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Exception in thread "main" java.lang.NegativeArraySizeException while invoking totalOutcomes() on RecordReaderDataSetIterator #7140

rahul-raj opened this issue Feb 11, 2019 · 4 comments


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commented Feb 11, 2019

Issue Description

Please describe our issue, along with:
- expected behavior
totalOutcomes() should return the number of labels. In the below dataset:
The first one is output label. So, it is expected to be 7.

- encountered behavior
I'm getting the below exception:

Exception in thread "main" java.lang.NegativeArraySizeException
	at org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.convertWritablesBatched(
	at org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.convertFeaturesOrLabels(
	at org.deeplearning4j.datasets.datavec.RecordReaderMultiDataSetIterator.nextMultiDataSet(
	at org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator.totalOutcomes(

Version Information

Please indicate relevant versions, including, if relevant:

  • Deeplearning4j version -> 1.0.0-beta3
  • platform information (OS, etc) -> Windows 7, 64-bit
  • CUDA version, if used -> NA
  • NVIDIA driver version, if in use -> NA


You can use the below gist as reference to code:

Let me know if further inputs required. Thank you.

Aha! Link:

@AlexDBlack AlexDBlack self-assigned this Feb 11, 2019


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commented Feb 11, 2019

OK, turns out this was a simple one: your data has 7 columns, hence should be indexed 0 to 6 inclusive, but you're indexing 0 to 7 (as if you had 8 total columns).
Runs fine with this:
DataSetIterator dataSetIterator = new RecordReaderDataSetIterator(transformProcessRecordReader,writableConverter,8,1,6,2,-1,true);
Note 6 not 7

As an aside, looks like you've got features and labels reversed... this might be what you want?

        DataSetIterator dataSetIterator = new RecordReaderDataSetIterator.Builder(transformProcessRecordReader, 8)
                .classification(0, 2)   //Column 0, 2 possible classes

(You can also do the same with the constructors instnead of the builder)

Edit: I'll add some better validation so it's more obvious what the problem actually is.


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commented Feb 11, 2019

Thank you very much for the response. The alternate approach that you suggested will suit better in my case. I still got one question.
Are you using the same dataset that I have? For me there are 8 columns in total.
In this case, the index should be still be from 1 till 7 provided index 0 is output label? Trying to understand why it cannot accept index 7 even though there's an 8th column.

I checked the schema transformation process too. Schema had total 8 columns. Then it was passed to transformation process:

                                                .removeColumns("Name","Fare") //remove 2 columns
                                                .categoricalToInteger("Sex") //no change
                                                .categoricalToOneHot("Pclass") //add 3 columns
                                                .removeColumns("Pclass[1]") //remove 1 column

At the end it's still having 8 columns as per my calculation. So I was trying to figure out how the index bound is still rounded to 6 instead of 7.


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commented Feb 11, 2019

@rahul-raj You can check the output of the transformProcessRecordReader by using .next() on it and looking at the size of the returned list. That has 7 elements when I run your code locally.

AlexDBlack added a commit that referenced this issue Feb 12, 2019
[WIP] DL4J/SameDiff Misc (#7145)
* Small SameDiff fix (variable creation)

* #7140 RRDSI better validation for invalid indices

* GELU tests + polishing

* Deconv3d

* Deconv3d fixes, test

* Switch to FB 1.10.0

* Small deconv3d tweaks

* Javadoc

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commented Mar 14, 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.

@lock lock bot locked and limited conversation to collaborators Mar 14, 2019

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