diff --git a/modelscope/models/cv/video_stabilization/utils/WarpUtils.py b/modelscope/models/cv/video_stabilization/utils/WarpUtils.py
index e8f713cd..eefd8697 100644
--- a/modelscope/models/cv/video_stabilization/utils/WarpUtils.py
+++ b/modelscope/models/cv/video_stabilization/utils/WarpUtils.py
@@ -46,8 +46,9 @@ def mesh_warp_frame(frame, x_motion, y_motion, cap_width, cap_height):
             homo,
             origin_kp.contiguous().view(2, -1).permute(1, 0)).permute(1, 0)
 
-        projection.append(projected_kp.contiguous().view(
-            *origin_kp.shape).permute(1, 2, 0))  # 2, H, W --> H, W, 2
+        projection.append(
+            projected_kp.contiguous().view(*origin_kp.shape).permute(
+                1, 2, 0))  # 2, H, W --> H, W, 2
     projection = torch.stack(projection, 0)
 
     projection[:, :, :, 0] = projection[:, :, :, 0] / cfg.MODEL.WIDTH * 2. - 1.
diff --git a/modelscope/models/nlp/gpt_moe/moe/sharded_moe.py b/modelscope/models/nlp/gpt_moe/moe/sharded_moe.py
index f8eed00f..ff12e13a 100644
--- a/modelscope/models/nlp/gpt_moe/moe/sharded_moe.py
+++ b/modelscope/models/nlp/gpt_moe/moe/sharded_moe.py
@@ -430,9 +430,9 @@ class MOELayer(Base):
         self.use_expert_residual_network = use_expert_residual_network
 
         if self.use_expert_residual_network:
-            self.expert_network = nn.Sequential(*([
-                ExpertResidualLayer(self.gate.model_dim) for _ in range(6)
-            ]))  # noqa
+            self.expert_network = nn.Sequential(
+                *([ExpertResidualLayer(self.gate.model_dim)
+                   for _ in range(6)]))  # noqa
 
         self.use_tutel = use_tutel and TUTEL_INSTALLED
 
diff --git a/modelscope/pipelines/audio/asr_inference_pipeline.py b/modelscope/pipelines/audio/asr_inference_pipeline.py
index 823964e5..2379274c 100644
--- a/modelscope/pipelines/audio/asr_inference_pipeline.py
+++ b/modelscope/pipelines/audio/asr_inference_pipeline.py
@@ -210,7 +210,12 @@ class AutomaticSpeechRecognitionPipeline(Pipeline):
 
         if isinstance(audio_in, str):
             # for funasr code, generate wav.scp from url or local path
-            self.audio_in, self.raw_inputs = generate_scp_from_url(audio_in)
+            if audio_in.startswith('http') or os.path.isfile(audio_in):
+                self.audio_in, self.raw_inputs = generate_scp_from_url(
+                    audio_in)
+            else:
+                raise FileNotFoundError(
+                    f'file {audio_in} NOT FOUND, please CHECK!')
         elif isinstance(audio_in, bytes):
             self.audio_in = audio_in
             self.raw_inputs = None
diff --git a/modelscope/pipelines/audio/speaker_diarization_pipeline.py b/modelscope/pipelines/audio/speaker_diarization_pipeline.py
index 24ebb130..dfb808d0 100644
--- a/modelscope/pipelines/audio/speaker_diarization_pipeline.py
+++ b/modelscope/pipelines/audio/speaker_diarization_pipeline.py
@@ -237,7 +237,8 @@ class SpeakerDiarizationPipeline(Pipeline):
                 (isinstance(audio_in, tuple) and all(isinstance(item, str) for item in audio_in)):
             logger.info(f'Speaker Verification Processing: {audio_in} ...')
         else:
-            logger.info(f'Speaker Verification Processing: {str(audio_in)[:100]} ...')
+            logger.info(
+                f'Speaker Verification Processing: {str(audio_in)[:100]} ...')
 
         data_cmd, raw_inputs = None, None
         if isinstance(audio_in, tuple) or isinstance(audio_in, list):