cache speaker metadata

libriheavy.py

@@ -1,5 +1,7 @@
 import json
 import gzip
+import os
+from pathlib import Path
 
 import datasets
 import numpy as np
@@ -79,15 +81,25 @@ class Libriheavy(datasets.GeneratorBasedBuilder):
         # now we load the individual speaker metadata
         speaker_metadata = {}
         for speaker_id, metadata_path in tqdm(speaker_list.items()):
-            metadata_path = f"{PATH}/{speaker_id}/{metadata_path}"
-            metadata_path = dl_manager.download_and_extract(metadata_path)
-            with open(metadata_path, "r") as f:
-                speaker_metadata[speaker_id] = json.load(f)
+            hf_home = os.environ.get("HF_HOME", "~/.cache/huggingface")
+            metadata_cache = f"hf_home/libriheavy_metadata"
+            # we always cache the speaker metadata, as it is small
+            if os.path.exists(f"{metadata_cache}/{speaker_id}.json"):
+                with open(f"{metadata_cache}/{speaker_id}.json", "r") as f:
+                    speaker_metadata[speaker_id] = json.load(f)
+            else:
+                Path(metadata_cache).mkdir(parents=True, exist_ok=True)
+                metadata_path = f"{PATH}/{speaker_id}/{metadata_path}"
+                metadata_path = dl_manager.download_and_extract(metadata_path)
+                with open(metadata_path, "r") as f:
+                    speaker_metadata[speaker_id] = json.load(f)
+                with open(f"{metadata_cache}/{speaker_id}.json", "w") as f:
+                    json.dump(speaker_metadata[speaker_id], f)
+
         speaker_chunks = []
         even_speaker_chunks = []
         odd_speaker_chunks = []
         for speaker_id, metadata in speaker_metadata.items():
-            print(f"Processing speaker {speaker_id}")
             for chunk_id, chunk in metadata["chunks"].items():
                 chunk_dict = {
                     "speaker_id": speaker_id,
@@ -124,9 +136,7 @@ class Libriheavy(datasets.GeneratorBasedBuilder):
 
     def _generate_examples(self, speaker_chunks, split):
         """Yields examples."""
-        print(f"Generating examples for {split}")
         for chunk in speaker_chunks:
-            print(f"Processing {chunk['id']}")
             npz = dict(np.load(chunk["audio"], allow_pickle=True))
             utterances = npz.keys()
             with gzip.open(chunk["text"], "rt") as f: