code: def from_cfg(
      cls, cfg, use_pooler=True, dtype=None
  ) -> "MobileBertModel":
      cfg = MobileBertModel.get_cfg().clone_merge(cfg)
      assert cfg.VERSION == 1, "Wrong version!"
      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(
          vocab_size=cfg.MODEL.vocab_size,
          units=cfg.MODEL.units,
          hidden_size=cfg.MODEL.hidden_size,
          embed_size=cfg.MODEL.embed_size,
          num_layers=cfg.MODEL.num_layers,
          num_heads=cfg.MODEL.num_heads,
          bottleneck_strategy=cfg.MODEL.bottleneck_strategy,
          inner_size=cfg.MODEL.inner_size,
          num_stacked_ffn=cfg.MODEL.num_stacked_ffn,
          max_length=cfg.MODEL.max_length,
          hidden_dropout_prob=cfg.MODEL.hidden_dropout_prob,
          attention_dropout_prob=cfg.MODEL.attention_dropout_prob,
          num_token_types=cfg.MODEL.num_token_types,
          pos_embed_type=cfg.MODEL.pos_embed_type,
          activation=cfg.MODEL.activation,
          normalization=cfg.MODEL.normalization,
          layer_norm_eps=cfg.MODEL.layer_norm_eps,
          dtype=dtype,
          embed_initializer=embed_initializer,
          weight_initializer=weight_initializer,
          bias_initializer=bias_initializer,
          use_bottleneck=cfg.MODEL.use_bottleneck,
          trigram_embed=cfg.MODEL.trigram_embed,
          use_pooler=use_pooler,
          classifier_activation=cfg.MODEL.classifier_activation,
          layout=cfg.MODEL.layout,
          compute_layout=cfg.MODEL.compute_layout,
      )
  
imports: import os
  from typing import Tuple, Optional
  import mxnet
  from mxnet import use_np, np, npx
  from mxnet.gluon import HybridBlock, nn
  from .base import BACKBONE_REGISTRY
  from ..op import select_vectors_by_position
  from ..base import get_model_zoo_home_dir, get_repo_model_zoo_url, get_model_zoo_checksum_dir
  from ..layers import InitializerType, PositionwiseFFN, PositionalEmbedding, get_norm_layer, get_activation
  from ..initializer import TruncNorm
  from ..utils.config import CfgNode
  from ..utils.misc import load_checksum_stats, download
  from ..utils.registry import Registry
  from ..attention_cell import MultiHeadAttentionCell, gen_self_attn_mask
  from ..data.tokenizers import HuggingFaceWordPieceTokenizer
label_desc: Use image node_id 8 for calling the MobileBertModel obj's underlying member method code with example usage: obj.from_cfg(cls, cfg, use_pooler, dtype) and returns: cls