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

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Eclipse Migration Initial Commit
2019-06-06 14:21:15 +02:00
/*******************************************************************************
* 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
******************************************************************************/
//
// @aurhot Yurii Shyrma
// @author Alex Black
//
#include <op_boilerplate.h>
#if NOT_EXCLUDED(OP_gruCell)
#include <ops/declarable/CustomOperations.h>
#include<ops/declarable/helpers/gru.h>
namespace nd4j {
namespace ops {
//////////////////////////////////////////////////////////////////////////
CUSTOM_OP_IMPL(gruCell, 6, 4, false, 0, 0) {
auto x = INPUT_VARIABLE(0); // input [bS x inSize]
auto hLast = INPUT_VARIABLE(1); // previous cell output [bS x numUnits], that is at previous time step t-1
auto Wru = INPUT_VARIABLE(2); // RU weights - [(nIn+nOut), 2*numUnits] - reset and update gates (input/recurrent weights)
auto Wc = INPUT_VARIABLE(3); // C weights - [(nIn+nOut), numUnits] - cell gate (input/recurrent weights)
auto bru = INPUT_VARIABLE(4); // reset and update biases, [2*numUnits] - reset and update gates
auto bc = INPUT_VARIABLE(5); // cell biases, [numUnits]
auto r = OUTPUT_VARIABLE(0); // Reset gate output [bS, numUnits]
auto u = OUTPUT_VARIABLE(1); // Update gate output [bS, numUnits]
auto c = OUTPUT_VARIABLE(2); // Cell gate output [bS, numUnits]
auto h = OUTPUT_VARIABLE(3); // current cell output [bS, numUnits]
REQUIRE_TRUE(x->rankOf()==2 && hLast->rankOf()==2, 0, "gruCell: Input ranks must be 2 for inputs 0 and 1 (x, hLast) - got %i, %i", x->rankOf(), hLast->rankOf());
const int rank = x->rankOf();
const auto bS = x->sizeAt(0);
const auto nIn = x->sizeAt(1);
const auto nU = hLast->sizeAt(1);
REQUIRE_TRUE(x->sizeAt(0) == hLast->sizeAt(0), 0, "gruCell: Input minibatch sizes (dimension 0) must be same for x and hLast");
REQUIRE_TRUE(Wru->rankOf()==2 && Wc->rankOf()==2, 0, "gruCell: weight arrays (Wru, Wc) arrays must be 2, got %i and %i", Wru->rankOf(), Wc->rankOf());
REQUIRE_TRUE(Wru->sizeAt(0)==(nIn+nU) && Wc->sizeAt(0)==(nIn+nU), 0, "gruCell: Weights size(0) must be equal to inSize + numUnits, got %i", Wru->sizeAt(0));
REQUIRE_TRUE(Wru->sizeAt(1)==(2*nU), 0, "gruCell: Weights (reset and update) size(1) must be equal to 2*numUnits, got %i", Wru->sizeAt(1));
REQUIRE_TRUE(Wc->sizeAt(1)==nU, 0, "gruCell: Weights (cell) size(1) must be equal to numUnits, got %i", Wc->sizeAt(1));
REQUIRE_TRUE(bru->rankOf()==1 && bru->sizeAt(0)==(2*nU), 0, "gruCell: reset/update biases must be rank 1, size 2*numUnits");
REQUIRE_TRUE(bc->rankOf()==1 && bc->sizeAt(0)==nU, 0, "gruCell: cell biases must be rank 1, size numUnits");
REQUIRE_TRUE(r->rankOf()==2 && u->rankOf()==2 && c->rankOf()==2 && h->rankOf()==2 &&
r->sizeAt(0)==bS && u->sizeAt(0)==bS && c->sizeAt(0)==bS && h->sizeAt(0)==bS &&
r->sizeAt(1)==nU && u->sizeAt(1)==nU && c->sizeAt(1)==nU && h->sizeAt(1)==nU,
0, "gruCell: Output arrays must all be rank 2 with size(0) == batchSize and size(1) == numUnits");
helpers::gruCell(block.launchContext(), x, hLast, Wru, Wc, bru, bc, r, u, c, h);
return Status::OK();
}
DECLARE_TYPES(gruCell) {
getOpDescriptor()
->setAllowedInputTypes(0, nd4j::DataType::ANY)
->setAllowedInputTypes(1, {ALL_FLOATS})
->setAllowedInputTypes(2, {ALL_FLOATS})
->setAllowedInputTypes(3, {ALL_FLOATS})
->setAllowedInputTypes(4, {ALL_FLOATS})
->setAllowedOutputTypes({ALL_FLOATS});
}
DECLARE_SHAPE_FN(gruCell) {
auto x = inputShape->at(0); // input [bS x inSize]
auto hLast = inputShape->at(1); // previous cell output [bS x numUnits], that is at previous time step t-1
auto Wru = inputShape->at(2); // RU weights - [(nIn+nOut), 2*numUnits] - reset and update gates (input/recurrent weights)
auto Wc = inputShape->at(3); // C weights - [(nIn+nOut), numUnits] - cell gate (input/recurrent weights)
auto bru = inputShape->at(4); // reset and update biases, [2*numUnits] - reset and update gates
auto bc = inputShape->at(5); // cell biases, [numUnits]
REQUIRE_TRUE(shape::rank(x)==2 && shape::rank(hLast)==2, 0, "gruCell: Input ranks must be 2 for inputs 0 and 1 (x, hLast) - got %i, %i", shape::rank(x), shape::rank(hLast));
const int rank = x[0];
const auto bS = x[1];
const auto inSize = x[2];
const auto numUnits = hLast[2];
REQUIRE_TRUE(x[1] == hLast[1], 0, "gruCell: Input minibatch sizes (dimension 0) must be same for x and hLast");
REQUIRE_TRUE(shape::rank(Wru)==2 && shape::rank(Wc)==2, 0, "gruCell: weight arrays (Wru, Wc) arrays must be 2, got %i and %i", shape::rank(Wru), shape::rank(Wc));
REQUIRE_TRUE(Wru[1]==(inSize+numUnits) && Wc[1]==(inSize+numUnits), 0, "gruCell: Weights size(0) must be equal to inSize + numUnits, got %i and %i", Wru[1], Wc[1]);
REQUIRE_TRUE(Wru[2]==(2*numUnits), 0, "gruCell: Weights (reset and update) size(1) must be equal to 2*numUnits, got %i", Wru[2]);
REQUIRE_TRUE(Wc[2]==numUnits, 0, "gruCell: Weights (cell) size(1) must be equal to numUnits, got %i", Wc[2]);
REQUIRE_TRUE(shape::rank(bru)==1 && bru[1]==(2*numUnits), 0, "gruCell: reset/update biases must be rank 1, size 2*numUnits");
REQUIRE_TRUE(shape::rank(bc)==1 && bc[1]==numUnits, 0, "gruCell: cell biases must be rank 1, size numUnits");
Nd4jLong *s0(nullptr);
ALLOCATE(s0, block.getWorkspace(), shape::shapeInfoLength(rank), Nd4jLong);// [bS x numUnits]
s0[0] = rank;
s0[1] = bS;
s0[2] = numUnits;
ShapeUtils::updateStridesAndType(s0, x, shape::order(hLast));
auto ts0 = ConstantShapeHelper::getInstance()->createFromExisting(s0, block.workspace());
//4 output shapes, all [bs, numUnits]
return SHAPELIST(ts0, ts0, ts0, ts0);
}
//////////////////////////////////////////////////////////////////////////
CUSTOM_OP_IMPL(gruCell_bp, 6, 5, false, 0, 0) {
auto x = INPUT_VARIABLE(0); // input [bS x iS]
auto hi = INPUT_VARIABLE(1); // previous cell output [bS x nU]
auto Wx = INPUT_VARIABLE(2); // input-to-hidden weights, [iS x 3*nU]
auto Wh = INPUT_VARIABLE(3); // hidden-to-hidden weights, [nU x 3*nU]
auto b = INPUT_VARIABLE(4); // biases, [3*nU]
auto dLdh = INPUT_VARIABLE(5); // gradient wrt output, [bS,nU], that is epsilon_next
auto dLdWxi = block.width() > 6 ? INPUT_VARIABLE(6) : nullptr; // gradient wrt Wx at previous time step, [iS, 3*nU]
auto dLdWhi = block.width() > 7 ? INPUT_VARIABLE(7) : nullptr; // gradient wrt Wh at previous time step, [nU, 3*nU]
auto dLdbi = block.width() > 8 ? INPUT_VARIABLE(8) : nullptr; // gradient wrt b at previous time step, [3*nU]
auto dLdx = OUTPUT_VARIABLE(0); // gradient wrt x, [bS, iS], that is epsilon
auto dLdhi = OUTPUT_VARIABLE(1); // gradient wrt hi, [bS, nU]
auto dLdWx = OUTPUT_VARIABLE(2); // gradient wrt Wx, [iS, 3*nU]
auto dLdWh = OUTPUT_VARIABLE(3); // gradient wrt Wh, [nU, 3*nU]
auto dLdb = OUTPUT_VARIABLE(4); // gradient wrt biases, [3*nU]
const int rank = x->rankOf(); // = 2
const Nd4jLong bS = x->sizeAt(0);
const Nd4jLong iS = x->sizeAt(1);
const Nd4jLong nU = hi->sizeAt(1);
const std::string hiShape = ShapeUtils::shapeAsString(hi);
const std::string hiCorrectShape = ShapeUtils::shapeAsString({bS, nU});
const std::string wxShape = ShapeUtils::shapeAsString(Wx);
const std::string wxCorrectShape = ShapeUtils::shapeAsString({iS, 3*nU});
const std::string whShape = ShapeUtils::shapeAsString(Wh);
const std::string whCorrectShape = ShapeUtils::shapeAsString({nU, 3*nU});
const std::string bShape = ShapeUtils::shapeAsString(b);
const std::string bCorrectShape = ShapeUtils::shapeAsString({3*nU});
const std::string dLdhShape = ShapeUtils::shapeAsString(dLdh);
const std::string dLdhCorrectShape = ShapeUtils::shapeAsString({bS, nU});
REQUIRE_TRUE(hiShape == hiCorrectShape, 0, "GRU_CELL_BP op: wrong shape of previous cell output array, expected is %s, but got %s instead !", hiCorrectShape.c_str(), hiShape.c_str());
REQUIRE_TRUE(wxShape == wxCorrectShape, 0, "GRU_CELL_BP op: wrong shape of input-to-hidden weights array, expected is %s, but got %s instead !", wxCorrectShape.c_str(), wxShape.c_str());
REQUIRE_TRUE(whShape == whCorrectShape, 0, "GRU_CELL_BP op: wrong shape of hidden-to-hidden weights array, expected is %s, but got %s instead !", whCorrectShape.c_str(), whShape.c_str());
REQUIRE_TRUE(bShape == bCorrectShape, 0, "GRU_CELL_BP op: wrong shape of biases array, expected is %s, but got %s instead !", bCorrectShape.c_str(), bShape.c_str());
REQUIRE_TRUE(dLdhShape == dLdhCorrectShape, 0, "GRU_CELL_BP op: wrong shape of dLdh array (epsilon_next), expected is %s, but got %s instead !", dLdhCorrectShape.c_str(), dLdhShape.c_str());
if(dLdWxi != nullptr) {
const std::string dLdWxiShape = ShapeUtils::shapeAsString(dLdWxi);
const std::string dLdWxiCorrectShape = ShapeUtils::shapeAsString({iS, 3*nU});
REQUIRE_TRUE(dLdWxiShape == dLdWxiCorrectShape, 0, "GRU_CELL_BP op: wrong shape of dLdWxi array (gradient wrt Wx at previous time step), expected is %s, but got %s instead !", dLdWxiCorrectShape.c_str(), dLdWxiShape.c_str());
}
if(dLdWhi != nullptr) {
const std::string dLdWhiShape = ShapeUtils::shapeAsString(dLdWhi);
const std::string dLdWhiCorrectShape = ShapeUtils::shapeAsString({nU, 3*nU});
REQUIRE_TRUE(dLdWhiShape == dLdWhiCorrectShape, 0, "GRU_CELL_BP op: wrong shape of dLdWhi array (gradient wrt Wh at previous time step), expected is %s, but got %s instead !", dLdWhiCorrectShape.c_str(), dLdWhiShape.c_str());
}
if(dLdbi != nullptr) {
const std::string dLdbiShape = ShapeUtils::shapeAsString(dLdbi);
const std::string dLdbiCorrectShape = ShapeUtils::shapeAsString({3*nU});
REQUIRE_TRUE(dLdbiShape == dLdbiCorrectShape, 0, "GRU_CELL_BP op: wrong shape of dLdbi array (gradient wrt biases at previous time step), expected is %s, but got %s instead !", dLdbiCorrectShape.c_str(), dLdbiShape.c_str());
}
helpers::gruCellBP(block.launchContext(), x, hi, Wx, Wh, b, dLdh, dLdWxi, dLdWhi, dLdbi, dLdx, dLdhi, dLdWx, dLdWh, dLdb);
return Status::OK();
}
DECLARE_TYPES(gruCell_bp) {
getOpDescriptor()
->setAllowedInputTypes(0, nd4j::DataType::ANY)
->setAllowedInputTypes(1, {ALL_FLOATS})
->setAllowedInputTypes(2, {ALL_FLOATS})
->setAllowedInputTypes(3, {ALL_FLOATS})
->setAllowedInputTypes(4, {ALL_FLOATS})
->setAllowedInputTypes(5, {ALL_FLOATS})
->setAllowedInputTypes(6, {ALL_FLOATS})
->setAllowedInputTypes(7, {ALL_FLOATS})
->setAllowedInputTypes(8, {ALL_FLOATS})
->setAllowedOutputTypes({ALL_FLOATS});
}
DECLARE_SHAPE_FN(gruCell_bp) {
auto xShapeInfo = inputShape->at(0); // [bS x iS]
auto hiShapeInfo = inputShape->at(1); // [bS x nU]
auto wxShapeInfo = inputShape->at(2); // [iS x 3*nU]
auto whShapeInfo = inputShape->at(3); // [nU x 3*nU]
auto bShapeInfo = inputShape->at(4); // [3*nU]
auto dLdhShapeInfo = inputShape->at(5); // [bS x nU]
const int rank = xShapeInfo[0]; // = 2
const Nd4jLong bS = xShapeInfo[1];
const Nd4jLong iS = xShapeInfo[2];
const Nd4jLong nU = hiShapeInfo[2];
const std::string hiShape = ShapeUtils::shapeAsString(hiShapeInfo);
const std::string hiCorrectShape = ShapeUtils::shapeAsString({bS, nU});
const std::string wxShape = ShapeUtils::shapeAsString(wxShapeInfo);
const std::string wxCorrectShape = ShapeUtils::shapeAsString({iS, 3*nU});
const std::string whShape = ShapeUtils::shapeAsString(whShapeInfo);
const std::string whCorrectShape = ShapeUtils::shapeAsString({nU, 3*nU});
const std::string bShape = ShapeUtils::shapeAsString(bShapeInfo);
const std::string bCorrectShape = ShapeUtils::shapeAsString({3*nU});
const std::string dLdhShape = ShapeUtils::shapeAsString(dLdhShapeInfo);
const std::string dLdhCorrectShape = ShapeUtils::shapeAsString({bS, nU});
REQUIRE_TRUE(hiShape == hiCorrectShape, 0, "GRU_CELL_BP op: wrong shape of previous cell output array, expected is %s, but got %s instead !", hiCorrectShape.c_str(), hiShape.c_str());
REQUIRE_TRUE(wxShape == wxCorrectShape, 0, "GRU_CELL_BP op: wrong shape of input-to-hidden weights array, expected is %s, but got %s instead !", wxCorrectShape.c_str(), wxShape.c_str());
REQUIRE_TRUE(whShape == whCorrectShape, 0, "GRU_CELL_BP op: wrong shape of hidden-to-hidden weights array, expected is %s, but got %s instead !", whCorrectShape.c_str(), whShape.c_str());
REQUIRE_TRUE(bShape == bCorrectShape, 0, "GRU_CELL_BP op: wrong shape of biases array, expected is %s, but got %s instead !", bCorrectShape.c_str(), bShape.c_str());
REQUIRE_TRUE(dLdhShape == dLdhCorrectShape, 0, "GRU_CELL_BP op: wrong shape of dLdh array (epsilon_next), expected is %s, but got %s instead !", dLdhCorrectShape.c_str(), dLdhShape.c_str());
if(block.width() > 6) {
Nd4jLong* dLdWxiShapeInfo = inputShape->at(6); // [iS x 3*nU]
const std::string dLdWxiShape = ShapeUtils::shapeAsString(dLdWxiShapeInfo);
const std::string dLdWxiCorrectShape = ShapeUtils::shapeAsString({iS, 3*nU});
REQUIRE_TRUE(dLdWxiShape == dLdWxiCorrectShape, 0, "GRU_CELL_BP op: wrong shape of dLdWxi array (gradient wrt Wx at previous time step), expected is %s, but got %s instead !", dLdWxiCorrectShape.c_str(), dLdWxiShape.c_str());
}
if(block.width() > 7) {
Nd4jLong* dLdWhiShapeInfo = inputShape->at(7); // [nU x 3*nU]
const std::string dLdWhiShape = ShapeUtils::shapeAsString(dLdWhiShapeInfo);
const std::string dLdWhiCorrectShape = ShapeUtils::shapeAsString({nU, 3*nU});
REQUIRE_TRUE(dLdWhiShape == dLdWhiCorrectShape, 0, "GRU_CELL_BP op: wrong shape of dLdWhi array (gradient wrt Wh at previous time step), expected is %s, but got %s instead !", dLdWhiCorrectShape.c_str(), dLdWhiShape.c_str());
}
if(block.width() > 8) {
Nd4jLong* dLdbiShapeInfo = inputShape->at(8); // [3*nU]
const std::string dLdbiShape = ShapeUtils::shapeAsString(dLdbiShapeInfo);
const std::string dLdbiCorrectShape = ShapeUtils::shapeAsString({3*nU});
REQUIRE_TRUE(dLdbiShape == dLdbiCorrectShape, 0, "GRU_CELL_BP op: wrong shape of dLdbi array (gradient wrt biases at previous time step), expected is %s, but got %s instead !", dLdbiCorrectShape.c_str(), dLdbiShape.c_str());
}
Nd4jLong *dLdxShapeInfo = nullptr;
COPY_SHAPE(xShapeInfo, dLdxShapeInfo);
Nd4jLong *dLdhiShapeInfo = nullptr;
COPY_SHAPE(hiShapeInfo, dLdhiShapeInfo);
Nd4jLong *dLdWxShapeInfo = nullptr;
COPY_SHAPE(wxShapeInfo, dLdWxShapeInfo);
Nd4jLong *dLdWhShapeInfo = nullptr;
COPY_SHAPE(whShapeInfo, dLdWhShapeInfo);
Nd4jLong *dLdbShapeInfo = nullptr;
COPY_SHAPE(bShapeInfo, dLdbShapeInfo);
return SHAPELIST(dLdxShapeInfo, dLdhiShapeInfo, dLdWxShapeInfo, dLdWhShapeInfo, dLdbShapeInfo);
}
}
}
#endif