* 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
109 lines
3.9 KiB
C++
109 lines
3.9 KiB
C++
/*******************************************************************************
|
|
* 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 01.11.2017.
|
|
//
|
|
|
|
#include <op_boilerplate.h>
|
|
#if NOT_EXCLUDED(OP_stack)
|
|
|
|
#include <ops/declarable/CustomOperations.h>
|
|
#include<ops/declarable/helpers/stack.h>
|
|
|
|
namespace nd4j {
|
|
namespace ops {
|
|
|
|
CUSTOM_OP_IMPL(stack, -1, 1, false, 0, 0) {
|
|
auto input = INPUT_VARIABLE(0);
|
|
auto output = OUTPUT_VARIABLE(0);
|
|
int dim = block.getIArguments()->size() > 0 ? INT_ARG(0) : 0;
|
|
if(dim < 0)
|
|
dim += input->rankOf() + 1;
|
|
|
|
// no-op in case of empty output array
|
|
if (output->isEmpty())
|
|
return Status::OK();
|
|
|
|
// input validation
|
|
// check whether shapes of all input array are the same
|
|
for (int i = 0; i < (int) block.width() - 1; ++i)
|
|
REQUIRE_TRUE(shape::equalsSoft((INPUT_VARIABLE(i))->getShapeInfo(), (INPUT_VARIABLE(i+1))->getShapeInfo()), 0, "STACK op: the shapes of all input arrays must be the same !");
|
|
|
|
REQUIRE_TRUE(dim <= input->rankOf(), 0, "STACK op: the input dimension parameter must be <= rank of input arrays shapes (rank=%i), but got %i instead !", input->shapeOf(), dim);
|
|
|
|
|
|
std::vector<NDArray*> inArrs(block.width());
|
|
for(int i = 0; i < block.width(); ++i)
|
|
inArrs[i] = INPUT_VARIABLE(i);
|
|
|
|
helpers::stack(block.launchContext(), inArrs, output, dim);
|
|
|
|
return Status::OK();
|
|
}
|
|
DECLARE_SYN(pack, stack);
|
|
DECLARE_SYN(Pack, stack);
|
|
|
|
DECLARE_TYPES(stack) {
|
|
//getOpDescriptor()->setSameMode(true);
|
|
getOpDescriptor()
|
|
->setAllowedInputTypes(DataType::ANY)
|
|
->setAllowedOutputTypes(DataType::ANY);
|
|
|
|
}
|
|
|
|
DECLARE_SHAPE_FN(stack) {
|
|
|
|
// check whether input dimension is within rank range
|
|
auto inShapeInfo = inputShape->at(0);
|
|
int rank = shape::rank(inShapeInfo);
|
|
int dim = block.getIArguments()->size() > 0 ? INT_ARG(0) : 0;
|
|
if(dim < 0 )
|
|
dim += rank + 1;
|
|
|
|
REQUIRE_TRUE(dim <= inShapeInfo[0], 0, "STACK op: the input dimension parameter must be <= rank of input arrays shapes (rank=%i), but got %i instead !", inShapeInfo[0], dim);
|
|
|
|
// empty input arrays require some special handling
|
|
if (shape::isEmpty(inShapeInfo)) {
|
|
switch (rank) {
|
|
case 0: {
|
|
// we're going to return rank 1 here
|
|
if (block.width() == 1) {
|
|
return SHAPELIST(ConstantShapeHelper::getInstance()->vectorShapeInfo(0, ArrayOptions::dataType(inShapeInfo)));
|
|
} else {
|
|
return SHAPELIST(ConstantShapeHelper::getInstance()->createShapeInfo(ArrayOptions::dataType(inShapeInfo), 'c', {(Nd4jLong) block.width(), 0}));
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
if(rank == 0) {
|
|
return SHAPELIST(ConstantShapeHelper::getInstance()->vectorShapeInfo(block.width(), ArrayOptions::dataType(inShapeInfo)));
|
|
}
|
|
|
|
//the rank of output ShapeInfo is larger by one compared to input ShapeInfo
|
|
std::vector<Nd4jLong> outShape(inShapeInfo + 1, inShapeInfo + 1 + rank);
|
|
|
|
// insert (int) block.width() at dim position of input shape to get output shape
|
|
outShape.insert(outShape.begin() + Nd4jLong(dim), (Nd4jLong) block.width());
|
|
return SHAPELIST(ConstantShapeHelper::getInstance()->createShapeInfo(ShapeDescriptor(ArrayOptions::dataType(inShapeInfo), shape::order(inShapeInfo), outShape)));
|
|
}
|
|
|
|
|
|
}
|
|
}
|
|
|
|
#endif |