chore: import upstream snapshot with attribution
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wehub-resource-sync
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/* ******************************************************************************
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*
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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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* See the NOTICE file distributed with this work for additional
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* information regarding copyright ownership.
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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, created on 05.04.2018
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//
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#include <ops/declarable/CustomOperations.h>
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#include <ops/declarable/helpers/rnn.h>
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#if NOT_EXCLUDED(OP_dynamic_rnn)
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namespace sd {
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namespace ops {
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//////////////////////////////////////////////////////////////////////////
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CUSTOM_OP_IMPL(dynamic_rnn, 4, 2, false, 0, 0) {
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auto x = INPUT_VARIABLE(0); // input [time x bS x inSize] or [bS x time x inSize], depends on timeMajor parameter
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auto Wx = INPUT_VARIABLE(1); // input-to-hidden weights, [inSize x numUnits]
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auto Wh = INPUT_VARIABLE(2); // hidden-to-hidden weights, [numUnits x numUnits]
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auto b = INPUT_VARIABLE(3); // biases for, [2*numUnits]
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NDArray* h0 = nullptr; // initial cell output (at time step = 0) [bS x numUnits]
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NDArray* maxTimeStep =
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nullptr; // vector [bS] containing integer values within [0,time), each element of this vector set max time step
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// per each input in batch, this means there are no calculations for time >= maxTimeStep
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const int timeMajor =
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block.getIArguments()->size() > 0 ? INT_ARG(0) : 0; // if true then [time, bS, ...], else [bS, time, ...]
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if (block.width() == 5) {
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if ((*INPUT_VARIABLE(4)).rankOf() == 2)
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h0 = INPUT_VARIABLE(4);
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else
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maxTimeStep = INPUT_VARIABLE(4);
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} else if (block.width() == 6) {
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h0 = INPUT_VARIABLE(4);
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maxTimeStep = INPUT_VARIABLE(5);
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}
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auto h = OUTPUT_VARIABLE(0); // cell outputs [time x bS x numUnits] or [bS x time x numUnits], depends on timeMajor parameter
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auto hFinal = OUTPUT_VARIABLE(1); // at the end it will store cell final non-zero output [bS x numUnits]
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REQUIRE_TRUE(x->rankOf() == 3, 0,
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"DYNAMIC_RNN custom operation: input array x must have rank = 3, but got %i instead !", x->rankOf());
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REQUIRE_TRUE(Wx->rankOf() == 2, 0,
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"DYNAMIC_RNN custom operation: input-to-hidden weights array must have rank = 2, but got %i instead !",
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Wx->rankOf());
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const int inRank = x->rankOf();
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const int time = timeMajor ? x->sizeAt(0) : x->sizeAt(1);
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const int bS = timeMajor ? x->sizeAt(1) : x->sizeAt(0);
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const int numUnits = Wx->sizeAt(1);
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std::vector<LongType> expectedWhShape = {numUnits, numUnits};
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std::vector<LongType> expectedBShape = {2 * numUnits};
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REQUIRE_TRUE(Wh->isSameShape(expectedWhShape), 0,
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"DYNAMIC_RNN custom operation: wrong shape of hidden-to-hidden weights array, expected is %s, but got "
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"%s instead !",
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ShapeUtils::shapeAsString(expectedWhShape).c_str(), ShapeUtils::shapeAsString(Wh).c_str());
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REQUIRE_TRUE(b->isSameShape(expectedBShape), 0,
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"DYNAMIC_RNN custom operation: wrong shape of biases array, expected is %s, but got %s instead !",
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ShapeUtils::shapeAsString(expectedBShape).c_str(), ShapeUtils::shapeAsString(b).c_str());
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if (h0) {
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std::vector<LongType> expectedh0Shape = {bS, numUnits};
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REQUIRE_TRUE(
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h0->isSameShape(expectedh0Shape), 0,
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"DYNAMIC_RNN custom operation: wrong shape of initial cell output array, expected is %s but got %s instead !",
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ShapeUtils::shapeAsString(expectedh0Shape).c_str(), ShapeUtils::shapeAsString(h0).c_str());
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}
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if (maxTimeStep) {
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std::vector<LongType> expectedmaxTimeStepShape = {bS};
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REQUIRE_TRUE(maxTimeStep->isSameShape(expectedmaxTimeStepShape), 0,
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"DYNAMIC_RNN custom operation: wrong shape of maxTimeStep array, expected is %s, but got %s instead !",
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ShapeUtils::shapeAsString(expectedmaxTimeStepShape).c_str(),
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ShapeUtils::shapeAsString(maxTimeStep).c_str());
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}
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if (timeMajor == false) {
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std::vector<sd::LongType> perm = {1, 0, 2};
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x = x->permute(perm, false, false); // [bS x time x inSize] -> [time x bS x inSize]
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h = h->permute(perm, false, false); // [bS x time x numUnits] -> [time x bS x numUnits]
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}
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helpers::rnnTimeLoop(block.launchContext(), x, Wx, Wh, b, h0, maxTimeStep, h, hFinal);
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if (timeMajor == false) {
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delete x;
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delete h;
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}
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return Status::OK;
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}
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DECLARE_TYPES(dynamic_rnn) {
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getOpDescriptor()
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->setAllowedInputTypes(0, ANY)
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->setAllowedInputTypes(1, {ALL_FLOATS})
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->setAllowedInputTypes(2, {ALL_FLOATS})
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->setAllowedInputTypes(3, {ALL_FLOATS})
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->setAllowedInputTypes(4, {ALL_FLOATS, ALL_INTS})
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->setAllowedInputTypes(5, {ALL_FLOATS, ALL_INTS})
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->setAllowedOutputTypes(0, {ALL_FLOATS})
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->setAllowedOutputTypes(1, {ALL_FLOATS});
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}
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DECLARE_SHAPE_FN(dynamic_rnn) {
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auto xShapeInfo =
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inputShape->at(0); // input [time x bS x inSize] or [bS x time x inSize], depends on timeMajor parameter
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auto WxShapeInfo = inputShape->at(1); // input-to-hidden weights, [inSize x numUnits]
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auto WhShapeInfo = inputShape->at(2); // hidden-to-hidden weights, [numUnits x numUnits]
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auto bShapeInfo = inputShape->at(3); // biases for, [2*numUnits]
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LongType const* h0ShapeInfo = nullptr; // initial cell output (at time step = 0) [bS x numUnits]
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LongType const* maxTimeStepShapeInfo =
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nullptr; // vector [bS] containing integer values within [0,time), each element of this vector set max time step
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// per each input in batch, this means there are no calculations for time >= maxTimeStep
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const int timeMajor =
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block.getIArguments()->size() > 0 ? INT_ARG(0) : 0; // if true then [time, bS, ...], else [bS, time, ...]
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if (block.width() == 5) {
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if (inputShape->at(4)[0] == 2)
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h0ShapeInfo = inputShape->at(4);
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else
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maxTimeStepShapeInfo = inputShape->at(4);
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} else if (block.width() == 6) {
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h0ShapeInfo = inputShape->at(4);
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maxTimeStepShapeInfo = inputShape->at(5);
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}
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REQUIRE_TRUE(xShapeInfo[0] == 3, 0,
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"DYNAMIC_RNN custom operation: input array x must have rank = 3, but got %i instead !", xShapeInfo[0]);
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REQUIRE_TRUE(WxShapeInfo[0] == 2, 0,
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"DYNAMIC_RNN custom operation: input-to-hidden weights array must have rank = 2, but got %i instead !",
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WxShapeInfo[0]);
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const int inRank = xShapeInfo[0];
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const int time = timeMajor ? xShapeInfo[1] : xShapeInfo[2];
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const int bS = timeMajor ? xShapeInfo[2] : xShapeInfo[1];
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const int numUnits = WxShapeInfo[2];
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std::vector<LongType> expectedWhShape = {numUnits, numUnits};
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std::vector<LongType> expectedBShape = {2 * numUnits};
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REQUIRE_TRUE(ShapeUtils::areShapesEqual(WhShapeInfo, expectedWhShape), 0,
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"DYNAMIC_RNN custom operation: wrong shape of hidden-to-hidden weights array, expected is %s, but got "
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"%s instead !",
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ShapeUtils::shapeAsString(expectedWhShape).c_str(), ShapeUtils::shapeAsString(WhShapeInfo).c_str());
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REQUIRE_TRUE(ShapeUtils::areShapesEqual(bShapeInfo, expectedBShape), 0,
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"DYNAMIC_RNN custom operation: wrong shape of biases array, expected is %s, but got %s instead !",
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ShapeUtils::shapeAsString(expectedBShape).c_str(), ShapeUtils::shapeAsString(bShapeInfo).c_str());
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if (h0ShapeInfo) {
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std::vector<LongType> expectedh0Shape = {bS, numUnits};
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REQUIRE_TRUE(
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ShapeUtils::areShapesEqual(h0ShapeInfo, expectedh0Shape), 0,
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"DYNAMIC_RNN custom operation: wrong shape of initial cell output array, expected is %s but got %s instead !",
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ShapeUtils::shapeAsString(expectedh0Shape).c_str(), ShapeUtils::shapeAsString(h0ShapeInfo).c_str());
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}
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if (maxTimeStepShapeInfo) {
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std::vector<LongType> expectedmaxTimeStepShape = {bS};
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REQUIRE_TRUE(ShapeUtils::areShapesEqual(maxTimeStepShapeInfo, expectedmaxTimeStepShape), 0,
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"DYNAMIC_RNN custom operation: wrong shape of maxTimeStep array, expected is %s, but got %s instead !",
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ShapeUtils::shapeAsString(expectedmaxTimeStepShape).c_str(),
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ShapeUtils::shapeAsString(maxTimeStepShapeInfo).c_str());
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}
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// evaluate output shapeInfos
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LongType *hShapeInfo(nullptr), *hPrevShapeInfo(nullptr);
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ALLOCATE(hShapeInfo, block.getWorkspace(), shape::shapeInfoLength(inRank), sd::LongType);
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ALLOCATE(hPrevShapeInfo, block.getWorkspace(), shape::shapeInfoLength(inRank - 1), sd::LongType);
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hShapeInfo[0] = inRank;
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hPrevShapeInfo[0] = inRank - 1;
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hShapeInfo[1] = timeMajor ? time : bS;
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hShapeInfo[2] = timeMajor ? bS : time;
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hPrevShapeInfo[1] = bS;
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hShapeInfo[3] = hPrevShapeInfo[2] = numUnits;
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ShapeUtils::updateStridesAndType(hShapeInfo, WhShapeInfo, shape::order(xShapeInfo));
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ShapeUtils::updateStridesAndType(hPrevShapeInfo, WhShapeInfo, shape::order(xShapeInfo));
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return SHAPELIST(CONSTANT(hShapeInfo), CONSTANT(hPrevShapeInfo));
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}
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} // namespace ops
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} // namespace sd
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#endif
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