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Update torchvision_tutorial.rst
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intermediate_source/torchvision_tutorial.rst

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@@ -59,7 +59,7 @@ training and evaluation, and will use the evaluation scripts from
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One note on the ``labels``. The model considers class ``0`` as background. If your dataset does not contain the background class, you should not have ``0`` in your ``labels``. For example, assuming you have just two classes, *cat* and *dog*, you can define ``1`` (not ``0``) to represent *cats* and ``2`` to represent *dogs*. So, for instance, if one of the images has both classes, your ``labels`` tensor should look like ``[1,2]``.
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Additionally, if you want to use aspect ratio grouping during training
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(so that each batch only contains images with similar aspect ratio),
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(so that each batch only contains images with similar aspect ratios),
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then it is recommended to also implement a ``get_height_and_width``
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method, which returns the height and the width of the image. If this
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method is not provided, we query all elements of the dataset via

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