_boilerplate.h>
#if NOT_EXCLUDED(OP_lstmBlock)
#include <ops/declarable/CustomOperations.h>
#include<ops/declarable/helpers/lstmBlock.h>
namespace sd {
namespace ops {
//////////////////////////////////////////////////////////////////////////
CUSTOM_OP_IMPL(lstmBlock, 9, 7, false, 2, 2) {
auto maxTSLength = INPUT_VARIABLE(0);
auto x = INPUT_VARIABLE(1); // input [seqLen, bS, nIn] at time t
auto cLast = INPUT_VARIABLE(2); // previous cell state [bS, nOut], time t-1
auto yLast = INPUT_VARIABLE(3); // previous output [bS, nOut], time t-1
auto W = INPUT_VARIABLE(4); // Weights - concatenated (input-to-hidden, hidden-to-hidden weights) weights, [(nIn+nOut), 4*nOut]
auto Wci = INPUT_VARIABLE(5); // weights - cell peephole (t-1) connections to input modulation gate, [nOut]
auto Wcf = INPUT_VARIABLE(6); // weights - cell peephole (t-1) connections to forget gate, [nOut]
auto Wco = INPUT_VARIABLE(7); // weights - cell peephole (t) connections to output gate, [nOut]
auto b = INPUT_VARIABLE(8); // biases, [4*nOut]
auto i = OUTPUT_VARIABLE(0); // Output - input modulation gate activations [seqLen, bS, nOut]
auto c = OUTPUT_VARIABLE(1); // Activations, cell state (pre tanh) [seqLen, bs, nOut]
auto f = OUTPUT_VARIABLE(2); // Output - forget gate activations [seqLen, bs, nOut]
auto o = OUTPUT_VARIABLE(3); // Output - output gate activations [seqLen, bs, nOut]
auto z = OUTPUT_VARIABLE(4); // Output - input gate activations [seqLen, bs, nOut]
auto h = OUTPUT_VARIABLE(5); // Cell state, post tanh [seqLen, bs, nOut]
auto y = OUTPUT_VARIABLE(6); // current cell output [seqLen, bS, numProj], time t
const int peephole = INT_ARG(0); // if 1, provide peephole connections
const int dataFormat = INT_ARG(1); // 0=TNS=[seqLen,bS,nIn]; 1=NST=[bS,nIn,seqLen]; 2=NTS=[bS,seqLen,nIn]
const double forgetBias = T_ARG(0);
const double clippingCellValue = T_ARG(1); // clipping value for ct, if it is not equal to zero, then cell state is clipped
REQUIRE_TRUE(x->rankOf()==3, 0, "lstmBlock: Input array 1 (x) rank must be got input with rank %i", x->rankOf());
REQUIRE_TRUE(cLast->rankOf()==2 && yLast->rankOf()==2, 0, "lstmBlock: Input ranks must be 2 for inputs 2/3 (cLast, yLast) - got %i, %i", cLast->rankOf(), yLast->rankOf());
REQUIRE_TRUE(W->rankOf()==2, 0, "lstmBlock: Weights array rank must be 2");
REQUIRE_TRUE(b->rankOf()==1, 0, "lstmBlock: Biases must be rank 1");
REQUIRE_TRUE(i->rankOf()==3 && c->rankOf()==3 && f->rankOf()==3 && o->rankOf()==3 && z->rankOf()==3 && h->rankOf()==3 && y->rankOf()==3,
0, "lstmBlock: Output arrays must all be rank 3");
helpers::lstmBlockTimeLoop(maxTSLength, x, cLast, yLast, W, Wci, Wcf, Wco, b, i, c, f, o, z, h, y, {(double)peephole, forgetBias, clippingCellValue}, dataFormat);
return Status::OK();
}
DECLARE_TYPES(lstmBlock) {
getOpDescriptor()
->setAllowedInputTypes(sd::DataType::ANY)
->setAllowedOutputTypes({ALL_FLOATS});
}
DECLARE_SHAPE_FN(lstmBlock) {
auto x = inputShape->at(1);
auto cLast = inputShape->at(2);
auto yLast = inputShape->at(3);
auto W = inputShape->at(4);
auto b = inputShape->at(8);
REQUIRE_TRUE(shape::rank(x)==3, 0, "lstmBlock: Input array 1 (x) rank must be got input with rank %i", shape::rank(x));
REQUIRE_TRUE(shape::rank(cLast)==2 && shape::rank(yLast)==2, 0, "lstmBlock: Input ranks must be 2 for inputs 2/3 (cLast, yLast) - got %i, %i", shape::rank(cLast), shape::rank(yLast));
REQUIRE_TRUE(shape::rank(W)==2, 0, "lstmBlock: Weights array rank must be 2");
REQUIRE_TRUE(shape::rank(b)==1, 0, "lstmBlock: Biases must be rank 1");
const int dataFormat = INT_ARG(1); // 0=TNS=[seqLen,bS,size]; 1=NST=[bS,size,seqLen]; 2=NTS=[bS,seqLen,size]
int bs;
int t;
int nOut = cLast[2]; //rank, bs, nOut, ...]
Nd4jLong *s(nullptr);
ALLOCATE(s, block.getWorkspace(), shape::shapeInfoLength(3), Nd4jLong); // [time, bS, nOut]
s[0] = 3;
if(dataFormat == 0){
//[rank, seqLen, bs, nIn, ...]
s[1] = x[1]; //seqLen
s[2] = x[2]; //bS
s[3] = nOut;
} else if(dataFormat==1){
//[rank, bs, nIn, seqLen, ...]
s[1] = x[1]; //bS
s[2] = nOut;
s[3] = x[3]; //seqLen
} else {
//[rank, bs, seqLen, nIn, ...]
s[1] = x[1]; //bS
s[2] = x[2]; //seqLen
s[3] = nOut;
}
ShapeUtils::updateStridesAndType(s, x, 'c');
auto s1 = CONSTANT(s);
//7 outputs, all same shape/type
return SHAPELIST(s1, s1, s1, s1, s1, s1, s1);
}
}
}
#endif