Activation statistics should only be collected during the training

[madaan]

The activation statistics should only be collected during the training, and not validation. The fix is to check for the flag self.training which is set when model.training() is called.

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[AlisonDavey]

Couldn't we just plot the training part of the statistics, e.g. ax0.plot(ms[:int(x_train.shape[0]/bs)])?

[AlisonDavey]

As in this notebook: https://gist.github.com/AlisonDavey/a9fc0181c988dfd7178fa01264d785f0

[jph00]

Couldn't we just plot the training part of the statistics, e.g. ax0.plot(ms[:int(x_train.shape[0]/bs)])?

That should work too.

[madaan]

Hey @AlisonDavey, while that may work in this case for now, the solution makes an assumption about the order of training and validation data, and thus might not be the best way to go about it.

[AlisonDavey]

I appreciate that we need to understand the order of training and validation data but this is a more robust solution since once we start to use PyTorch hooks we no longer use the class SequentialModel where the update 'self.training' was made.

[madaan]

I appreciate that we need to understand the order of training and validation data but this is a more robust solution since once we start to use PyTorch hooks we no longer use the class SequentialModel where the update 'self.training' was made.

Thanks, fixed here: #80

[jph00]

Note that `self.training` is part of pytorch, and is set by the callback system.