Missing einops.layers.....Repeat

I tried to use repeat for in torch and needed a layer, but strangely it was not there. I know, that I could use einops.layers.torch.Reduce('...', reduction='repeat', ...), but that is confusing to read.

What do you think about adding einops.layers.....Repeat functions to einops?

Here is a toy example, where the last line fails because the function counterpart is missing and the first line is difficult to read:

import einops

t = torch.randn((2, 3))
print(einops.layers.torch.Reduce('a b -> a b c', reduction='repeat', c=4)(t).shape)  # torch.Size([2, 3, 4])
print(einops.repeat(t, 'a b -> a b c', c=4).shape)  # torch.Size([2, 3, 4])
print(einops.layers.torch.Repeat('a b -> a b c', reduction='repeat', c=4)(t).shape)  # AttributeError: module 'einops.layers.torch' has no attribute 'Repeat'

1. Try to collect use-cases

Since einops.repeat exists, I think the same use cases would be valid for a layer. I have one case, where I want to use it in pytorch.

2. Implementation. (optional) Implementing a sketch of your proposal in a code allows detecting possible conflicts and realize possible caveats.

Something like the following in each layers backend file

class Repeat(Reduce):
    def __init__(self, pattern, **axes_lengths):
        super().__init__(pattern, 'repeat', **axes_lengths)

3. Integrity - does it interplay well with existing operations and notation in einops?

I would say yes, it is the counterpart of the function einops.repeat.

4. Readability. This is harder to check, but give it a try. A simple but usable test is to write an exercise sheet with several examples of your extension explained, for others meaning of operation should be guessed. Send this test to a couple of your friends to collect the feedback and see how your notion will be understood. This should also help to improve your ideas to make them more digestible.

I think this is obvious, currently I use einops.layers.torch.Reduce('...', reduction='repeat', ...) and that is confusing.