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nena_speech_1_0.py

@@ -92,58 +92,63 @@ class NENASpeech(datasets.GeneratorBasedBuilder):
         )
 
     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, 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
+        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