code: def cfg():
      cfg = {
          "max_seq_len": 8,
          "num_attention_heads": 2,
          "layer_type": LayerType.encoder,
          "hidden_size": 4,
          "rpe_init_method_std": 0.02,
          "rpe_num_buckets": 6,
          "rpe_max_distance": 16,
      }
      return cfg
  
file_path: NeMo/tests/collections/nlp/test_position_embedding.py
imports: import random
  import pytest
  import torch
  from nemo.collections.nlp.modules.common.megatron.layer_type import LayerType
  from nemo.collections.nlp.modules.common.megatron.position_embedding import ALiBiRelativePositionEmbedding, KERPLERelativePositionEmbedding, RotaryEmbedding, SandwichRelativePositionEmbedding, T5RelativePositionEmbedding, XPOSPositionEmbedding
  from nemo.collections.nlp.modules.common.megatron.position_embedding.rotary_position_embedding import apply_rotary_pos_emb
  from nemo.collections.nlp.modules.common.megatron.utils import init_method_normal
label_desc: Use image node_id 1 for calling a global function with example usage: cfg() and returns: cfg