Implements Hitrate metric as proposed in #2631

Description:
Implements hitrate metric for recommendation systems. The hitrate is calculated for the top-k list provided by the user and returns a list of hitrate in sorted order. A "hit" is considered when atleast one of our model's top-k predictions for recommedations is actually correct.
Test cases and docstrings are also implemented.

I followed the code structure of other metrics like loss, KL divergence, etc.

Reference : https://github.com/catalyst-team/catalyst/blob/master/catalyst/metrics/functional/_hitrate.py
Also i used Gemini initially for understanding how recommendation systems and its evaluation/metrics work, and for understanding disrtibuted tests.

Check list:

• New tests are added (if a new feature is added)
• New doc strings: description and/or example code are in RST format
• Documentation is updated (if required)