Taejun Kim commited on
Commit ·
bf5a4b4
1
Parent(s): b48eccb
no message
Browse files
djmix.py
CHANGED
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@@ -44,22 +44,25 @@ _HOMEPAGE = ""
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_LICENSE = ""
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# TODO: Add link to the official dataset URLs here
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# The HuggingFace Datasets library doesn
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# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
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_URLS = {
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"first_domain": "https://huggingface.co/great-new-dataset-first_domain.zip",
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"second_domain": "https://huggingface.co/great-new-dataset-second_domain.zip",
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}
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# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
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class DJMixDataset(datasets.GeneratorBasedBuilder):
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"""TODO: Short description of my dataset."""
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VERSION = datasets.Version("1.
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# This is an example of a dataset with multiple configurations.
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# If you don
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# just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
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# If you need to make complex sub-parts in the datasets with configurable options
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@@ -67,16 +70,16 @@ class DJMixDataset(datasets.GeneratorBasedBuilder):
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# BUILDER_CONFIG_CLASS = MyBuilderConfig
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# You will be able to load one or the other configurations in the following list with
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# data = datasets.load_dataset(
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# data = datasets.load_dataset(
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name="
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description="This part of my dataset covers a first domain"),
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datasets.BuilderConfig(name="
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description="This part of my dataset covers a second domain"),
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]
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DEFAULT_CONFIG_NAME = "first_domain" # It
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def _info(self):
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# TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
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@@ -103,8 +106,8 @@ class DJMixDataset(datasets.GeneratorBasedBuilder):
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description=_DESCRIPTION,
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# This defines the different columns of the dataset and their types
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features=features, # Here we define them above because they are different between the two configurations
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# If there
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# specify them. They
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# supervised_keys=("sentence", "label"),
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# Homepage of the dataset for documentation
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homepage=_HOMEPAGE,
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@@ -121,7 +124,24 @@ class DJMixDataset(datasets.GeneratorBasedBuilder):
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# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
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# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
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# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
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urls = _URLS[self.config.name]
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data_dir = dl_manager.download_and_extract(urls)
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return [
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datasets.SplitGenerator(
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@@ -170,3 +190,66 @@ class DJMixDataset(datasets.GeneratorBasedBuilder):
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"option2": data["option2"],
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"second_domain_answer": "" if split == "test" else data["second_domain_answer"],
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}
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_LICENSE = ""
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# TODO: Add link to the official dataset URLs here
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+
# The HuggingFace Datasets library doesn"t host the datasets but only points to the original files.
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# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
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_URLS = {
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"first_domain": "https://huggingface.co/great-new-dataset-first_domain.zip",
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"second_domain": "https://huggingface.co/great-new-dataset-second_domain.zip",
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}
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# _METADATA_URL = "https://huggingface.co/datasets/taejunkim/djmix/resolve/b961f21ab1a22b12e3154229bb40de9c950f8b26/metadata.json"
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_METADATA_URL = "https://huggingface.co/datasets/taejunkim/djmix/resolve/b48eccb4738ba09b96ea21d0bdb33f29e7be3b3c/metadata.json.gz"
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+
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# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
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class DJMixDataset(datasets.GeneratorBasedBuilder):
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"""TODO: Short description of my dataset."""
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VERSION = datasets.Version("1.0.0")
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# This is an example of a dataset with multiple configurations.
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# If you don"t want/need to define several sub-sets in your dataset,
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# just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
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# If you need to make complex sub-parts in the datasets with configurable options
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# BUILDER_CONFIG_CLASS = MyBuilderConfig
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# You will be able to load one or the other configurations in the following list with
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# data = datasets.load_dataset("my_dataset", "first_domain")
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# data = datasets.load_dataset("my_dataset", "second_domain")
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name="mixes", version=VERSION,
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description="This part of my dataset covers a first domain"),
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datasets.BuilderConfig(name="tracks", version=VERSION,
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description="This part of my dataset covers a second domain"),
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]
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DEFAULT_CONFIG_NAME = "first_domain" # It"s not mandatory to have a default configuration. Just use one if it make sense.
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def _info(self):
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# TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
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description=_DESCRIPTION,
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# This defines the different columns of the dataset and their types
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features=features, # Here we define them above because they are different between the two configurations
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# If there"s a common (input, target) tuple from the features, uncomment supervised_keys line below and
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# specify them. They"ll be used if as_supervised=True in builder.as_dataset.
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# supervised_keys=("sentence", "label"),
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# Homepage of the dataset for documentation
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homepage=_HOMEPAGE,
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# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
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# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
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# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
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metadata_path = dl_manager.download(_METADATA_URL)
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metadata_path = dl_manager.extract(metadata_path)
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dl_manager.iter_archive()
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with open(metadata_path) as f:
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metadata = json.load(f)
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download_mixes(metadata, self.cache_dir)
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audio_urls = []
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for mix in metadata:
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audio_urls.append(mix["audio_url"])
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dl_manager.download_custom(mix["audio_url"], youtube_dl_download)
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print("HI!!!!!!!!!!!!!!!!!!!!!!")
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urls = _URLS[self.config.name]
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dl_manager.downloaded_paths
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dl_manager.download_custom("haha.mp3", custom)
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data_dir = dl_manager.download_and_extract(urls)
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return [
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datasets.SplitGenerator(
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"option2": data["option2"],
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"second_domain_answer": "" if split == "test" else data["second_domain_answer"],
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}
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def youtube_dl_download(src_url, dst_path):
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from yt_dlp import YoutubeDL
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params = {
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"format": "bestaudio",
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"outtmpl": f"{dst_path}.%(ext)s",
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"postprocessors": [{ # Extract audio using ffmpeg
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"key": "FFmpegExtractAudio",
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"preferredcodec": "mp3",
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}]
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}
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with YoutubeDL(params) as ydl:
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ydl.download(src_url)
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os.rename(f"{dst_path}.mp3", dst_path)
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return dst_path
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def download_mixes(metadata, cache_dir):
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from yt_dlp.utils import DownloadError
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for mix in metadata:
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audio_path = os.path.join(cache_dir, mix["id"] + ".mp3")
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# TODO: try/except
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try:
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ret = download_audio(mix["audio_url"], audio_path)
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except DownloadError as e:
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print(e)
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print()
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def download_audio(url, path):
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if os.path.isfile(path):
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# TODO: silence?
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print(f'{path} already exists. Skip downloading.')
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return
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from yt_dlp import YoutubeDL
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params = {
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'format': 'bestaudio',
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'outtmpl': path,
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'postprocessors': [{ # Extract audio using ffmpeg
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'key': 'FFmpegExtractAudio',
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'preferredcodec': 'mp3',
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}]
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}
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with YoutubeDL(params) as ydl:
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os.makedirs(os.path.dirname(path), exist_ok=True)
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return ydl.download(url)
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if __name__ == "__main__":
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builder = DJMixDataset(
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config_name="mixes",
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data_dir="/data/djmix"
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)
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builder.download_and_prepare()
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dir_path = os.path.dirname(os.path.realpath(__file__))
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datasets.load_dataset(dir_path)
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