[feat] update import

trainer/trainer_utils.py

@@ -8,6 +8,8 @@ import numpy as np
 import torch
 import torch.distributed as dist
 from torch.utils.data import Sampler
+from transformers import AutoTokenizer
+from model.model_minimind import MiniMindForCausalLM
 
 
 def is_main_process():
@@ -96,9 +98,6 @@ def lm_checkpoint(lm_config, weight='full_sft', model=None, optimizer=None, epoc
 
 
 def init_model(lm_config, from_weight='pretrain', tokenizer_path='../model', save_dir='../out', device='cuda'):
-    from transformers import AutoTokenizer
-    from model.model_minimind import MiniMindForCausalLM
-    
     tokenizer = AutoTokenizer.from_pretrained(tokenizer_path)
     model = MiniMindForCausalLM(lm_config)