code: def date_gen_for_double_heads():
      num_choices = 2
      batch_size = 2
      input_ids = torch.tensor(
          [
              [15496, 11, 616, 3290, 318, 13779, 318, 13779],
              [15496, 11, 616, 3290, 318, 13779, 318, 13779],
          ],
          dtype=torch.int64,
      )
      attention_mask = torch.tensor(
          [[1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1]],
          dtype=torch.int64,
      )
      mc_labels = torch.zeros(input_ids.shape[0], dtype=torch.int64)
  
      mc_token_ids = torch.arange(0, num_choices, dtype=torch.int64)
      mc_token_ids = mc_token_ids.expand((batch_size, num_choices))
      multiple_choice_inputs_ids = (
          input_ids.unsqueeze(1)
          .expand(-1, num_choices, -1)
          .contiguous()
      )
      multiple_choice_input_mask = (
          attention_mask.unsqueeze(1)
          .expand(-1, num_choices, -1)
          .contiguous()
      )
  
      inputs = {
          "input_ids": multiple_choice_inputs_ids,
          "mc_token_ids": mc_token_ids,
          "attention_mask": multiple_choice_input_mask,
          "labels": multiple_choice_inputs_ids,
          "mc_labels": mc_labels,
      }
      return inputs
  
file_path: colossalai/tests/kit/model_zoo/transformers/gpt.py
imports: import copy
  import torch
  import transformers
  from ..registry import ModelAttribute, model_zoo
label_desc: Use image node_id 6 for calling a global function with example usage: date_gen_for_double_heads() and returns: inputs