test remove script

my_dataset.py

@@ -1,132 +0,0 @@
-import LANGUAGES as LANGUAGES
-import STATS as STATS
-import datasets as datasets
-from datasets.utils.py_utils import size_str
-
-_HOMEPAGE = "homepage-info"
-_CITATION = "citation-info"
-_LICENSE = "license-info"
-_DESCRIPTION = "description-info"
-
-_PROMPTS_URLS = "....."
-_DATA_URL = "...."
-
-
-
-"""Configuration class, allows to have multiple configurations if needed"""
-class ParlaSpeechDatasetConfig(datasets.BuilderConfig):
-    """BuilderConfig for ParlaSpeech"""
-
-    def __init__(self, name, version, **kwargs):
-        self.language = kwargs.pop("language", None)
-        self.release_date = kwargs.pop("release_date", None)
-        self.num_clips = kwargs.pop("num_clips", None)
-        self.num_speakers = kwargs.pop("num_speakers", None)
-        self.validated_hr = kwargs.pop("validated_hr", None)
-        self.total_hr = kwargs.pop("total_hr", None)
-        self.size_bytes = kwargs.pop("size_bytes", None)
-        self.size_human = size_str(self.size_bytes)
-        description = ( ##Update Description in the final version
-            f"ParlaSpeech is a dataset in {self.language} released on {self.release_date}. "
-        )
-        super(ParlaSpeechDatasetConfig, self).__init__(
-            name=name,
-            version=datasets.Version(version),
-            description=description,
-            **kwargs,
-        )
-
-
-class ParlaSpeechDataset(datasets.GeneratroBasedBuilder):
-
-    """"
-    ### NO TENGO CLARO SI HACE FALTA ESTO ###
-    DEFAULT_CONFIG_NAME = "all"
-
-    BUILDER_CONFIGS = [
-        ParlaSpeechDatasetConfig(
-            name=lang,
-            version=STATS["version"],
-            language=LANGUAGES[lang],
-            release_date=STATS["date"],
-            num_clips=lang_stats["clips"],
-            num_speakers=lang_stats["users"],
-            total_hr=float(lang_stats["totalHrs"]) if lang_stats["totalHrs"] else None,
-            size_bytes=int(lang_stats["size"]) if lang_stats["size"] else None,
-        )
-        for lang, lang_stats in STATS["locales"].items()
-    ]
-    """
-
-    """ When the dataset is loaded and .info is called, the info defined here is displayed."""
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    #"speaker_id": datasets.Value("string"),
-                    "path": datasets.Value("string"),
-                    "audio": datasets.Audio(sampling_rate=16_000),
-                    "sentence": datasets.Value("string"),
-                }
-            ),
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-            version = self.config.version,
-        )
-
-    " Used to organize the audio files and sentence prompts in each split, once downloaded the dataset."
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators"""
-        prompts_paths = dl_manager.download(_PROMPTS_URLS)
-        archive = dl_manager.download(_DATA_URL)
-        ## local_extracted_archives = dl_manager.extract(archive)
-        train_dir = "vivos/train"
-        test_dir = "vivos/test"
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "prompts_path": prompts_paths["train"],
-                    "path_to_clips": train_dir + "/waves",
-                    "audio_files": dl_manager.iter_archive(archive),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "prompts_path": prompts_paths["test"],
-                    "path_to_clips": test_dir + "/waves",
-                    "audio_files": dl_manager.iter_archive(archive),
-                },
-            ),
-        ]
-
-    def _generate_examples(self, prompts_path, path_to_clips, audio_files):
-        """Yields examples as (key, example) tuples."""
-        examples = {}
-        with open(prompts_path, encoding="utf-8") as f: ##prompts_path -> transcript.tsv
-            for row in f:
-                data = row.strip().split(" ", 1)
-                #speaker_id = data[0].split("_")[0]
-                #audio_path = "/".join([path_to_clips, speaker_id, data[0] + ".wav"])
-                audio_path = "/".join([path_to_clips, "DSPG_137_23122015_9873.69_9888.03.wav"])
-                examples[audio_path] = {
-                    #"speaker_id": speaker_id,
-                    "path": audio_path,
-                    "sentence": data[1],
-                }
-        inside_clips_dir = False
-        id_ = 0
-        for path, f in audio_files:
-            if path.startswith(path_to_clips):
-                inside_clips_dir = True
-                if path in examples:
-                    audio = {"path": path, "bytes": f.read()}
-                    yield id_, {**examples[path], "audio": audio}
-                    id_ += 1
-            elif inside_clips_dir:
-                break