cavis/libnd4j/include/ops/declarable/generic/recurrent/dynamicRNN.cpp

162 lines
9.0 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, created on 05.04.2018
//
#include <ops/declarable/CustomOperations.h>
#include<ops/declarable/helpers/rnn.h>
namespace nd4j {
namespace ops {
//////////////////////////////////////////////////////////////////////////
CUSTOM_OP_IMPL(dynamic_rnn, 4, 2, false, 0, 0) {
auto x = INPUT_VARIABLE(0); // input [time x bS x inSize] or [bS x time x inSize], depends on timeMajor parameter
auto Wx = INPUT_VARIABLE(1); // input-to-hidden weights, [inSize x numUnits]
auto Wh = INPUT_VARIABLE(2); // hidden-to-hidden weights, [numUnits x numUnits]
auto b = INPUT_VARIABLE(3); // biases for, [2*numUnits]
NDArray* h0 = nullptr; // initial cell output (at time step = 0) [bS x numUnits]
NDArray* maxTimeStep = nullptr; // vector [bS] containing integer values within [0,time), each element of this vector set max time step per each input in batch, this means there are no calculations for time >= maxTimeStep
const int timeMajor = block.getIArguments()->size() > 0 ? INT_ARG(0) : 0; // if true then [time, bS, ...], else [bS, time, ...]
if(block.width() == 5) {
if ((*INPUT_VARIABLE(4)).rankOf() == 2)
h0 = INPUT_VARIABLE(4);
else
maxTimeStep = INPUT_VARIABLE(4);
}
else if(block.width() == 6) {
h0 = INPUT_VARIABLE(4);
maxTimeStep = INPUT_VARIABLE(5);
}
auto h = OUTPUT_VARIABLE(0); // cell outputs [time x bS x numUnits] or [bS x time x numUnits], depends on timeMajor parameter
auto hFinal = OUTPUT_VARIABLE(1); // at the end it will store cell final non-zero output [bS x numUnits]
REQUIRE_TRUE(x->rankOf() == 3, 0, "DYNAMIC_RNN custom operation: input array x must have rank = 3, but got %i instead !", x->rankOf());
REQUIRE_TRUE(Wx->rankOf() == 2, 0, "DYNAMIC_RNN custom operation: input-to-hidden weights array must have rank = 2, but got %i instead !", Wx->rankOf());
const int inRank = x->rankOf();
const int time = timeMajor ? x->sizeAt(0) : x->sizeAt(1);
const int bS = timeMajor ? x->sizeAt(1) : x->sizeAt(0);
const int numUnits = Wx->sizeAt(1);
REQUIRE_TRUE(ShapeUtils::shapeAsString(Wh) == ShapeUtils::shapeAsString({numUnits, numUnits}), 0, "DYNAMIC_RNN custom operation: wrong shape of hidden-to-hidden weights array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString({numUnits, numUnits}).c_str(), ShapeUtils::shapeAsString(Wh).c_str());
REQUIRE_TRUE(ShapeUtils::shapeAsString(b) == ShapeUtils::shapeAsString({2*numUnits}), 0, "DYNAMIC_RNN custom operation: wrong shape of biases array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString({2*numUnits}).c_str(), ShapeUtils::shapeAsString(b).c_str());
if(h0)
REQUIRE_TRUE(ShapeUtils::shapeAsString(h0) == ShapeUtils::shapeAsString({bS, numUnits}), 0, "DYNAMIC_RNN custom operation: wrong shape of initial cell output array, expected is %s but got %s instead !", ShapeUtils::shapeAsString({bS, numUnits}).c_str(), ShapeUtils::shapeAsString(h0).c_str());
if(maxTimeStep)
REQUIRE_TRUE(ShapeUtils::shapeAsString(maxTimeStep) == ShapeUtils::shapeAsString({bS}), 0, "DYNAMIC_RNN custom operation: wrong shape of maxTimeStep array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString({bS}).c_str(), ShapeUtils::shapeAsString(maxTimeStep).c_str());
if(timeMajor == false) {
x = x->permute({1, 0, 2}); // [bS x time x inSize] -> [time x bS x inSize]
h = h->permute({1, 0, 2}); // [bS x time x numUnits] -> [time x bS x numUnits]
}
helpers::rnnTimeLoop(block.launchContext(), x, Wx, Wh, b, h0, maxTimeStep, h, hFinal);
if(timeMajor == false) {
delete x;
delete h;
}
return Status::OK();
}
DECLARE_TYPES(dynamic_rnn) {
getOpDescriptor()
->setAllowedInputTypes(0, nd4j::DataType::ANY)
->setAllowedInputTypes(1, {ALL_FLOATS})
->setAllowedInputTypes(2, {ALL_FLOATS})
->setAllowedInputTypes(3, {ALL_FLOATS})
->setAllowedInputTypes(4, {ALL_FLOATS, ALL_INTS})
->setAllowedInputTypes(5, {ALL_FLOATS, ALL_INTS})
->setAllowedOutputTypes(0, {ALL_FLOATS})
->setAllowedOutputTypes(1, {ALL_FLOATS});
}
DECLARE_SHAPE_FN(dynamic_rnn) {
auto xShapeInfo = inputShape->at(0); // input [time x bS x inSize] or [bS x time x inSize], depends on timeMajor parameter
auto WxShapeInfo = inputShape->at(1); // input-to-hidden weights, [inSize x numUnits]
auto WhShapeInfo = inputShape->at(2); // hidden-to-hidden weights, [numUnits x numUnits]
auto bShapeInfo = inputShape->at(3); // biases for, [2*numUnits]
Nd4jLong* h0ShapeInfo = nullptr; // initial cell output (at time step = 0) [bS x numUnits]
Nd4jLong* maxTimeStepShapeInfo = nullptr; // vector [bS] containing integer values within [0,time), each element of this vector set max time step per each input in batch, this means there are no calculations for time >= maxTimeStep
const int timeMajor = block.getIArguments()->size() > 0 ? INT_ARG(0) : 0; // if true then [time, bS, ...], else [bS, time, ...]
if(block.width() == 5) {
if (inputShape->at(4)[0] == 2)
h0ShapeInfo = inputShape->at(4);
else
maxTimeStepShapeInfo = inputShape->at(4);
}
else if(block.width() == 6) {
h0ShapeInfo = inputShape->at(4);
maxTimeStepShapeInfo = inputShape->at(5);
}
REQUIRE_TRUE(xShapeInfo[0] == 3, 0, "DYNAMIC_RNN custom operation: input array x must have rank = 3, but got %i instead !", xShapeInfo[0]);
REQUIRE_TRUE(WxShapeInfo[0] == 2, 0, "DYNAMIC_RNN custom operation: input-to-hidden weights array must have rank = 2, but got %i instead !", WxShapeInfo[0]);
const int inRank = xShapeInfo[0];
const int time = timeMajor ? xShapeInfo[1] : xShapeInfo[2];
const int bS = timeMajor ? xShapeInfo[2] : xShapeInfo[1];
const int numUnits = WxShapeInfo[2];
REQUIRE_TRUE(ShapeUtils::shapeAsString(WhShapeInfo) == ShapeUtils::shapeAsString({numUnits, numUnits}), 0, "DYNAMIC_RNN custom operation: wrong shape of hidden-to-hidden weights array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString({numUnits, numUnits}).c_str(), ShapeUtils::shapeAsString(WhShapeInfo).c_str());
REQUIRE_TRUE(ShapeUtils::shapeAsString(bShapeInfo) == ShapeUtils::shapeAsString({2*numUnits}), 0, "DYNAMIC_RNN custom operation: wrong shape of biases array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString({2*numUnits}).c_str(), ShapeUtils::shapeAsString(bShapeInfo).c_str());
if(h0ShapeInfo)
REQUIRE_TRUE(ShapeUtils::shapeAsString(h0ShapeInfo) == ShapeUtils::shapeAsString({bS, numUnits}), 0, "DYNAMIC_RNN custom operation: wrong shape of initial cell output array, expected is %s but got %s instead !", ShapeUtils::shapeAsString({bS, numUnits}).c_str(), ShapeUtils::shapeAsString(h0ShapeInfo).c_str());
if(maxTimeStepShapeInfo)
REQUIRE_TRUE(ShapeUtils::shapeAsString(maxTimeStepShapeInfo) == ShapeUtils::shapeAsString({bS}), 0, "DYNAMIC_RNN custom operation: wrong shape of maxTimeStep array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString({bS}).c_str(), ShapeUtils::shapeAsString(maxTimeStepShapeInfo).c_str());
// evaluate output shapeInfos
Nd4jLong *hShapeInfo(nullptr), *hPrevShapeInfo(nullptr);
ALLOCATE(hShapeInfo, block.getWorkspace(), shape::shapeInfoLength(inRank), Nd4jLong);
ALLOCATE(hPrevShapeInfo, block.getWorkspace(), shape::shapeInfoLength(inRank-1), Nd4jLong);
hShapeInfo[0] = inRank;
hPrevShapeInfo[0] = inRank-1;
hShapeInfo[1] = timeMajor ? time : bS;
hShapeInfo[2] = timeMajor ? bS : time;
hPrevShapeInfo[1] = bS;
hShapeInfo[3] = hPrevShapeInfo[2] = numUnits;
ShapeUtils::updateStridesAndType(hShapeInfo, WhShapeInfo, shape::order(xShapeInfo));
ShapeUtils::updateStridesAndType(hPrevShapeInfo, WhShapeInfo, shape::order(xShapeInfo));
return SHAPELIST(CONSTANT(hShapeInfo), CONSTANT(hPrevShapeInfo));
}
}
}