/******************************************************************************* * 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), created on 15.02.2018 // // implementation of gated Recurrent Unit cell // (cf. http://arxiv.org/abs/1406.1078). // Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua Bengio // "Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation" #include #include #include #include namespace nd4j { namespace ops { namespace helpers { ////////////////////////////////////////////////////////////////////////// void gruCell(nd4j::LaunchContext * context, const NDArray* x, const NDArray* hLast, const NDArray* Wru, const NDArray* Wc, const NDArray* bru, const NDArray* bc, NDArray* r, NDArray* u, NDArray* c, NDArray* h) { //Inputs: // x input [bS x inSize] // hLast previous cell output [bS x numUnits], that is at previous time step t-1 // Wru RU weights - [bS, 2*numUnits] - reset and update gates // Wc C weights - [bS, numUnits] - cell gate // bru r and u biases, [2*numUnits] - reset and update gates // bc c biases, [numUnits] - cell gate //Outputs: // r Reset gate output [bS, numUnits] // u Update gate output [bS, numUnits] // c Cell gate output [bS, numUnits] // h current cell output [bS, numUnits] const int nIn = x->sizeAt(1); const int nU = hLast->sizeAt(1); // number of units //Concat inputs: [x, yt-1]: concat([bs,nIn],[bs,nOut]) -> [bs, (nIn+nOut)] nd4j::ops::concat concatOp; std::vector inputs; std::vector targs; std::vector iargs({1}); //Axis = 1 std::vector bargs; inputs.emplace_back(const_cast(x)); inputs.emplace_back(const_cast(hLast)); auto result = concatOp.execute(inputs, targs, iargs, bargs); auto concatOut = result->at(0); //mmul/z for reset and update gates: (x * weight_ux + hLast * weight_xr + b_u) auto m = mmul(*concatOut, *Wru); //mmul: [bs, (nIn+numUnits)]* [(inSize+numUnits), 2*numUnits] = [bs, 4*numUnits] m += (*bru); sigmoidInplace(m); //sigmoid(rz) and sigmoid(uz) auto mr = m({0,0, 0, nU}); auto mu = m({0,0, nU, 2*nU}); r->assign(&mr); u->assign(&mu); //Concatenated inputs: [x, yt-1 .* r] auto yr = (*concatOut)({0,0, nIn, nIn+nU}); yr *= (*r); //c = tanh(x * weight_cx + (hLast .* r) * weight_cr + b_c) MmulHelper::mmul(concatOut, const_cast(Wc), c, 1.0, 0.0); //c = 1.0 * concatOut * Wc + 0.0 * c *c += *bc; tanhInplace(*c); //Output: h = (1-u).*c + u .* hPrev //auto hResult = (*u) * (*hLast) + (1.0f - *u) * (*c); const_cast(h)->assign(&hResult); u->applyPairwiseTransform(pairwise::Multiply, hLast, h, nullptr); //h = u * hLast auto temp = (1.0f - *u); temp *= (*c); (*h) += temp; delete result; } ////////////////////////////////////////////////////////////////////////// void gruTimeLoop(nd4j::LaunchContext * context, const NDArray* x, const NDArray* h0, const NDArray* Wx, const NDArray* Wh, const NDArray* b, NDArray* h) { } ////////////////////////////////////////////////////////////////////////// void gruCellBP(nd4j::LaunchContext * context, const NDArray* x, const NDArray* h0, const NDArray* Wx, const NDArray* Wh, const NDArray* b, const NDArray* dLdh, const NDArray* dLdWx0, const NDArray* dLdWh0, const NDArray* dLdb0, NDArray* dLdx, NDArray* dLdh0, NDArray* dLdWx, NDArray* dLdWh, NDArray* dLdb) { } } } }