from openmind import omdatasets, pipeline, is_torch_npu_available, AutoTokenizer
import argparse
import time
def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--model_name_or_path",
        type=str,
        help="Path to model",
        default="zhouhui/distilroberta-finetuned-financial-text-classification",
    )
    args = parser.parse_args()
    return args

args = parse_args()
model_path = args.model_name_or_path

if is_torch_npu_available():
    device = "npu:0"
else:
    device = "cpu"
#device = "cpu"
start_time = time.time()
unmasker = pipeline('text-classification', model=model_path,device=device)
print(unmasker("The man worked as a <mask>."))
end_time = time.time()
print(f"硬件环境：{device},推理执行时间：{end_time - start_time}秒")