[to #42322933] fix ans_pipeline bug and add test

modelscope/pipelines/audio/ans_pipeline.py

@@ -48,13 +48,13 @@ class ANSPipeline(Pipeline):
 
     def preprocess(self, inputs: Input) -> Dict[str, Any]:
         if isinstance(inputs, bytes):
-            raw_data, fs = sf.read(io.BytesIO(inputs))
+            data1, fs = sf.read(io.BytesIO(inputs))
         elif isinstance(inputs, str):
-            raw_data, fs = sf.read(inputs)
+            data1, fs = sf.read(inputs)
         else:
             raise TypeError(f'Unsupported type {type(inputs)}.')
-        if len(raw_data.shape) > 1:
-            data1 = raw_data[:, 0]
+        if len(data1.shape) > 1:
+            data1 = data1[:, 0]
         if fs != self.SAMPLE_RATE:
             data1 = librosa.resample(data1, fs, self.SAMPLE_RATE)
         data1 = audio_norm(data1)

tests/pipelines/test_speech_signal_process.py

@@ -65,6 +65,21 @@ class SpeechSignalProcessTest(unittest.TestCase):
         ans(NOISE_SPEECH_FILE, output_path=output_path)
         print(f'Processed audio saved to {output_path}')
 
+    @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
+    def test_ans_bytes(self):
+        # Download audio files
+        download(NOISE_SPEECH_URL, NOISE_SPEECH_FILE)
+        model_id = 'damo/speech_frcrn_ans_cirm_16k'
+        ans = pipeline(
+            Tasks.speech_signal_process,
+            model=model_id,
+            pipeline_name=Pipelines.speech_frcrn_ans_cirm_16k)
+        output_path = os.path.abspath('output.wav')
+        with open(NOISE_SPEECH_FILE, 'rb') as f:
+            data = f.read()
+            ans(data, output_path=output_path)
+        print(f'Processed audio saved to {output_path}')
+
 
 if __name__ == '__main__':
     unittest.main()