code: def convert_trajectory_transformer_original_pytorch_checkpoint_to_pytorch(
      logbase, dataset, loadpath, epoch, device
  ):
      """Converting Sequential blocks to ModuleList"""
  
      gpt, gpt_epoch = utils.load_model(
          logbase, dataset, loadpath, epoch=epoch, device=device
      )
      trajectory_transformer = TrajectoryTransformerModel(gpt.config)
  
      trajectory_transformer.tok_emb.load_state_dict(
          gpt.tok_emb.state_dict()
      )
      trajectory_transformer.pos_emb = gpt.pos_emb
      trajectory_transformer.drop.load_state_dict(gpt.drop.state_dict())
      trajectory_transformer.ln_f.load_state_dict(gpt.ln_f.state_dict())
      trajectory_transformer.head.load_state_dict(gpt.head.state_dict())
  
      for i, block in enumerate(gpt.blocks):
          trajectory_transformer.blocks[i].ln1.load_state_dict(
              gpt.blocks[i].ln1.state_dict()
          )
          trajectory_transformer.blocks[i].ln2.load_state_dict(
              gpt.blocks[i].ln2.state_dict()
          )
          trajectory_transformer.blocks[i].attn.load_state_dict(
              gpt.blocks[i].attn.state_dict()
          )
  
          trajectory_transformer.blocks[i].l1.load_state_dict(
              gpt.blocks[i].mlp[0].state_dict()
          )
          trajectory_transformer.blocks[i].act.load_state_dict(
              gpt.blocks[i].mlp[1].state_dict()
          )
          trajectory_transformer.blocks[i].l2.load_state_dict(
              gpt.blocks[i].mlp[2].state_dict()
          )
          trajectory_transformer.blocks[i].drop.load_state_dict(
              gpt.blocks[i].mlp[3].state_dict()
          )
  
      torch.save(
          trajectory_transformer.state_dict(), "pytorch_model.bin"
      )
  
imports: import torch
  import trajectory.utils
  from transformers import TrajectoryTransformerModel
label_desc: Use image node_id 1 for calling a global function with example usage: convert_trajectory_transformer_original_pytorch_checkpoint_to_pytorch(logbase, dataset, loadpath, epoch, device) without return types