Update demo.py

demo.py

@@ -9,21 +9,33 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 from transformers.trainer_utils import set_seed
 
 
-def demo_qwen_pretrain(args):
+def _load_model_tokenizer(args):
     tokenizer = AutoTokenizer.from_pretrained(
-        args.checkpoint_path, trust_remote_code=True
+        args.checkpoint_path, trust_remote_code=True,
     )
     print("load tokenizer")
-    max_memory = f"{int(torch.cuda.mem_get_info()[0] / 1024 ** 3) - 2}GB"
 
+    if args.cpu_only:
+        device_map = "cpu"
+        max_memory = None
+    else:
+        device_map = "auto"
+        max_memory_str = f"{int(torch.cuda.mem_get_info()[0] / 1024 ** 3) - 2}GB"
         n_gpus = torch.cuda.device_count()
-    max_memory = {i: max_memory for i in range(n_gpus)}
+        max_memory = {i: max_memory_str for i in range(n_gpus)}
+
     model = AutoModelForCausalLM.from_pretrained(
         args.checkpoint_path,
-        device_map="cuda:0",
+        device_map=device_map,
         max_memory=max_memory,
         trust_remote_code=True,
     ).eval()
+
+    return model, tokenizer
+
+
+def demo_qwen_pretrain(args):
+    model, tokenizer = _load_model_tokenizer(args)
     inputs = tokenizer(
         "蒙古国的首都是乌兰巴托（Ulaanbaatar）\n冰岛的首都是雷克雅未克（Reykjavik）\n埃塞俄比亚的首都是",
         return_tensors="pt",
@@ -34,20 +46,7 @@ def demo_qwen_pretrain(args):
 
 
 def demo_qwen_chat(args):
-    tokenizer = AutoTokenizer.from_pretrained(
-        args.checkpoint_path, trust_remote_code=True
-    )
-    print("load tokenizer")
-    max_memory = f"{int(torch.cuda.mem_get_info()[0] / 1024 ** 3) - 2}GB"
-
-    n_gpus = torch.cuda.device_count()
-    max_memory = {i: max_memory for i in range(n_gpus)}
-    model = AutoModelForCausalLM.from_pretrained(
-        args.checkpoint_path,
-        device_map="cuda:0",
-        max_memory=max_memory,
-        trust_remote_code=True,
-    ).eval()
+    model, tokenizer = _load_model_tokenizer(args)
     queries = [
         "请问把大象关冰箱总共要几步？",
         "1+3=?",
@@ -65,16 +64,20 @@ def demo_qwen_chat(args):
         print("Response:", response, end="\n")
 
 
-if __name__ == "__main__":
+def main():
     parser = argparse.ArgumentParser(description="Test HF checkpoint.")
     parser.add_argument("-c", "--checkpoint-path", type=str, help="Checkpoint path")
     parser.add_argument("-s", "--seed", type=int, default=1234, help="Random seed")
-    parser.add_argument("--gpu", type=int, default=0, help="gpu id")
+    parser.add_argument("--cpu-only", action="store_true", help="Run demo with CPU only")
 
     args = parser.parse_args()
     set_seed(args.seed)
 
-    if 'chat' in args.checkpoint_path.lower():
+    if "chat" in args.checkpoint_path.lower():
         demo_qwen_chat(args)
     else:
         demo_qwen_pretrain(args)
+
+
+if __name__ == "__main__":
+    main()