Progress

.gitignore

@@ -6,3 +6,6 @@ venv
 
 # MacOS
 .DS_Store
+
+_common_voice.py
+_giga_speech.py

nena_speech_1_0.py

@@ -92,63 +92,58 @@ class NENASpeech(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        pass
-
-    # def _split_generators(self, dl_manager):
-    #     dialect = self.config.name
-
-    #     audio_urls = {}
-    #     splits = ("train", "dev", "test")
-    #     for split in splits:
-    #         audio_urls[split] = _AUDIO_URL.format(dialect=dialect, split=split)
-    #     archive_paths = dl_manager.download(audio_urls)
-    #     local_extracted_archive_paths = dl_manager.extract(archive_paths) if not dl_manager.is_streaming else {}
-
-    #     meta_urls = {split: _TRANSCRIPT_URL.format(dialect=dialect, split=split) for split in splits}
-    #     meta_paths = dl_manager.download_and_extract(meta_urls)
-
-    #     split_generators = []
-    #     split_names = {
-    #         "train": datasets.Split.TRAIN,
-    #         "dev": datasets.Split.VALIDATION,
-    #         "test": datasets.Split.TEST,
-    #     }
-    #     for split in splits:
-    #         split_generators.append(
-    #             datasets.SplitGenerator(
-    #                 name=split_names.get(split, split),
-    #                 gen_kwargs={
-    #                     "local_extracted_archive_paths": local_extracted_archive_paths.get(split),
-    #                     "archive": dl_manager.iter_archive(archive_paths.get(split)),
-    #                     "meta_path": meta_paths[split],
-    #                 },
-    #             ),
-    #         )
-
-    #     return split_generators
-
-    def _generate_examples(self):
-        pass
-    # def _generate_examples(self, local_extracted_archive_paths, archive, meta_path):
-    #     data_fields = list(self._info().features.keys())
-    #     metadata = {}
-    #     with open(meta_path, encoding="utf-8") as f:
-    #         reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
-    #         for row in tqdm(reader, desc="Reading metadata..."):
-    #             if not row["path"].endswith(".mp3"):
-    #                 row["path"] += ".mp3"
-    #             # if data is incomplete, fill with empty values
-    #             for field in data_fields:
-    #                 if field not in row:
-    #                     row[field] = ""
-    #             metadata[row["path"]] = row
-
-    #     for path, file in archive:
-    #         _, filename = os.path.split(path)
-    #         if filename in metadata:
-    #             result = dict(metadata[filename])
-    #             # set the audio feature and the path to the extracted file
-    #             path = os.path.join(local_extracted_archive_paths, path) if local_extracted_archive_paths else path
-    #             result["audio"] = {"path": path, "bytes": file.read()}
-    #             result["path"] = path
-    #             yield path, result
+        dialect = self.config.name
+
+        audio_urls = {}
+        splits = ("train", "dev", "test")
+        for split in splits:
+            audio_urls[split] = _AUDIO_URL.format(dialect=dialect, split=split)
+        archive_paths = dl_manager.download(audio_urls)
+        local_extracted_archive_paths = dl_manager.extract(archive_paths) if not dl_manager.is_streaming else {}
+
+        meta_urls = {split: _TRANSCRIPT_URL.format(dialect=dialect, split=split) for split in splits}
+        meta_paths = dl_manager.download_and_extract(meta_urls)
+
+        split_generators = []
+        split_names = {
+            "train": datasets.Split.TRAIN,
+            "dev": datasets.Split.VALIDATION,
+            "test": datasets.Split.TEST,
+        }
+        for split in splits:
+            split_generators.append(
+                datasets.SplitGenerator(
+                    name=split_names.get(split, split),
+                    gen_kwargs={
+                        "local_extracted_archive_paths": local_extracted_archive_paths.get(split),
+                        "archive": dl_manager.iter_archive(archive_paths.get(split)),
+                        "meta_path": meta_paths[split],
+                    },
+                ),
+            )
+
+        return split_generators
+
+    def _generate_examples(self, local_extracted_archive_paths, archive, meta_path):
+        data_fields = list(self._info().features.keys())
+        metadata = {}
+        with open(meta_path, encoding="utf-8") as f:
+            reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
+            for row in tqdm(reader, desc="Reading metadata..."):
+                if not row["path"].endswith(".mp3"):
+                    row["path"] += ".mp3"
+                # if data is incomplete, fill with empty values
+                for field in data_fields:
+                    if field not in row:
+                        row[field] = ""
+                metadata[row["path"]] = row
+
+        for path, file in archive:
+            _, filename = os.path.split(path)
+            if filename in metadata:
+                result = dict(metadata[filename])
+                # set the audio feature and the path to the extracted file
+                path = os.path.join(local_extracted_archive_paths, path) if local_extracted_archive_paths else path
+                result["audio"] = {"path": path, "bytes": file.read()}
+                result["path"] = path
+                yield path, result