This shows a trainable parameter in the full data frame and trainable vs non-trainable params in the summary. This should be like keras [example](https://github.com/keras-team/keras/pull/11795#issue-235955201).
I also changed the pandas display so that instead of putting (M) or (K) manually in the label, pandas appends it to the number automatically.
Is this the right approach?, perhaps it would be better to show trainable vs nontrainable parameters. Or sill use nontrainable parameters to estimate macs
I thought perhaps we could add an example of the outputs on a large model. I noticed that some of these summary packages break down in the presence of large models, even though these are the ones you most need to summarise.
Mike Clark