sangjaekang

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return NaN values when passing through specific convolution layer

Yes, Of Course. But Still get NaNs. ``` coreml_inputs = {"image":Image.fromarray((img*255).astype(np.uint8))} output = coreml_model.predict(coreml_inputs,useCPUOnly=True)['output'] ```

return NaN values when passing through specific convolution layer

I have found that when I insert a PIL image from another Keras model, the correct result is obtained. But this case return very weird result. Please check the link...

return NaN values when passing through specific convolution layer

The problem I'm referring to is that when encoding the model, there is the problem of spewing NaN with a random probability. The last cell result of the notebook is...

return NaN values when passing through specific convolution layer

Thank you very much for your reply. > I don't see why the model conversion call is within the for loop, nothing changes across iterations. The loop seems to iterate...

return NaN values when passing through specific convolution layer

I've found repeated problems with mobile phone. The same problem occurred when simulated on iphone 6, iOS 11.4.1.

return NaN values when passing through specific convolution layer

When do you think this issue will be update?