code: def from_cfg(cls, cfg, dtype=None):
      if dtype is not None:
          new_cfg = cfg.clone()
          new_cfg.defrost()
          new_cfg.MODEL.dtype = dtype
          return cls(cfg=new_cfg)
      else:
          return cls(cfg=cfg)
  
imports: import numpy
  import mxnet
  from mxnet import use_np, np, npx
  from mxnet.gluon import nn, Block, HybridBlock, Parameter
  from ..attention_cell import multi_head_dot_attn, gen_self_attn_mask, gen_mem_attn_mask, RelAttentionScoreCell, MultiHeadAttentionCell
  from ..layers import get_activation, PositionalEmbedding, PositionwiseFFN, AdaptiveEmbedding, ProjectedAdaptiveLogSoftmaxWithLoss
  from ..utils.config import CfgNode
  from ..sequence_sampler import BaseStepDecoder
label_desc: Use image node_id 5 for calling the TransformerXLForLM obj's underlying member method code with example usage: obj.from_cfg(cls, cfg, dtype) and returns: cls, cls