init

tokenize_dataset_s2s.py

@@ -4,7 +4,7 @@ from os.path import expanduser
 import shutil
 import torch
 from soundfile import LibsndfileError
-from datasets import load_dataset, DatasetDict
+from datasets import load_dataset, DatasetDict, Audio
 from encodec_audio_tokenizer import EncodecTokenizer
 
 
@@ -18,18 +18,24 @@ hf_dataset = f"seamless-align-{direction}"
 dataset = load_dataset(f"{hf_org}/{hf_dataset}", f"subset_{dataset_id}", split="train")
 tokenizer = EncodecTokenizer.from_pretrained()
 
+audio_loader = Audio()
+
 
 def error_file(example):
     for side in sides:
         try:
-            example[f"{side}.audio"]
+            audio_loader.decode_example(example[f"{side}.audio"])
         except LibsndfileError:
             return False
     return True
 
 
 print(f"Num examples: {len(dataset)}")
-dataset = dataset.filter(error_file)
+for s in sides:
+    dataset = dataset.cast_column(f"{s}.audio", Audio(decode=False))
+dataset = dataset.filter(error_file, num_proc=num_proc, desc="drop broken audio")
+for s in sides:
+    dataset = dataset.cast_column(f"{s}.audio", Audio())
 print(f"Num examples (after filtering): {len(dataset)}")