add check for plenary

voxpopuli.py

@@ -13,16 +13,16 @@ _LANGUAGES = sorted(
         "sk", "sl", "et", "lt", "pt", "bg", "el", "lv", "mt", "sv", "da"
     ]
 )
-_LANGUAGES_V2 = [f"{x}_v2" for x in _LANGUAGES]
+_LANGUAGES_V2 = [f"{x}_v2" for x in _LANGUAGES]  # TODO: what are they used for?
 
 _YEARS = list(range(2009, 2020 + 1))
 
 # unnecessary
-_CONFIG_TO_LANGS = {
-    "400k": _LANGUAGES,
-    "100k": _LANGUAGES,
-    "10k": _LANGUAGES,
-}
+# _CONFIG_TO_LANGS = {
+#     "400k": _LANGUAGES,
+#     "100k": _LANGUAGES,
+#     "10k": _LANGUAGES,
+# }
 
 _CONFIG_TO_YEARS = {
     "400k": _YEARS + [f"{y}_2" for y in _YEARS],
@@ -31,7 +31,8 @@ _CONFIG_TO_YEARS = {
     # "asr": _YEARS
 }
 for lang in _LANGUAGES:
-    _CONFIG_TO_YEARS[lang] = _YEARS
+    # _CONFIG_TO_YEARS[lang] = _YEARS
+    _CONFIG_TO_YEARS[lang] = [2020]
 
 _BASE_URL = "https://dl.fbaipublicfiles.com/voxpopuli/"
 
@@ -66,9 +67,20 @@ class Voxpopuli(datasets.GeneratorBasedBuilder):
         for name in _LANGUAGES + ["10k", "100k", "400k"]
     ]
     # DEFAULT_CONFIG_NAME = "400k"
-    # DEFAULT_WRITER_BATCH_SIZE = 256
+    DEFAULT_WRITER_BATCH_SIZE = 256
 
     def _info(self):
+        try:
+            import torch
+            import torchaudio
+        except ImportError as e:
+            raise ValueError(
+                f"{str(e)}.\n" +
+                "Loading voxpopuli requires `torchaudio` to be installed."
+                "You can install torchaudio with `pip install torchaudio`."
+            )
+        global torchaudio
+
         features = datasets.Features(
             {
                 "path": datasets.Value("string"),
@@ -87,8 +99,19 @@ class Voxpopuli(datasets.GeneratorBasedBuilder):
         )
 
     def _read_metadata(self, metadata_path):
-        # TODO: check for predicate??
-        #  @ https://github.com/facebookresearch/voxpopuli/blob/main/voxpopuli/get_unlabelled_data.py#L34
+        #  from https://github.com/facebookresearch/voxpopuli/blob/main/voxpopuli/get_unlabelled_data.py#L34
+        def predicate(id_):
+            is_plenary = id_.find("PLENARY") > -1
+            if self.config.name == "10k":  # in {"10k", "10k_sd"}
+                return is_plenary and 20190101 <= int(id_[:8]) < 20200801
+            elif self.config.name == "100k":
+                return is_plenary
+            elif self.config.name in _LANGUAGES:
+                return is_plenary and id_.endswith(self.config.name)
+            elif self.config.name in _LANGUAGES_V2:
+                return id_.endswith(self.config.name.split("_")[0])
+            return True
+
         metadata = defaultdict(list)
 
         with open(metadata_path, encoding="utf-8") as csv_file:
@@ -96,11 +119,10 @@ class Voxpopuli(datasets.GeneratorBasedBuilder):
             for i, row in tqdm(enumerate(csv_reader)):
                 if i == 0:
                     continue
-                audio_id, segment_id, start, end = row
-                event_id, lang = audio_id.rsplit("_", 1)[-2:]
-                if lang in self.languages:
-                # if lang in ["hr", "et"]:
-                    metadata[audio_id].append((float(start), float(end)))
+                event_id, segment_id, start, end = row
+                _, lang = event_id.rsplit("_", 1)[-2:]
+                if lang in self.config.languages and predicate(event_id):
+                    metadata[event_id].append((float(start), float(end)))
 
         return metadata
 
@@ -108,7 +130,6 @@ class Voxpopuli(datasets.GeneratorBasedBuilder):
         metadata_path = dl_manager.download_and_extract(_META_URL)
 
         years = _CONFIG_TO_YEARS[self.config.name]
-        # urls = [_DATA_URL.format(lang=language, year=year) for language in ["hr", "et"] for year in [2020]]  # , "et"]
         urls = [_DATA_URL.format(lang=language, year=year) for language in self.config.languages for year in years]
         dl_manager.download_config.num_proc = len(urls)
         data_dirs = dl_manager.download_and_extract(urls)
@@ -124,15 +145,6 @@ class Voxpopuli(datasets.GeneratorBasedBuilder):
         ]
 
     def _generate_examples(self, data_dirs, metadata_path):
-        try:
-            import torch
-            import torchaudio
-        except ImportError as e:
-            raise ValueError(
-                "Loading voxpopuli requires `torchaudio` to be installed."
-                "You can install torchaudio with `pip install torchaudio`." + e
-            )
-
         metadata = self._read_metadata(metadata_path)
 
         for data_dir in data_dirs:
@@ -140,12 +152,14 @@ class Voxpopuli(datasets.GeneratorBasedBuilder):
                 path_components = file.split(os.sep)
                 language, year, audio_filename = path_components[-3:]
                 audio_id, _ = os.path.splitext(audio_filename)
+                if audio_id not in metadata:
+                    continue
                 timestamps = metadata[audio_id]
 
                 waveform, sr = torchaudio.load(file)
                 duration = waveform.size(1)
 
-                # split audio on the fly and write segments as arrays
+                # split audio on the fly and yield segments as arrays - they will be converted to bytes by Audio feature
                 for segment_id, (start, stop) in enumerate(timestamps):
                     segment = waveform[:, int(start * sr): min(int(stop * sr), duration)]