code: def get_gpt2_components(model_type: str, batch_size: int):
      vocab_size = 1024
      seq_len = 8
  
      def gpt2_model_builder():
          if model_type == "gpt2_medium":
              return GPTLMModel(
                  hidden_size=1024,
                  num_layers=24,
                  num_attention_heads=16,
              )
          elif model_type == "gpt2_xl":
              return GPTLMModel(
                  hidden_size=1600,
                  num_layers=48,
                  num_attention_heads=32,
              )
          elif model_type == "gpt2_10b":
              return GPTLMModel(
                  hidden_size=4096,
                  num_layers=50,
                  num_attention_heads=16,
              )
          elif model_type == "gpt2_14b":
              return GPTLMModel(
                  hidden_size=4096,
                  num_layers=70,
                  num_attention_heads=16,
              )
          elif model_type == "gpt2_20b":
              return GPTLMModel(
                  hidden_size=8192,
                  num_layers=25,
                  num_attention_heads=16,
              )
          elif model_type == "gpt2_24b":
              return GPTLMModel(
                  hidden_size=8192,
                  num_layers=30,
                  num_attention_heads=16,
              )
          else:
              raise TypeError(f"model_builder {model_type}")
  
      def gpt2_data_gen(device="cuda"):
          input_ids = torch.randint(
              0, vocab_size, (batch_size, seq_len), device=device
          )
          attention_mask = torch.ones_like(input_ids, device=device)
          kwargs = dict(
              input_ids=input_ids, attention_mask=attention_mask
          )
          return kwargs
  
      return gpt2_model_builder, gpt2_data_gen
  
file_path: ColossalAI/examples/language/gpt/experiments/auto_offload/model_zoo.py
imports: import torch
  import torch.nn
  from transformers import GPT2Config, GPT2LMHeadModel
label_desc: Use image node_id 1 for calling a global function with example usage: get_gpt2_components(model_type, batch_size) and returns: gpt2_model_builder,  gpt2_data_gen, kwargs, GPTLMModel, GPTLMModel, GPTLMModel, GPTLMModel, GPTLMModel, GPTLMModel