[ao][sparsity] Basic implementation of activation sparsifier (#80886)
The Activation sparsifier class aims to sparsify/prune activations in a neural
network. The idea is to attach the sparsifier to a layer (or layers) and it
zeroes out the activations based on the mask_fn (or sparsification function)
input by the user.
The mask_fn is applied once all the inputs are aggregated and reduced i.e.
mask = mask_fn(reduce_fn(aggregate_fn(activations)))
Note::
The sparsification mask is computed on the input **before it goes through the attached layer**.
Test Plan:
```python test/test_ao_sparsity.py TestActivationSparsifier```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80886
Approved by: https://github.com/HDCharles
