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/* ******************************************************************************
*
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*
* 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.
*
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* See the NOTICE file distributed with this work for additional
* information regarding copyright ownership .
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* 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 raver119@gmail.com
//
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# include <system/op_boilerplate.h>
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# if NOT_EXCLUDED(OP_dilation2d)
# include <ops/declarable/headers/convo.h>
# include <ops/declarable/helpers/dilation2d.h>
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namespace sd {
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namespace ops {
CUSTOM_OP_IMPL ( dilation2d , 2 , 1 , false , 0 , 1 ) {
auto input = INPUT_VARIABLE ( 0 ) ;
auto weights = INPUT_VARIABLE ( 1 ) ;
auto output = OUTPUT_VARIABLE ( 0 ) ;
REQUIRE_TRUE ( input - > rankOf ( ) = = 4 , 0 , " Dilation2D: input should be 4D " ) ;
REQUIRE_TRUE ( weights - > rankOf ( ) = = 3 , 0 , " Dilation2D: weights should be 3D " ) ;
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const int bS = input - > sizeAt ( 0 ) ;
const int iC = input - > sizeAt ( 3 ) ;
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const bool isSameShape = INT_ARG ( 0 ) = = 1 ;
REQUIRE_TRUE ( input - > sizeAt ( 3 ) = = weights - > sizeAt ( 2 ) , 0 , " Dilation2D: number of input channels doesn't match number of channels in weights: %i vs %i " , input - > sizeAt ( 3 ) , weights - > sizeAt ( 2 ) ) ;
std : : vector < int > strides ( 4 ) ;
std : : vector < int > rates ( 4 ) ;
if ( block . width ( ) > 2 ) {
REQUIRE_TRUE ( block . width ( ) > = 4 , 0 , " Dilation2D: number of input arrays should be 4 at least " ) ;
auto r = INPUT_VARIABLE ( 2 ) ;
auto s = INPUT_VARIABLE ( 3 ) ;
strides = s - > template asVectorT < int > ( ) ;
rates = r - > template asVectorT < int > ( ) ;
} else {
REQUIRE_TRUE ( block . numI ( ) > = 9 , 0 , " Dilation2D: number of Int arguments should be 9 at least " ) ;
int e = 1 ;
for ( int cnt = 0 ; cnt < 4 ; cnt + + )
rates [ cnt ] = INT_ARG ( e + + ) ;
for ( int cnt = 0 ; cnt < 4 ; cnt + + )
strides [ cnt ] = INT_ARG ( e + + ) ;
}
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int sH = 0 , sW = 0 ;
int dH = 0 , dW = 0 ;
int pH = 0 , pW = 0 ;
int oH = 0 , oW = 0 ;
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helpers : : dilation_hw ( block . launchContext ( ) , input - > shapeInfo ( ) , weights - > shapeInfo ( ) , strides , rates , isSameShape , & sH , & sW , & pH , & pW , & dH , & dW , & oH , & oW ) ;
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REQUIRE_TRUE ( oH > 0 & & oW > 0 , 0 , " Dilation2D: outY and outX should have positive values, but got [%i, %i] instead " , oH , oW ) ;
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helpers : : dilation2d ( block . launchContext ( ) , input , weights , output , sH , sW , pH , pW , dH , dW ) ;
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return Status : : OK ( ) ;
}
DECLARE_TYPES ( dilation2d ) {
getOpDescriptor ( )
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- > setAllowedInputTypes ( sd : : DataType : : ANY )
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- > setAllowedOutputTypes ( { ALL_FLOATS } ) ;
}
DECLARE_SHAPE_FN ( dilation2d ) {
auto input = inputShape - > at ( 0 ) ;
auto weights = inputShape - > at ( 1 ) ;
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const int bS = shape : : sizeAt ( input , 0 ) ;
const int iC = shape : : sizeAt ( input , 3 ) ;
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const bool isSameShape = INT_ARG ( 0 ) = = 1 ;
std : : vector < int > strides ( 4 ) ;
std : : vector < int > rates ( 4 ) ;
if ( block . width ( ) > 2 ) {
auto r = INPUT_VARIABLE ( 2 ) ;
auto s = INPUT_VARIABLE ( 3 ) ;
strides = s - > template asVectorT < int > ( ) ;
rates = r - > template asVectorT < int > ( ) ;
} else {
if ( block . numI ( ) < 9 ) {
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auto newShape = ConstantShapeHelper : : getInstance ( ) . scalarShapeInfo ( block . dataType ( ) ) ;
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return SHAPELIST ( newShape ) ;
}
Merge master to upstream (#7945)
* Shugeo strided slice zeros (#14)
* Modified strided_slice op to properly work with empty-like shapes.
* Fixed test for reduce_mean with empty-like input.
* [WIP] Last merge (#15)
* 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
* [WIP] Fixing outstanding issues for NLP (#9)
* Avoid using not-inited objects
* Test fixed.
* Redundant method avoided for models like FastText
* KMeans++ implementation
* KMeans++ implementation
* Disable parallel execution
* KMeans++
* Tests
* Dev branch merge (#16)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Fix some issues on master (#17)
* Fix DataVec test issue
* Fix issue with dl4j SameDiff output layer
* Dtype fix for lambda layers
* #7912 BertIterator dtype fix (use float32 not global default)
* [WIP] Next set of CUDA stuff (#7)
New CUDA implementations and improvements
* bad file
* Dev branch master merge (#23)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* SameDiff ops, TF import and fixes (#24)
* CheckNumerics tests + fixes + misc fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fake quant
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fixes
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* FakeQuantWithMinMaxArgs
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* CheckNumerics fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix libnd4j ALL_INTS and ALL_FLOATS declaration (uint and bfloat types)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Small fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Javadoc
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* Exception tweak
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix for out of scope stack allocated var use
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignores
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Ignore for known failing test (already logged issue)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Merge upstream to fork (#25)
* Add thousand-separator commas to TotalParams (#7915)
* Add thousand-separator commas to TotalParams
The number of parameters can be quite large, and it would help the reading of the summary printout to have the TotalParams column & values at the bottom have thousand-separator-commas in them.
* Add thousand-separator commas to MultiLayerNetwork
Corresponding change to MultiLayerNetwork
Signed-off-by: Jxtps Jxtps <jxtps435@gmail.com>
* Update contributing and issue/PR templates (#7934)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Fix link to AdaDelta paper (#7942)
Fix link to AdaDelta paper hosted on matthewzeiler.com
Signed-off-by: Jxtps
* Fixes, and ignores for known/logged failing issues (#7943)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* SameDiff + DL4J/SameDiff: Multiple fixes (#28)
* #7919 HDF5 attribute buffer length fix
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7909 Arbiter constructor exception ux improvements
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7925 RNN output layer length checks
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Add listener for validating inputs are not incorrectly modified
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* #7939 Integrate NonInplaceValidationListener into tests
* #7844 DL4J SameDiff fixes for variable minibatch size
* DL4J SameDiff fixes - ensure gradient for input placeholder is available
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* Tweaks to ExternalErrorsFunction - use placeholders, make more robust
* Another fix
* More fixes
* More SameDiff/DL4J fixes
* Scope out scalar array creation in BaseScalarOp
* Remove debug code
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] Final dev branch merge (#29)
* SameDiff: convertDataType and gradient check util improvements (#12)
* GradCheck util improvements
* StopGradient constructor + test
* SameDiff: Add datatype conversion
* Javadoc and add DataType.isNumerical()
* Small fix
* Fix SameDiff TF import test cases intermediate naming (workaround for bad default)
* TFGraphTestAllHelper: check intermediates in execution order
* Add missing debug listener
* [WIP] lstmBlock fix + other changes (#13)
- fixes lstmBlock issue
- changes NDArray method reshape(), permute(), transpose() by making them return instance instead of pointer
- CheckNumerics op
- fixes for ReduceBool IsInfOrNan & IsFinite
* Small test fix
* CheckNumerics op wrapper
* Compatibility of deserialization (#18)
Signed-off-by: Alexander Stoyakin <alexander.stoyakin@gmail.com>
* SameDiff: add activation gradient checking support for debugging (#19)
* SameDiff gradient checker: first pass on activation gradient checks
* Fixes + tests for activation gradient checking
* Javadoc
* [WIP] Some nd4j data type corrections (#20)
* Adjust data type
* Set correct Data type.
* Size of proper data type.
* fix averaged cpu load (#22)
* [WIP] Multiple dataset iterators (#27)
* Splitting dataset into arbitrary number
* Fixes
* Multiple split of iterator
* Test
* Test
* Some fixes
* signature change
* one more tweak
Signed-off-by: raver119 <raver119@gmail.com>
* one more test for sequential use of DataSetIteratorSplitter
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* Fixes
* Fixes
* one more test for Alexander
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* Some fixes
* Some fixes
* one more test for Alexander
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* minor test fix
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* Some fixes
* Some fixes
* couple of assertions tweaked
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* MDS splitter test :/
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* Minor refactoring
* Multi dataset
* Some fixes
* More tests
* Small number of test fixes/improvements (failures on CI) (#31)
Signed-off-by: AlexDBlack <blacka101@gmail.com>
* [WIP] More CUDA stuff (#26)
* initial commit
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* LRN BP CUDA
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* less memory
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* Fixed bug with crop_and_resize op helper.
* get rid of unnecessary index-calculation dunction
Signed-off-by: Yurii <yurii@skymind.io>
* Fixed sort with nth_element cuda-based helper.
* Refactored nth_element.
* Refactored nth_element op and tests.
* Modified usage of dim array with sortTad routine.
* Refactored main routine of helper for non_max_image_suppression op.
* non_max_image_suppression op helper with cuda kernel implementation. Initial revision.
* fix vol2col cuda kernel
* meh
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* topK concept
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* unsorted topK with scanWitdh of 1
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* correct vol2col tests
* sorted/unsorted topK
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* implementation and fixing col2im/col2vol
* Corrected usage flags with input/output with reverse op.
* dup is const now
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* percentile op
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* group tests for mapool2d
Signed-off-by: Yurii <yurii@skymind.io>
* special test for george
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* less threads for sortTad
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* provide conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* remove auther in sort tad kernel code
Signed-off-by: Yurii <yurii@skymind.io>
* provide depthwise_conv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* - max_pooling_with_argmax
- null check for special use
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* dts cuda
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* provide sconv2d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* std cuda
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* Refactored non_max_suppression op to conform TF implementation.
* Improved suppression helper.
* provide pooling3d for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* minor lstm rearrangements
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* more of minor lstm rearrangements
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* (bi)dynamic_rnn
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* templates init order
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* Refactored non_max_suppression op.
* Added cuda kernel for non_max_suppression.
* CPU sort by key/value
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* CPU sort TAD by key/value
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* CPU sort TAD by key/value tests
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* Eliminate compiler error with cuda implementation.
* - repaired gradCheck in cuda
- provide conv2d_bp for cuda
Signed-off-by: Yurii <yurii@skymind.io>
* missed signature
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* provide depthwise_conv2d_bp for cuda
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* Implementation of lup helper with cuda kernel. Initial commit.
* further work on backprops for convolutions
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* CUDA linear sort by key/val
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* CUDA tad sort by key/val
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* start providing of backprop for pooling2d/3d
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* Added atomicAdd for bool datatype.
* dynamic partition concept
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* dynamic partition concept
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* dynamic partition scalar CUDA
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* important comment
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* fix pooling2d/3d backprop helpers
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* Added non-linear test with dynamic_partition.
* Improved test for dynamic_partition.
* dynamic_partition TAD concept
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* - dynamic_partition TAD CUDA impl
- dynamic_partition TAD CPU fix
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* - rewrite cpu code for usampling2d/3d
- write cuda code for usampling2d/3d
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* dynamic_stitch CUDA vector case
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* dynamic_stitch CUDA TAD case concept
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* dynamic_stitch CUDA TAD case impl
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* Added tests for dynamic_stitch 3D-4D cases.
* minor tests tweaks
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* Fixed type check for dynamic stitch.
* min/max bp
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* rewrite code for upsampling2d/3d cpu
Signed-off-by: Yurii <yurii@skymind.io>
* reduce min/max/norm_max bp
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* lup implementation. Additional enhancements.
* provide code for upsamling2d/3d backprop
Signed-off-by: Yurii <yurii@skymind.io>
* weightedCrossEntropyWithLogits
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* Fixed template math atomicMul for 64bit ints.
* Refactored dynamic_partition_bp op.
* inverseBroadcast fix
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* DynamicPartitionBP test datatype fixed.
* - nd4j_atomicMul Windows fix
- cpu/NDArrayLambda.hpp excluded from CUDA
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2019-06-27 17:37:04 +02:00
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int e = 1 ;
for ( int cnt = 0 ; cnt < 4 ; cnt + + )
rates [ cnt ] = INT_ARG ( e + + ) ;
for ( int cnt = 0 ; cnt < 4 ; cnt + + )
strides [ cnt ] = INT_ARG ( e + + ) ;
}
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int sH = 0 , sW = 0 ;
int dH = 0 , dW = 0 ;
int pH = 0 , pW = 0 ;
int oH = 0 , oW = 0 ;
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helpers : : dilation_hw ( block . launchContext ( ) , input , weights , strides , rates , isSameShape , & sH , & sW , & pH , & pW , & dH , & dW , & oH , & oW ) ;
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std : : array < Nd4jLong , 4 > shape = { { bS , oH , oW , iC } } ;
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auto newShape = ConstantShapeHelper : : getInstance ( ) . createShapeInfo ( ArrayOptions : : dataType ( weights ) , ' c ' , 4 , shape . data ( ) ) ;
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return SHAPELIST ( newShape ) ;
}
}
}
# endif