189 lines
11 KiB
C++
189 lines
11 KiB
C++
/*******************************************************************************
|
|
* Copyright (c) 2015-2018 Skymind, Inc.
|
|
* Copyright (c) 2020 Konduit K.K.
|
|
*
|
|
* 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)
|
|
//
|
|
|
|
#include <system/op_boilerplate.h>
|
|
#if NOT_EXCLUDED(OP_gru)
|
|
|
|
#include <ops/declarable/CustomOperations.h>
|
|
#include<ops/declarable/helpers/gru.h>
|
|
|
|
namespace sd {
|
|
namespace ops {
|
|
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
CUSTOM_OP_IMPL(gru, 5, 1, false, 0, 0) {
|
|
auto x = INPUT_VARIABLE(0); // input [time, bS, nIn]
|
|
auto hI = INPUT_VARIABLE(1); // initial cell output (at time step = 0) [bS, nOut]
|
|
|
|
auto Wx = INPUT_VARIABLE(2); // input-to-hidden weights, [nIn, 3*nOut]
|
|
auto Wh = INPUT_VARIABLE(3); // hidden-to-hidden weights, [nOut, 3*nOut]
|
|
auto b = INPUT_VARIABLE(4); // biases, [3*nOut]
|
|
|
|
auto h = OUTPUT_VARIABLE(0); // cell outputs [time, bS, nOut], that is per each time step
|
|
|
|
const int bS = x->sizeAt(1);
|
|
const int nIn = x->sizeAt(2);
|
|
const int nOut = hI->sizeAt(1);
|
|
|
|
const std::vector<Nd4jLong> h0CorrectShape = {bS, nOut};
|
|
const std::vector<Nd4jLong> wxCorrectShape = {nIn, 3*nOut};
|
|
const std::vector<Nd4jLong> whCorrectShape = {nOut, 3*nOut};
|
|
const std::vector<Nd4jLong> bCorrectShape = {3*nOut};
|
|
|
|
REQUIRE_TRUE(hI->isSameShape(h0CorrectShape), 0, "GRU operation: wrong shape of previous cell output array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(h0CorrectShape).c_str(), ShapeUtils::shapeAsString(hI).c_str());
|
|
REQUIRE_TRUE(Wx->isSameShape(wxCorrectShape), 0, "GRU operation: wrong shape of input-to-hidden weights array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(wxCorrectShape).c_str(), ShapeUtils::shapeAsString(Wx).c_str());
|
|
REQUIRE_TRUE(Wh->isSameShape(whCorrectShape), 0, "GRU operation: wrong shape of hidden-to-hidden weights array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(whCorrectShape).c_str(), ShapeUtils::shapeAsString(Wh).c_str());
|
|
REQUIRE_TRUE(b->isSameShape(bCorrectShape), 0, "GRU operation: wrong shape of biases array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(bCorrectShape).c_str(), ShapeUtils::shapeAsString(b).c_str());
|
|
|
|
helpers::gruTimeLoop(block.launchContext(), x, hI, Wx, Wh, b, h);
|
|
|
|
return Status::OK();
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
DECLARE_TYPES(gru) {
|
|
getOpDescriptor()
|
|
->setAllowedInputTypes(sd::DataType::ANY)
|
|
->setAllowedOutputTypes({ALL_FLOATS});
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
DECLARE_SHAPE_FN(gru) {
|
|
|
|
auto x = INPUT_VARIABLE(0); // input [time, bS, nIn]
|
|
auto hI = INPUT_VARIABLE(1); // initial cell output (at time step = 0) [bS, nOut]
|
|
|
|
auto Wx = INPUT_VARIABLE(2); // input-to-hidden weights, [nIn, 3*nOut]
|
|
auto Wh = INPUT_VARIABLE(3); // hidden-to-hidden weights, [nOut, 3*nOut]
|
|
auto b = INPUT_VARIABLE(4); // biases, [3*nOut]
|
|
|
|
const int time = x->sizeAt(0);
|
|
const int bS = x->sizeAt(1);
|
|
const int nIn = x->sizeAt(2);
|
|
const int nOut = hI->sizeAt(1);
|
|
|
|
const std::vector<Nd4jLong> h0CorrectShape = {bS, nOut};
|
|
const std::vector<Nd4jLong> wxCorrectShape = {nIn, 3*nOut};
|
|
const std::vector<Nd4jLong> whCorrectShape = {nOut, 3*nOut};
|
|
const std::vector<Nd4jLong> bCorrectShape = {3*nOut};
|
|
|
|
REQUIRE_TRUE(hI->isSameShape(h0CorrectShape), 0, "GRU operation: wrong shape of previous cell output array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(h0CorrectShape).c_str(), ShapeUtils::shapeAsString(hI).c_str());
|
|
REQUIRE_TRUE(Wx->isSameShape(wxCorrectShape), 0, "GRU operation: wrong shape of input-to-hidden weights array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(wxCorrectShape).c_str(), ShapeUtils::shapeAsString(Wx).c_str());
|
|
REQUIRE_TRUE(Wh->isSameShape(whCorrectShape), 0, "GRU operation: wrong shape of hidden-to-hidden weights array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(whCorrectShape).c_str(), ShapeUtils::shapeAsString(Wh).c_str());
|
|
REQUIRE_TRUE(b->isSameShape(bCorrectShape), 0, "GRU operation: wrong shape of biases array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(bCorrectShape).c_str(), ShapeUtils::shapeAsString(b).c_str());
|
|
|
|
auto hShapeInfo = ConstantShapeHelper::getInstance().createShapeInfo(hI->dataType(), hI->ordering(), {time, bS, nOut});
|
|
|
|
return SHAPELIST(hShapeInfo);
|
|
}
|
|
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
CUSTOM_OP_IMPL(gru_bp, 6, 5, false, 0, 0) {
|
|
|
|
auto x = INPUT_VARIABLE(0); // input [time, bS, nIn]
|
|
auto hI = INPUT_VARIABLE(1); // initial cell output (at time step = 0) [bS, nOut]
|
|
|
|
auto Wx = INPUT_VARIABLE(2); // input-to-hidden weights, [nIn, 3*nOut]
|
|
auto Wh = INPUT_VARIABLE(3); // hidden-to-hidden weights, [nOut, 3*nOut]
|
|
auto b = INPUT_VARIABLE(4); // biases, [3*nOut]
|
|
|
|
auto dLdh = INPUT_VARIABLE(5); // gradient vs. ff output, [time, bS, nOut]
|
|
|
|
auto dLdx = OUTPUT_VARIABLE(0); // gradient vs. ff input, [time, bS, nIn]
|
|
auto dLdhI = OUTPUT_NULLIFIED(1); // gradient vs. initial cell output, [bS, nOut]
|
|
auto dLdWx = OUTPUT_NULLIFIED(2); // gradient vs. input-to-hidden weights, [nIn, 3*nOut]
|
|
auto dLdWh = OUTPUT_NULLIFIED(3); // gradient vs. hidden-to-hidden weights, [nOut, 3*nOut]
|
|
auto dLdb = OUTPUT_NULLIFIED(4); // gradient vs. biases [3*nOut]
|
|
|
|
const int time = x->sizeAt(0);
|
|
const int bS = x->sizeAt(1);
|
|
const int nIn = x->sizeAt(2);
|
|
const int nOut = hI->sizeAt(1);
|
|
|
|
const std::vector<Nd4jLong> h0CorrectShape = {bS, nOut};
|
|
const std::vector<Nd4jLong> wxCorrectShape = {nIn, 3*nOut};
|
|
const std::vector<Nd4jLong> whCorrectShape = {nOut, 3*nOut};
|
|
const std::vector<Nd4jLong> bCorrectShape = {3*nOut};
|
|
const std::vector<Nd4jLong> hCorrectShape = {time, bS, nOut};
|
|
|
|
REQUIRE_TRUE(hI->isSameShape(h0CorrectShape), 0, "GRU_BP operation: wrong shape of previous cell output array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(h0CorrectShape).c_str(), ShapeUtils::shapeAsString(hI).c_str());
|
|
REQUIRE_TRUE(Wx->isSameShape(wxCorrectShape), 0, "GRU_BP operation: wrong shape of input-to-hidden weights array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(wxCorrectShape).c_str(), ShapeUtils::shapeAsString(Wx).c_str());
|
|
REQUIRE_TRUE(Wh->isSameShape(whCorrectShape), 0, "GRU_BP operation: wrong shape of hidden-to-hidden weights array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(whCorrectShape).c_str(), ShapeUtils::shapeAsString(Wh).c_str());
|
|
REQUIRE_TRUE(b->isSameShape(bCorrectShape), 0, "GRU_BP operation: wrong shape of biases array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(bCorrectShape).c_str(), ShapeUtils::shapeAsString(b).c_str());
|
|
REQUIRE_TRUE(dLdh->isSameShape(hCorrectShape),0, "GRU_BP operation: wrong shape of gradient vs. ff output, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(hCorrectShape).c_str(), ShapeUtils::shapeAsString(dLdh).c_str());
|
|
|
|
helpers::gruTimeLoopBp(block.launchContext(), x, hI, Wx, Wh, b, dLdh, dLdx, dLdhI, dLdWx, dLdWh, dLdb);
|
|
|
|
return Status::OK();
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
DECLARE_TYPES(gru_bp) {
|
|
getOpDescriptor()
|
|
->setAllowedInputTypes(sd::DataType::ANY)
|
|
->setAllowedOutputTypes({ALL_FLOATS});
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////
|
|
DECLARE_SHAPE_FN(gru_bp) {
|
|
|
|
auto x = INPUT_VARIABLE(0); // input [time, bS, nIn]
|
|
auto hI = INPUT_VARIABLE(1); // initial cell output (at time step = 0) [bS, nOut]
|
|
|
|
auto Wx = INPUT_VARIABLE(2); // input-to-hidden weights, [nIn, 3*nOut]
|
|
auto Wh = INPUT_VARIABLE(3); // hidden-to-hidden weights, [nOut, 3*nOut]
|
|
auto b = INPUT_VARIABLE(4); // biases, [3*nOut]
|
|
|
|
auto dLdh = INPUT_VARIABLE(5); // gradient vs. ff output, [time, bS, nOut]
|
|
|
|
const int time = x->sizeAt(0);
|
|
const int bS = x->sizeAt(1);
|
|
const int nIn = x->sizeAt(2);
|
|
const int nOut = hI->sizeAt(1);
|
|
|
|
const std::vector<Nd4jLong> h0CorrectShape = {bS, nOut};
|
|
const std::vector<Nd4jLong> wxCorrectShape = {nIn, 3*nOut};
|
|
const std::vector<Nd4jLong> whCorrectShape = {nOut, 3*nOut};
|
|
const std::vector<Nd4jLong> bCorrectShape = {3*nOut};
|
|
const std::vector<Nd4jLong> hCorrectShape = {time, bS, nOut};
|
|
|
|
REQUIRE_TRUE(hI->isSameShape(h0CorrectShape), 0, "GRU_BP operation: wrong shape of previous cell output array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(h0CorrectShape).c_str(), ShapeUtils::shapeAsString(hI).c_str());
|
|
REQUIRE_TRUE(Wx->isSameShape(wxCorrectShape), 0, "GRU_BP operation: wrong shape of input-to-hidden weights array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(wxCorrectShape).c_str(), ShapeUtils::shapeAsString(Wx).c_str());
|
|
REQUIRE_TRUE(Wh->isSameShape(whCorrectShape), 0, "GRU_BP operation: wrong shape of hidden-to-hidden weights array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(whCorrectShape).c_str(), ShapeUtils::shapeAsString(Wh).c_str());
|
|
REQUIRE_TRUE(b->isSameShape(bCorrectShape), 0, "GRU_BP operation: wrong shape of biases array, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(bCorrectShape).c_str(), ShapeUtils::shapeAsString(b).c_str());
|
|
REQUIRE_TRUE(dLdh->isSameShape(hCorrectShape),0, "GRU_BP operation: wrong shape of gradient vs. ff output, expected is %s, but got %s instead !", ShapeUtils::shapeAsString(hCorrectShape).c_str(), ShapeUtils::shapeAsString(dLdh).c_str());
|
|
|
|
auto dLdxShapeInfo = ConstantShapeHelper::getInstance().createShapeInfo(dLdh->dataType(), x->shapeInfo());
|
|
auto dLdhIShapeInfo = ConstantShapeHelper::getInstance().createShapeInfo(dLdh->dataType(), hI->shapeInfo());
|
|
auto dLdWxShapeInfo = ConstantShapeHelper::getInstance().createShapeInfo(dLdh->dataType(), Wx->shapeInfo());
|
|
auto dLdWhShapeInfo = ConstantShapeHelper::getInstance().createShapeInfo(dLdh->dataType(), Wh->shapeInfo());
|
|
auto dLdbShapeInfo = ConstantShapeHelper::getInstance().createShapeInfo(dLdh->dataType(), b->shapeInfo());
|
|
|
|
return SHAPELIST(dLdxShapeInfo, dLdhIShapeInfo, dLdWxShapeInfo, dLdWhShapeInfo, dLdbShapeInfo);
|
|
}
|
|
|
|
}
|
|
}
|
|
|
|
|
|
#endif |