ImageDataGenerators ``standardize`` modifies input about keras-preprocessing HOT 7 CLOSED

Maybe the parameter should work the other way round, because actually your PR is a breaking change, if someone relies on the fact that the input variable is indeed standardized. I assume this is a very edgy case, however, I can think of it.

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It is as designed, mostly to reuse memory when possible. When using jupyter, I would suggest providing a copy of the input instead.

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In this case I agree with @alxy. This is a bad practice and should be avoided, as it is an unexpected behavior that faces the user and can have unexpected consequences down the pipeline, which normally turns out to be a nightmare to debug. Since Keras puts the user first this should be avoided on any function facing the user directly. The behavior of course reduces the memory footprint and can bring benefits, but it should only be used on internal logic not on top-level user facing functions.

That's why for example we do this: https://github.com/keras-team/keras-preprocessing/blob/master/keras_preprocessing/image/dataframe_iterator.py#L106 even though this holds two copies of the dataframe at some point in time, but the user is first so we do it.

@Dref360 I made a PR #138 to address this issue. If there are more places where this happens it should be addressed as well.

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Modify in place wouldn't be bad if you wouldn't return a value.

If the user wishes to save memory, passing an extra param (in_place for example) is better suited.

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@Dref360 should we merge the related PR and close this issue? then we can discuss the introduction of an inplace argument or so. I need a review on the PR though before I can merge.

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Good point, specially because it is used internally by the ImageDataGenerator in this way. I'll update the PR, thanks for the feedback.

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I believe this can be closed.

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