This should probably be considered deprecated in favour of explicit
specification via iterator() calls.


On Fri, Apr 18, 2014 at 1:48 PM, Xavier Bouthillier <
notifications@github.com> wrote:

> In pylearn2/datasets/sparse_dataset.py:
>
> > +
> > +        convert = []
> > +        for sp, src in safe_zip(sub_spaces, sub_sources):
> > +            if src == 'features' and \
> > +               getattr(self, 'view_converter', None) is not None:
> > +                conv_fn = (lambda batch, self=self, space=sp:
> > +                           self.view_converter.get_formatted_batch(batch,
> > +                                                                   space))
> > +            else:
> > +                conv_fn = None
> > +
> > +            convert.append(conv_fn)
> > +
> > +        # TODO: Refactor
> > +        if mode is None:
> > +            if hasattr(self, '_iter_subset_class'):
>
> Do you know where we can possibly set those attributes
> (_iter_subset_class, _iter_batch_size and _iter_numbatches)? I see the same
> code in DenseDesignMatrix but I do not see them assigned anywhere.
>
> —
> Reply to this email directly or view it on GitHub<https://github.com/lisa-lab/pylearn2/pull/796/files#r11780266>
> .
>