streaming embeddings

dcase23-task2-enriched.py

@@ -5,6 +5,8 @@ import datasets.info
 import pandas as pd
 import numpy as np
 import tempfile
+import requests
+import io
 from pathlib import Path
 from datasets import load_dataset
 from typing import Iterable, Dict, Optional, Union, List
@@ -395,10 +397,15 @@ class DCASE2023Task2Dataset(datasets.GeneratorBasedBuilder):
                 audio_path[split] = dl_manager.download(self.config.data_urls[split])
                 local_extracted_archive[split] = dl_manager.extract(
                     audio_path[split]) if not dl_manager.is_streaming else None
-                if self.config.embeddings_urls is not None and not dl_manager.is_streaming:
+                if self.config.embeddings_urls is not None:
                     for emb_name, emb_data in self.config.embeddings_urls.items():
                         downloaded_embeddings = dl_manager.download(emb_data[split])
-                        embeddings[split][emb_name] = np.load(downloaded_embeddings, allow_pickle=True)["arr_0"].item()
+                        if dl_manager.is_streaming:
+                            response = requests.get(downloaded_embeddings)
+                            response.raise_for_status()
+                            downloaded_embeddings = io.BytesIO(response.content)
+                        npz_file = np.load(downloaded_embeddings, allow_pickle=True)
+                        embeddings[split][emb_name] = npz_file["arr_0"].item()
 
         return [
             datasets.SplitGenerator(