class_docstr: Bert Language model.
class_docstr_tok: ["Bert","Language","model","."]
docstr: Customized load.
docstr_tok: ["Customized","load","."]
code: def load_state_dict(self, state_dict, strict=True):
      """Customized load."""
  
      self.language_model.load_state_dict(
          state_dict[self._language_model_key], strict=strict
      )
      if self.post_process:
          self.lm_head.load_state_dict(
              state_dict[self._lm_head_key], strict=strict
          )
      if self.post_process and self.add_binary_head:
          self.binary_head.load_state_dict(
              state_dict[self._binary_head_key], strict=strict
          )
      # Load word_embeddings.
      if self.post_process and not self.pre_process:
          self.word_embeddings.load_state_dict(
              state_dict[self._word_embeddings_for_head_key],
              strict=strict,
          )
  
imports: import torch
  from megatron import get_args
  from megatron.core import tensor_parallel
  from megatron.model.enums import AttnMaskType
  from megatron.model.language_model import parallel_lm_logits
  from megatron.model.language_model import get_language_model
  from megatron.model.utils import get_norm
  from megatron.model.utils import openai_gelu, erf_gelu
  from megatron.model.utils import get_linear_layer
  from megatron.model.utils import init_method_normal
  from megatron.model.utils import scaled_init_method_normal
  from .module import MegatronModule
label_desc: Use image node_id 5 for calling the BertModel obj's underlying member method code with example usage: obj.load_state_dict(state_dict, strict) without return types