init

tokenize_dataset_s2s.py

@@ -1,6 +1,7 @@
 import os
 
 import torch
+import numpy as np
 from datasets import load_dataset, DatasetDict
 from encodec_audio_tokenizer import EncodecTokenizer
 
@@ -18,7 +19,9 @@ tokenizer = EncodecTokenizer.from_pretrained()
 
 def tokenize(batch):
     for side in sides:
-        wav = torch.concat([i["array"] for i in batch[f"{side}.audio"]])
+        wav = torch.as_tensor(np.concatenate([i["array"] for i in batch[f"{side}.audio"]]))
+        print(wav.shape)
+
         sr = [i["sampling_rate"] for i in batch[f"{side}.audio"]]
         batch[f"{side}.audio.tokens"] = tokenizer.wav_to_tokens(wav=wav, sample_rate=sr).numpy().tolist()
     return batch