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Merged
merged 1 commit into from
Oct 11, 2025
+6 −11
Merged

lm_eval stop try except and add back missing arguments #884

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2 changes: 1 addition & 1 deletion auto_round/__main__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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,
Expand Down
15 changes: 5 additions & 10 deletions auto_round/eval/eval_cli.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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(
Expand Down Expand Up @@ -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
)
Expand Down Expand Up @@ -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"
Expand Down