Adjusted Longrope embedding function to match Huggingface Implementation

[babusid]

This updated implementation of longrope allows for the consideration of long_factors and short_factors, which are scaling dictionaries provided via HF configs for MSFT's Phi3+ models. In the HF canonical implementation of longrope, once the sequence length exceeds a certain pre-configured dimension, you must use a different set of ext_factors than you were previously. This patch enables this by packing both sets of scaling factors into one argument, and selecting which to use dynamically within the returned prim_func.

The HF implementation of this can be found here:
https://github.com/huggingface/transformers/blob/7b325cd573e40bbb12951b8446176c96e8b1afaa/src/transformers/modeling_rope_utils.py#L521

The link above points directly to the switching logic between long and short factors, which has been replicated in this PR.