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