Alex Black 68ea5f3688
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 21:34:34 +10:00

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
******************************************************************************/
//
// Created by raver119 on 29/10/17.
//
#include <op_boilerplate.h>
#if NOT_EXCLUDED(OP_permute)
#include <ops/declarable/CustomOperations.h>
#include <helpers/ShapeUtils.h>
namespace nd4j {
namespace ops {
//////////////////////////////////////////////////////////////////////////
// here iArgs is int vector of ordered set of dimensions to be permuted
CUSTOM_OP_IMPL(permute, 1, 1, true, 0, -2) {
auto x = INPUT_VARIABLE(0);
bool replace = false;
auto origArgs = block.width() > 1 ? INPUT_VARIABLE(1)->asVectorT<int>() : *block.getIArguments();
std::vector<int> arguments({});
if(origArgs.size() > 0){
for (int e = 0; e < origArgs.size(); e++) {
int ax = origArgs[e];
if (ax < 0)
ax += x->rankOf();
arguments.emplace_back(ax);
}
replace = true;
} else {
for (int e = x->rankOf() - 1; e >= 0; e--)
arguments.emplace_back(e);
}
// 0D edge case
if (x->rankOf() == 0) {
REQUIRE_TRUE(arguments.size() == 1, 0, "Permute: only one axis is allowed for scalar");
auto output = OUTPUT_VARIABLE(0);
if (!block.isInplace())
output->assign(x);
return Status::OK();
}
if(block.isInplace()) { // in-place
x->permutei(arguments);
STORE_RESULT(x);
} else {
auto output = OUTPUT_VARIABLE(0);
auto result = x->permute(arguments);
output->assign(result);
STORE_RESULT(output);
delete result;
}
return Status::OK();
}
DECLARE_TYPES(permute) {
getOpDescriptor()
->setAllowedInputTypes(0, nd4j::DataType::ANY)
->setAllowedInputTypes(1, {ALL_INTS})
->setSameMode(true);
}
DECLARE_SHAPE_FN(permute) {
auto shapeList = SHAPELIST();
auto arguments = block.width() > 1 ? INPUT_VARIABLE(1)->asVectorT<int>() : *block.getIArguments();
if (shape::rank(inputShape->at(0)) == 0) {
shapeList->push_back(ConstantShapeHelper::getInstance()->scalarShapeInfo(ArrayOptions::dataType(inputShape->at(0))));
} else if (inputShape->size() == 1 && !arguments.empty()) {
shapeList->push_back(ShapeUtils::evalPermShapeInfo(arguments.data(), arguments.size(), *INPUT_VARIABLE(0), block.workspace()));
} else {
if(arguments.size() == 0){
//Reverse dimensions
int rank = shape::rank(inputShape->at(0));
for (int e = rank - 1; e >= 0; e--)
arguments.emplace_back(e);
}
shapeList->push_back(ShapeUtils::evalPermShapeInfo(arguments.data(), arguments.size(), *INPUT_VARIABLE(0), block.workspace()));
}
return shapeList;
}
}
}
#endif