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@jonashaag
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Also optimise Dockerfile for quick rebuilds.

Also add multiple input files support to predict.py.

Is it expected that the estimate for 5 speakers example is 6?

@jonashaag
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Also, what is the purpose of predict_audio.py?

@faroit
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faroit commented Sep 4, 2020

@jonashaag as far as I remember I got 6 with the tf backend and 5 with theano. But I will check later.

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faroit commented Sep 4, 2020

@jonashaag can be removed

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faroit commented Sep 4, 2020

Is it expected that the estimate for 5 speakers example is 6?

i checked again, for both CRNN and RNN i get the correct response (5). So you probably have fallen into the wrong tf backend.

Also optimise Dockerfile for quick rebuilds.

Also add multiple input files support to `predict.py`.
@jonashaag
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OK, changed to Theano backend. I also switched to Conda so that any numeric libraries (such as MKL) are automatically installed

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faroit commented Sep 5, 2020

Okay. Great. I will probably add a simple unit test to make sure that the backends are correct

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2 participants