I get an error
RuntimeError: Expected 3-dimensional input for 3-dimensional weight [512, 1, 10], but got 5-dimensional input of size [1, 1, 1, 240000, 2] instead

while feeding the Wav2Vec2Processor and HubertForCTC with a wav audio file:
processor = Wav2Vec2Processor.from_pretrained("facebook/hubert-xlarge-ls960-ft"
    , cache_dir=os.getenv("cache_dir", "../../models"))
model = HubertForCTC.from_pretrained("facebook/hubert-xlarge-ls960-ft"
    , cache_dir=os.getenv("cache_dir", "../../models"))
for idx, audio in enumerate(train_loader):
    input_values = processor(audio, sampling_rate=sampling_rate, return_tensors="pt").input_values  # Batch size 1
    logits = model(input_values).logits
    predicted_ids = torch.argmax(logits, dim=-1)
    transcription = processor.decode(predicted_ids[0])
    print(transcription)

where the audio input comes from this function
def read_audio(self, audio_path):
        try:
            import soundfile as sf
            y, _ = sf.read(audio_path)
            return y # [1, 960000]
        except Exception as err:
            try:
                import librosa
                y, _ = librosa.load(audio_path, sr=self.sr)
                return y
            except Exception as err:
                pass
                return None

The shape of the audio is like (with soundfile):
0 torch.Size([1, 960000])
1 torch.Size([1, 240000, 2])

and librosa:
0 torch.Size([1, 240000])
1 torch.Size([1, 960000])

Testing code is here 8. Original question on SF here 25.