class_docstr: Relative Position Embedding implementation from the T5 paper : https://arxiv.org/abs/1910.10683
code: def _compute_relative_position_bias(self, relative_position_bucket):
      # shape (query_length, key_length, num_heads)
      values = self.relative_position_embedding(
          relative_position_bucket
      )
      # shape (1, num_heads, query_length, key_length)
      values = values.permute([2, 0, 1]).unsqueeze(0)
  
      return values
  
file_path: NeMo/nemo/collections/nlp/modules/common/megatron/position_embedding/t5_relative_position_embedding.py
imports: import math
  import torch
label_desc: Use image node_id 4 for calling the T5RelativePositionEmbedding obj's underlying member method code with example usage: obj._compute_relative_position_bias(relative_position_bucket) and returns: values