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

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2019-06-06 14:21:15 +02:00
/*******************************************************************************
* Copyright (c) 2015-2019 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 Alex Black
//
#include <op_boilerplate.h>
#if NOT_EXCLUDED(OP_lstmBlockCell)
#include <ops/declarable/CustomOperations.h>
#include<ops/declarable/helpers/lstmBlock.h>
namespace nd4j {
namespace ops {
//////////////////////////////////////////////////////////////////////////
CUSTOM_OP_IMPL(lstmBlockCell, 8, 7, false, 2, 1) {
//Notation: mostly following https://arxiv.org/pdf/1503.04069.pdf
auto xt = INPUT_VARIABLE(0); // input [bS, inSize] at time t
auto cLast = INPUT_VARIABLE(1); // previous cell state [bS, numUnits], time t-1
auto yLast = INPUT_VARIABLE(2); // previous output [bS, numUnits], time t-1
auto W = INPUT_VARIABLE(3); // Weights - concatenated (input-to-hidden, hidden-to-hidden weights) weights, [(inSize+numUnits), 4*numUnits]
auto Wci = INPUT_VARIABLE(4); // weights - cell peephole (t-1) connections to input modulation gate, [numUnits]
auto Wcf = INPUT_VARIABLE(5); // weights - cell peephole (t-1) connections to forget gate, [numUnits]
auto Wco = INPUT_VARIABLE(6); // weights - cell peephole (t) connections to output gate, [numUnits]
auto b = INPUT_VARIABLE(7); // biases, [4*numUnits]
auto i = OUTPUT_VARIABLE(0); // Output - input modulation gate activations [bS, numUnits]
auto c = OUTPUT_VARIABLE(1); // Activations, cell state (pre tanh) [bs, numUnits]
auto f = OUTPUT_VARIABLE(2); // Output - forget gate activations [bs, numUnits]
auto o = OUTPUT_VARIABLE(3); // Output - output gate activations [bs, numUnits]
auto z = OUTPUT_VARIABLE(4); // Output - input gate activations [bs, numUnits]
auto h = OUTPUT_VARIABLE(5); // Cell state, post tanh [bs, numUnits]
auto y = OUTPUT_VARIABLE(6); // current cell output [bS, numProj], time t
const int peephole = INT_ARG(0); // if 1, provide peephole connections
const double forgetBias = T_ARG(0);
const double clippingCellValue = T_ARG(1); // clipping value for ct, if it is not equal to zero, then cell state is clipped
REQUIRE_TRUE(xt->rankOf()==2 && cLast->rankOf()==2 && yLast->rankOf()==2, 0, "lstmBlockCell: Input ranks must be 2 for inputs 0/1/2 (x, cLast, outLast) - got %i, %i, %i", xt->rankOf(), cLast->rankOf(), yLast->rankOf());
const int rank = xt->rankOf();
const int bS = xt->sizeAt(0);
const int inSize = xt->sizeAt(1);
const int numUnits = cLast->sizeAt(1);
REQUIRE_TRUE(xt->sizeAt(0) == yLast->sizeAt(0) && xt->sizeAt(0) == cLast->sizeAt(0), 0, "lstmBlockCell: Input minibatch sizes (dimension 0) must be same for xt, cLast, yLast");
REQUIRE_TRUE(W->rankOf()==2, 0, "lstmBlockCell: Weights array rank must be 2");
REQUIRE_TRUE(W->sizeAt(0)==(inSize+numUnits), 0, "lstmBlockCell: Weights size(0) must be equal to inSize + numUnits, got %i", W->sizeAt(0));
REQUIRE_TRUE(W->sizeAt(1)==(4*numUnits), 0, "lstmBlockCell: Weights size(1) must be equal to 4*numUnits, got %i", W->sizeAt(1));
REQUIRE_TRUE(b->rankOf()==1 && b->sizeAt(0)==(4*numUnits), 0, "lstmBlockCell: Biases must be rank 1, size 4*numUnits");
REQUIRE_TRUE(i->rankOf()==2 && c->rankOf()==2 && f->rankOf()==2 && o->rankOf()==2 && z->rankOf()==2 && h->rankOf()==2 && y->rankOf()==2 &&
i->sizeAt(0)==bS && c->sizeAt(0)==bS && f->sizeAt(0)==bS && o->sizeAt(0)==bS && z->sizeAt(0)==bS && h->sizeAt(0)==bS && y->sizeAt(0)==bS &&
i->sizeAt(1)==numUnits && c->sizeAt(1)==numUnits && f->sizeAt(1)==numUnits && o->sizeAt(1)==numUnits && z->sizeAt(1)==numUnits && h->sizeAt(1)==numUnits && y->sizeAt(1)==numUnits,
0, "lstmBlockCell: Output arrays must all be rank 2 with size(0) == batchSize and size(1) == numUnits");
// calculations
helpers::lstmBlockCell(xt, cLast, yLast, W, Wci, Wcf, Wco, b, i, c, f, o, z, h, y, {(double)peephole, forgetBias, clippingCellValue});
return Status::OK();
}
DECLARE_TYPES(lstmBlockCell) {
getOpDescriptor()
->setAllowedInputTypes(nd4j::DataType::ANY)
->setAllowedOutputTypes({ALL_FLOATS});
}
DECLARE_SHAPE_FN(lstmBlockCell) {
auto xt = inputShape->at(0); // input [bS, inSize] at time t
auto cLast = inputShape->at(1); // previous cell state [bS, numUnits], time t-1
auto yLast = inputShape->at(2); // previous output [bS, numUnits], time t-1
auto W = inputShape->at(3); // Weights - concatenated (input-to-hidden, hidden-to-hidden weights) weights, [(inSize+numUnits), 4*numUnits]
auto Wci = inputShape->at(4); // weights - cell peephole (t-1) connections to input modulation gate, [numUnits]
auto Wcf = inputShape->at(5); // weights - cell peephole (t-1) connections to forget gate, [numUnits]
auto Wco = inputShape->at(6); // weights - cell peephole (t) connections to output gate, [numUnits]
auto b = inputShape->at(7); // biases, [4*numUnits]
REQUIRE_TRUE(shape::rank(xt)==2 && shape::rank(cLast)==2 && shape::rank(yLast)==2, 0, "lstmBlockCell: Input ranks must be 2 for inputs 0/1/2 (x, cLast, outLast) - got %i, %i, %i", shape::rank(xt), shape::rank(cLast), shape::rank(yLast));
const int inSize = xt[2];
const int numUnits = cLast[2]; //[rank, bS, nOut, ...]
REQUIRE_TRUE(xt[1] == yLast[1] && xt[1] == cLast[1], 0, "lstmBlockCell: Input minibatch sizes (dimension 0) must be same for xt, cLast, yLast");
REQUIRE_TRUE(shape::rank(W)==2, 0, "lstmBlockCell: Weights array rank must be rank 2, got %i", shape::rank(W));
REQUIRE_TRUE(W[1]==(inSize+numUnits), 0, "lstmBlockCell: Weights size(0) must be equal to inSize + numUnits, got %i", W[1]);
REQUIRE_TRUE(W[2]==(4*numUnits), 0, "lstmBlockCell: Weights size(1) must be equal to 4*numUnits, got %i", W[2]);
REQUIRE_TRUE(shape::rank(b)==1 && b[1]==(4*numUnits), 0, "lstmBlockCell: Biases must be rank 1, size 4*numUnits");
// evaluate output shapeInfos
const int bS = xt[1];
Nd4jLong *s(nullptr);
ALLOCATE(s, block.getWorkspace(), shape::shapeInfoLength(2), Nd4jLong); // [bS, numUnits]
s[0] = 2;
s[1] = bS;
s[2] = numUnits;
ShapeUtils::updateStridesAndType(s, xt, 'c');
Dev branch merge: dev_20190606 (#7904) * correct logsoftmax looss (#2) * Small SameDiff listener fix (#4) * Various fixes (#6) * #7839 Fix for asXMatrix and tests * #7866 EmbeddingSequenceLayer dtype fix + test * #7856 SameDiff save/load stream methods * #7859 RegressionEvaluation rank 4 fix + tests + axis configuration * EvaluationBinary 3d/4d * More evaluation 3d/4d tests * #7847 Evaluation empty checks * Small test ifx * #7848 Fix median edge case * Improve DL4J samediff layer tests * [WIP] FastText wrapper implemented (#8) * FastText implemented * Some fixes * Fix shapes for wordsNearest * Validation of input vectors * Fixes * Fixed test * Thread tagged * Some tweaks * setContextClassLoader for DeallocatorServiceThread * Numpy format tests (#1) * Various fixes (#11) * #7852 SameDiff gather fix * #7892 SameDiff placeholder to constant conversion * #7890 validate input rank for MLN/CG init methods * Fix broken permute shape calculation * Permute and gather fixes * Tests * #7850 LogSumExp fix + test * Handful of test fixes * Empty arrays with non-scalar shapes (#10) * minor rearrangements for lambdas * empty tensors with non-scalar shapes * numpy empty tensors with non-scalar shapes * few more empty tweaks * Small fixes * conv3d signature update * micro fix in batchnorm mkldnn * Import fixes * Fix * MKL-DNN update * Small fill fix * fill with empty input + test * Fixes * Small error improvement * Fix * one special test * couple of fixes for lstm * Rewrite TFGraphMapper.getNDArrayFromTensor to be maintainable and less error prone * Fixes * FP16 * Unsigned * BFloat16 * Fill op - empty tweaks * - couple of fixes for empty arrays construction - stack updated * strided slice fix * one transform test * provide method for reducing shapeInfo in case of input array is empty * Fixed reduceAlongDimensions to use empty input properly. * couple of broadcast tests * couple of tests broadcast tests + tweak to make them pass * add check of non-empty to methods producing sub-arrays * Fixed reshapeC with zeros in shape. * complete empty check in reduce_... legacy ops * Concat and cumsum/prod * Tweak to empty shape inference on import * add empty check to the rest of reduce legacy ops * one more test * correct typo in evalReduceShapeInfoEmpty * Added tests for reduce_* ops to tests with zero shapes. * few more tests for empty reductions * Fixed strided_slice op with empty case and tests. * one more empty reduction test * Fixed strided_slice test. * add empty check to NDArray::reshapei * infOrMax * empty min/max with infinity tests * made unstack working correctly with empty arrays * few IndexReduce tests + tweaks for empty shapes * add test for empty concat * few tests fixed * Validation fix for reductions on empty shapes * Reverse fix * Reduction shape calc fixes * SameDiff.generateOutputVariable: don't use shape function to determine number of outputs * Range fix * - NDArray constructor updated for scalars/empty arrays - few tests fixed * More fixes * Empty creator fixes * concat fix * concat fix * TF import tests: allow 'both all NaN' and 'both all inf' to pass * Slice, zero fraction, and reshape fixes * transpose, gather * Zero fraction * scalar cast fix * Empty reduction axis support * few more tests fixed * Fixed input checks conforming with TF for concat op and tests. * few tests fixed * matmul scalar shape fix * Fixed checkout for data type and scalarity with concat to allow non-empty scalars with vector concats. * broadcast bool fix * few more tests * few more tests * correct evalReduceShapeInfoEmpty * argmax/argmin + tests * one more empty edge case + one more test * argmax/argmin/realdiv_bp tweaks * empty reshape test + fix * Helper fixes * Small fixes * Gather test fix * Gather test fix * Small fixes * reduce scalar zero values * scalar mean workaround * Remove debug code * along dim mean workaround * one more test * - equalsTo() tweak for empty arrays - one more test * broadcast tweaks
2019-06-15 13:34:34 +02:00
Nd4jLong *s1 = CONSTANT(s);
2019-06-06 14:21:15 +02:00
//7 outputs, all same shape: z, i, f, o, h, c, y
Dev branch merge: dev_20190606 (#7904) * correct logsoftmax looss (#2) * Small SameDiff listener fix (#4) * Various fixes (#6) * #7839 Fix for asXMatrix and tests * #7866 EmbeddingSequenceLayer dtype fix + test * #7856 SameDiff save/load stream methods * #7859 RegressionEvaluation rank 4 fix + tests + axis configuration * EvaluationBinary 3d/4d * More evaluation 3d/4d tests * #7847 Evaluation empty checks * Small test ifx * #7848 Fix median edge case * Improve DL4J samediff layer tests * [WIP] FastText wrapper implemented (#8) * FastText implemented * Some fixes * Fix shapes for wordsNearest * Validation of input vectors * Fixes * Fixed test * Thread tagged * Some tweaks * setContextClassLoader for DeallocatorServiceThread * Numpy format tests (#1) * Various fixes (#11) * #7852 SameDiff gather fix * #7892 SameDiff placeholder to constant conversion * #7890 validate input rank for MLN/CG init methods * Fix broken permute shape calculation * Permute and gather fixes * Tests * #7850 LogSumExp fix + test * Handful of test fixes * Empty arrays with non-scalar shapes (#10) * minor rearrangements for lambdas * empty tensors with non-scalar shapes * numpy empty tensors with non-scalar shapes * few more empty tweaks * Small fixes * conv3d signature update * micro fix in batchnorm mkldnn * Import fixes * Fix * MKL-DNN update * Small fill fix * fill with empty input + test * Fixes * Small error improvement * Fix * one special test * couple of fixes for lstm * Rewrite TFGraphMapper.getNDArrayFromTensor to be maintainable and less error prone * Fixes * FP16 * Unsigned * BFloat16 * Fill op - empty tweaks * - couple of fixes for empty arrays construction - stack updated * strided slice fix * one transform test * provide method for reducing shapeInfo in case of input array is empty * Fixed reduceAlongDimensions to use empty input properly. * couple of broadcast tests * couple of tests broadcast tests + tweak to make them pass * add check of non-empty to methods producing sub-arrays * Fixed reshapeC with zeros in shape. * complete empty check in reduce_... legacy ops * Concat and cumsum/prod * Tweak to empty shape inference on import * add empty check to the rest of reduce legacy ops * one more test * correct typo in evalReduceShapeInfoEmpty * Added tests for reduce_* ops to tests with zero shapes. * few more tests for empty reductions * Fixed strided_slice op with empty case and tests. * one more empty reduction test * Fixed strided_slice test. * add empty check to NDArray::reshapei * infOrMax * empty min/max with infinity tests * made unstack working correctly with empty arrays * few IndexReduce tests + tweaks for empty shapes * add test for empty concat * few tests fixed * Validation fix for reductions on empty shapes * Reverse fix * Reduction shape calc fixes * SameDiff.generateOutputVariable: don't use shape function to determine number of outputs * Range fix * - NDArray constructor updated for scalars/empty arrays - few tests fixed * More fixes * Empty creator fixes * concat fix * concat fix * TF import tests: allow 'both all NaN' and 'both all inf' to pass * Slice, zero fraction, and reshape fixes * transpose, gather * Zero fraction * scalar cast fix * Empty reduction axis support * few more tests fixed * Fixed input checks conforming with TF for concat op and tests. * few tests fixed * matmul scalar shape fix * Fixed checkout for data type and scalarity with concat to allow non-empty scalars with vector concats. * broadcast bool fix * few more tests * few more tests * correct evalReduceShapeInfoEmpty * argmax/argmin + tests * one more empty edge case + one more test * argmax/argmin/realdiv_bp tweaks * empty reshape test + fix * Helper fixes * Small fixes * Gather test fix * Gather test fix * Small fixes * reduce scalar zero values * scalar mean workaround * Remove debug code * along dim mean workaround * one more test * - equalsTo() tweak for empty arrays - one more test * broadcast tweaks
2019-06-15 13:34:34 +02:00
return SHAPELIST(s1, s1, s1, s1, s1, s1, s1);
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}
}
}
#endif