code: def forward(self, model_input, attention_mask, tokentype_ids=None):
      # [batch, choices, sequence] --> [batch * choices, sequence] -->
      #    transformer --> [batch, choices] --> softmax
  
      # Ensure the shape is [batch-size, choices, sequence]
      assert len(attention_mask.shape) == 3
      num_choices = attention_mask.shape[1]
  
      # Reshape and treat choice dimension the same as batch.
      attention_mask = attention_mask.view(-1, attention_mask.size(-1))
      extended_attention_mask = bert_extended_attention_mask(
          attention_mask
      )
  
      input_ids = model_input
      # Do the same as attention_mask for input_ids, tokentype_ids
      assert len(input_ids.shape) == 3
      assert len(tokentype_ids.shape) == 3
      input_ids = input_ids.view(-1, input_ids.size(-1))
      tokentype_ids = tokentype_ids.view(-1, tokentype_ids.size(-1))
      position_ids = bert_position_ids(input_ids)
  
      lm_output = self.language_model(
          input_ids,
          position_ids,
          extended_attention_mask,
          tokentype_ids=tokentype_ids,
      )
      if self.post_process:
          _, pooled_output = lm_output
          multichoice_output = self.multichoice_dropout(pooled_output)
          multichoice_logits = self.multichoice_head(multichoice_output)
  
          # Reshape back to separate choices.
          multichoice_logits = multichoice_logits.view(-1, num_choices)
  
          return multichoice_logits
      return lm_output
  
file_path: megatron-lm/megatron/model/multiple_choice.py
imports: import torch
  from megatron import get_args, print_rank_last
  from megatron.model.enums import AttnMaskType
  from megatron.model.bert_model import bert_extended_attention_mask, bert_position_ids
  from megatron.model.language_model import get_language_model
  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 3 for calling the MultipleChoice obj's underlying member method code with example usage: obj.forward(model_input, attention_mask, tokentype_ids) and returns: lm_output, multichoice_logits