Debug

Signed-off-by: Jael Gu <mengjia.gu@zilliz.com>

torch_vggish.py

@@ -56,7 +56,7 @@ class Vggish(NNOperator):
     def __call__(self, datas: List[NamedTuple('data', [('audio', 'ndarray'), ('sample_rate', 'int')])]) -> numpy.ndarray:
         audios = numpy.stack([item.audio for item in datas])
         sr = datas[0].sample_rate
-        audio_array = numpy.reshape(audios, (-1, 2))
+        audio_array = numpy.reshape(audios, (-1, 1))
         audio_tensors = self.preprocess(audio_array, sr).to(self.device)
         features = self.model(audio_tensors)
         outs = features.to("cpu")
@@ -66,15 +66,3 @@ class Vggish(NNOperator):
         ii = numpy.iinfo(audio.dtype)
         samples = 2 * audio / (ii.max - ii.min + 1)
         return vggish_input.waveform_to_examples(samples, sr, return_tensor=True)
-
-
-# if __name__ == '__main__':
-#     encoder = Vggish()
-#
-#     # audio_path = '/path/to/audio'
-#     # vec = encoder(audio_path)
-#
-#     audio_data = numpy.zeros((2, 441344))
-#     sample_rate = 44100
-#     vec = encoder(audio_data, sample_rate)
-#     print(vec)