stop try except and add back missing arguments (#884)

Signed-off-by: He, Xin3 <xin3.he@intel.com>

Author: xin3he

auto_round/__main__.py

@@ -18,7 +18,7 @@
 import sys
 
 from auto_round.compressors import BaseCompressor
-from auto_round.eval.eval_cli import EvalArgumentParser, _eval_init, eval, eval_task_by_task, eval_with_vllm
+from auto_round.eval.eval_cli import EvalArgumentParser, _eval_init, eval, eval_task_by_task
 from auto_round.schemes import PRESET_SCHEMES
 from auto_round.utils import (
     clear_memory,

auto_round/eval/eval_cli.py

@@ -54,6 +54,7 @@ def __init__(self, *args, **kwargs):
         self.add_argument(
             "--disable_trust_remote_code", action="store_true", help="whether to disable trust_remote_code"
         )
+        self.add_argument("--seed", default=42, type=int, help="random seed")
         self.add_argument("--eval_bs", "--bs", "--batch_size", default=None, type=int, help="batch size in evaluation")
         self.add_argument("--eval_task_by_task", action="store_true", help="whether to eval task by task.")
         self.add_argument(
@@ -113,15 +114,9 @@ def _eval_init(tasks, model_path, device, disable_trust_remote_code=False, dtype
 
 def eval(args):
     if args.eval_backend == "vllm":
-        try:
-            assert isinstance(args.model, str), "vllm evaluation only supports model name or path."
-            eval_with_vllm(args)
-            return
-        except Exception as e:  # pragma: no cover
-            print(f"vllm evaluation failed: {e}, fallback to default hf backend evaluation.")
-            args.eval_backend = "hf"
-            clear_memory()
-
+        assert isinstance(args.model, str), "vllm evaluation only supports model name or path."
+        eval_with_vllm(args)
+        return
     tasks, model_args, device_str = _eval_init(
         args.tasks, args.model, args.device_map, args.disable_trust_remote_code, args.eval_model_dtype
     )
@@ -308,7 +303,7 @@ def eval_with_vllm(args):
 
     st = time.time()
     os.environ["TOKENIZERS_PARALLELISM"] = "false"
-    device_str, _ = get_device_and_parallelism(args.device)
+    device_str, _ = get_device_and_parallelism(args.device_map)
     eval_model_dtype = get_model_dtype(args.eval_model_dtype, "auto")
     if (batch_size := args.eval_bs) is None:
         batch_size = "auto:8"