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DL4J: SimpleRnnParamInitializer does not respect biasInit configuration #6431

Charele opened this issue Sep 12, 2018 · 2 comments · Fixed by #6470


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commented Sep 12, 2018

Let's see the init() method of SimpleRnnParamInitializer:

... ...
INDArray rw = WeightInitUtil.initWeights(nOut, nOut, new long[]{nOut, nOut}, rwInit, rwDist, 'f', m.get(RECURRENT_WEIGHT_KEY));
} else {
m = getSubsets(paramsView, nIn, nOut, true);


    return m;

It initialize the "W" and "RW", forget the init of parameter "b"(will keep default 0)
It's a lost? or bias 0 value is helpful for RNN?

@AlexDBlack AlexDBlack changed the title Init in SimpleRnnParamInitializer DL4J: SimpleRnnParamInitializer does not respect biasInit configuration Sep 13, 2018


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commented Sep 13, 2018

Thanks for reporting. Looks like yes, SimpleRNN does dave a biasInit config option but it doesn't use that in the weight initializer.

@AlexDBlack AlexDBlack self-assigned this Sep 20, 2018

AlexDBlack added a commit that referenced this issue Sep 23, 2018
DL4J/ND4J Misc fixes (#6470)
* #6431 SimpleRNN respect biasInit config value

* #6457 FileSplit android compatibility

* #6451 Improve preconditions class

* Fix pad op mapping

* #6471 Check for OutputLayer as first step in MultiLayerNetwork.computeGradientAndScore()

* Fix Reverse op mapping; map HistogramFixedWidth

* Fix HistogramfixedWidth mapping

* Fix DeConv2DTF op import mapping

* Fix unsorted op mapping

* HistogramFixedWidth fix; map DynamicPartitionBp

* Conv3d and OneHot test fixes

* More test fixes/re-enabling

* Restore ReverseV2 op

* Test tweaks

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commented Oct 24, 2018

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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