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DL4J: MultiLayerNetwork.output(DataSetIterator,boolean) can fail for variable length RNN data #7352

AlexDBlack opened this issue Mar 26, 2019 · 1 comment · Fixed by #7340


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commented Mar 26, 2019

For variable length time series, we can't just use concat, as the array lengths won't match - we need to pad.
However, if we introduce padding in this method, we have no way of returning the mask array also - i.e., the user has no way (other than looking for all 0s) to work out what data is real vs. padded.

At the very least, we should check this and throw a useful exception; perhaps a better solution would be to return either a mask array or the sequence lengths somehow.

@AlexDBlack AlexDBlack self-assigned this Mar 27, 2019

AlexDBlack added a commit that referenced this issue Mar 27, 2019
AlexDBlack added a commit that referenced this issue Mar 28, 2019
[WIP] Misc DL4J/ND4J/DataVec Issues (#7340)
* Add FirstDigitTransform (Benfords law) + tests

* Javadoc, polish

* #7325 Fix SameDiff.asFlatPrint

* Refactor DataVec readers to remove hard-coded use of Files, in favor of streams

* Add StreamInputSplit (partly complete)

* More tests, fixes

* Fixes for model import test failures

* DataVec fixes after earlier changes

* Another DataVec fix

* #7355 SameDiff array reuse fix

* #7343 SameDiff method for Pad op

* #7305 Fix getColumn on row vector (returning scalar, not view)

* #7168 Empty arrays - create only once

* #7002 Remove newFormat arg/field

* #7352 MultiLayerNetwork.output(DataSetIterator) validation

* Fixes

* Small fixes

* SameDiff variables: Switch to LinkedHashMap for consitent iteration order

* Fix validation NPE for LogFileWriter

* Reduce3 fixes

* Small test fix

* Small test fix

* Fix bad test

* Small test threshold tweak

* OpProfiler fix: null x array (random ops etc)

* Fix issue with array order not matching flattening order when Nd4j.ordering() == f - Nd4j.createFromArray

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commented Apr 27, 2019

This thread has been automatically locked since there has not been any recent activity after it was closed. Please open a new issue for related bugs.

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