first revise

test_funasr.py

@@ -1,7 +1,7 @@
 import os
 import time
-import torchaudio
 import torch
+import torchaudio
 from funasr import AutoModel
 from funasr.utils.postprocess_utils import rich_transcription_postprocess
 from utils.calculate import cal_per_cer
@@ -34,18 +34,11 @@ def test_funasr(model_dir, audio_file, answer_file, use_gpu):
     model_name = os.path.basename(model_dir)
     model_type = determine_model_type(model_name)
     
-    if torch.cuda.get_device_name() == "Iluvatar BI-V100" and model_type == "whisper":
-        # 天垓100情况下的Whisper需要绕过不支持算子
-        torch.backends.cuda.enable_flash_sdp(False)
-        torch.backends.cuda.enable_mem_efficient_sdp(False)
-        torch.backends.cuda.enable_math_sdp(True)
-    
     # 不使用VAD, punct，spk模型，就测试原始ASR能力
     model = AutoModel(
         model=model_dir,
         # vad_model="fsmn-vad",
         # vad_kwargs={"max_single_segment_time": 30000},
-        vad_model=None,
         device="cuda:0" if use_gpu else "cpu",
         disable_update=True
     )
@@ -114,14 +107,6 @@ def test_funasr(model_dir, audio_file, answer_file, use_gpu):
                     batch_size_s=300
                 )
                 text = res[0]["text"]
-            # elif model_type == "uni_asr":
-            #     if i == 0:
-            #         os.remove(segment_path)
-            #         continue
-            #     res = model.generate(
-            #         input=segment_path
-            #     )
-            #     text = res[0]["text"]
             else:
                 raise RuntimeError("unknown model type")
             ts2 = time.time()
@@ -142,6 +127,13 @@ def test_funasr(model_dir, audio_file, answer_file, use_gpu):
     return processing_time, acc, generated_text
 
 if __name__ == "__main__":
+    if torch.cuda.is_available():
+        cuda_tensor = torch.randn(2, 2, device='cuda:0')
+        print(f"CUDA device index: {cuda_tensor.get_device()}")
+    else:
+        print("CUDA not available")
+        os._exit(1)
+
     test_result = {
         "time_cuda": 0,
         "acc_cuda": 0,
@@ -176,5 +168,5 @@ if __name__ == "__main__":
         json.dump(test_result, fp, ensure_ascii=False, indent=4)
     # 如果是SUT起来镜像的话，需要加上下面让pod永不停止以迎合k8s deployment, 本地测试以及docker run均不需要
     if K8S_TEST:
-        print(f"Start to sleep indefinitely", flush=True)
-        time.sleep(100000)
+        print(f"Start to sleep indefinity", flush=True)
+        time.sleep(100000)