class_docstr: BERT-based encoder for queries or blocks used for learned information retrieval.
class_docstr_tok: ["BERT-based","encoder","for","queries","or","blocks","used","for","learned","information","retrieval","."]
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
      )
      self.ict_head.load_state_dict(
          state_dict[self._ict_head_key], strict=strict
      )
  
imports: import os
  import torch
  from megatron import get_args, print_rank_0
  from megatron.checkpointing import get_checkpoint_tracker_filename, get_checkpoint_name
  from megatron.model import BertModel
  from .module import MegatronModule
  from megatron.core import mpu
  from megatron.model.enums import AttnMaskType
  from megatron.model.utils import get_linear_layer
  from megatron.model.utils import init_method_normal
  from megatron.model.language_model import get_language_model
  from megatron.model.utils import scaled_init_method_normal
  from megatron.model.bert_model import bert_extended_attention_mask, bert_position_ids
label_desc: Use image node_id 4 for calling the IREncoderBertModel obj's underlying member method code with example usage: obj.load_state_dict(state_dict, strict) without return types