code: def __init__(self, config: CPMBeeConfig):
      super().__init__()
  
      self.encoder = Encoder(
          num_layers=config.num_layers,
          dim_model=config.dim_model,
          dim_ff=config.dim_ff,
          num_heads=config.num_heads,
          dim_head=config.dim_head,
          dtype=config.dtype,
          eps=config.eps,
          dropout_p=config.dropout_p,
          mask_modules=config.mask_modules,
      )
  
      self.input_embedding = EmbeddingExt(
          vocab_size=config.vocab_size,
          embedding_size=config.dim_model,
          dtype=config.dtype,
          init_std=0.02,
      )
  
      self.position_bias = BucketPositionBias(
          num_heads=config.num_heads,
          num_buckets=config.position_bias_num_buckets,
          num_segment_bucket=config.position_bias_num_segment_buckets,
          max_distance=config.position_bias_max_distance,
          dtype=config.dtype,
      )
  
file_path: DeepKE/example/llm/CPM-Bee/src/cpm_live/models/bee_torch.py
imports: from typing import Optional, Tuple
  import torch
  from ..native_layers import Encoder, EmbeddingExt, BucketPositionBias
  from .bee import CPMBeeConfig, CPMBeeInferenceState
label_desc: Use image node_id 1 to create a new CPMBeeTorch object from inherited base classes: torch.nn with example: obj = CPMBeeTorch(config)