code: def from_cfg(cls, cfg, dtype=None):
      cfg = cls.get_cfg().clone_merge(cfg)
      embed_initializer = mx.init.create(*cfg.INITIALIZER.embed)
      weight_initializer = mx.init.create(*cfg.INITIALIZER.weight)
      bias_initializer = mx.init.create(*cfg.INITIALIZER.bias)
      if dtype is None:
          dtype = cfg.MODEL.dtype
      return cls(
          src_vocab_size=cfg.MODEL.src_vocab_size,
          tgt_vocab_size=cfg.MODEL.tgt_vocab_size,
          max_src_length=cfg.MODEL.max_src_length,
          max_tgt_length=cfg.MODEL.max_tgt_length,
          scale_embed=cfg.MODEL.scale_embed,
          pos_embed_type=cfg.MODEL.pos_embed_type,
          shared_embed=cfg.MODEL.shared_embed,
          tie_weights=cfg.MODEL.tie_weights,
          attention_dropout=cfg.MODEL.attention_dropout,
          activation_dropout=cfg.MODEL.activation_dropout,
          dropout=cfg.MODEL.dropout,
          enc_num_layers=cfg.MODEL.ENCODER.num_layers,
          enc_units=cfg.MODEL.ENCODER.units,
          enc_num_heads=cfg.MODEL.ENCODER.num_heads,
          enc_hidden_size=cfg.MODEL.ENCODER.hidden_size,
          enc_recurrent=cfg.MODEL.ENCODER.recurrent,
          enc_activation=cfg.MODEL.ENCODER.activation,
          enc_pre_norm=cfg.MODEL.ENCODER.pre_norm,
          enc_use_qkv_bias=cfg.MODEL.ENCODER.use_qkv_bias,
          dec_num_layers=cfg.MODEL.DECODER.num_layers,
          dec_units=cfg.MODEL.DECODER.units,
          dec_num_heads=cfg.MODEL.DECODER.num_heads,
          dec_hidden_size=cfg.MODEL.DECODER.hidden_size,
          dec_recurrent=cfg.MODEL.DECODER.recurrent,
          dec_activation=cfg.MODEL.DECODER.activation,
          dec_pre_norm=cfg.MODEL.DECODER.pre_norm,
          dec_use_qkv_bias=cfg.MODEL.DECODER.use_qkv_bias,
          layout=cfg.MODEL.layout,
          embed_initializer=embed_initializer,
          weight_initializer=weight_initializer,
          bias_initializer=bias_initializer,
          dtype=dtype,
      )
  
imports: import numpy
  import mxnet
  from mxnet import np, npx
  from mxnet import use_np
  from mxnet.gluon import nn, HybridBlock
  from typing import Optional, Tuple, List
  from ..utils.registry import Registry
  from ..attention_cell import MultiHeadAttentionCell, gen_self_attn_mask, gen_mem_attn_mask
  from ..layers import PositionalEmbedding, PositionwiseFFN, InitializerType
  from ..utils.config import CfgNode
  from ..sequence_sampler import BaseStepDecoder
label_desc: Use image node_id 9 for calling the TransformerModel obj's underlying member method code with example usage: obj.from_cfg(cls, cfg, dtype) and returns: cls