Add a torch implementation of "convolution reverb"

🚀 The feature

A pure Pytorch implementation of the "convolution reverb" like described in https://pytorch.org/audio/stable/tutorials/audio_data_augmentation_tutorial.html#simulating-room-reverberation

This should be implemented like "pitch shift" both in "functional" and as a module.

Motivation, pitch

torchaudio has been recently ramping up the utilities for data augmentation but so far the convolution reverb hasn't been implemented. Having a pure pytorch implementation would allow to run it efficiently on GPU.

Alternatives

note that sox_effects can be used to provide a "reverb" but it's a CPU only implementation.
Note that sox is not doing a convolution reverb but another algorithm

Additional context

I'm a Meta employee and @roa-beep and @gziz will be working on it throught the MLH fellowship.

Start by reading the existing "pitch shift" functional transform and module, then review the linked torchaudio room-reverberation tutorial. Implement convolution reverb in both forms using pure PyTorch, with GPU execution supported; completion should include the corresponding behavior in the functional API and module.