[BUG] [DOCS] VitTransformerBlock examples have einops error

[evelynmitchell]

---------------------------------------------------------------------------
EinopsError                               Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/einops/einops.py](https://localhost:8080/#) in reduce(tensor, pattern, reduction, **axes_lengths)
    521         shape = backend.shape(tensor)
--> 522         recipe = _prepare_transformation_recipe(pattern, reduction, axes_names=tuple(axes_lengths), ndim=len(shape))
    523         return _apply_recipe(

10 frames
EinopsError: Wrong shape: expected 4 dims. Received 3-dim tensor.

During handling of the above exception, another exception occurred:

EinopsError                               Traceback (most recent call last)
[/usr/local/lib/python3.10/dist-packages/einops/einops.py](https://localhost:8080/#) in reduce(tensor, pattern, reduction, **axes_lengths)
    531             message += "\n Input is list. "
    532         message += "Additional info: {}.".format(axes_lengths)
--> 533         raise EinopsError(message + "\n {}".format(e))
    534 
    535

EinopsError:  Error while processing rearrange-reduction pattern "b p n (h d) -> b h p n d".
 Input tensor shape: torch.Size([5, 4, 512]). Additional info: {'h': 8}.
 Wrong shape: expected 4 dims. Received 3-dim tensor.

I'm going to try to figure out what the correct input shape is.

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[Kye Gomez]

It says it expects 4 dimensions

[evelynmitchell]

Docs PR incoming to fix