feat: update code to download data
Browse files
jhtdb.py
CHANGED
@@ -11,12 +11,18 @@ import datasets
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# TODO: Add BibTeX citation
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# Find for instance the citation on arxiv or on the dataset repo/website
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_CITATION = """\
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@
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title
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},
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}
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"""
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# TODO: Add description of the dataset here
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@@ -31,12 +37,8 @@ _HOMEPAGE = ""
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# TODO: Add the licence for the dataset here if you can find it
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_LICENSE = ""
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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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"small_50": {
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"train": (
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"datasets/jhtdb/small_50/metadata_train.csv",
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@@ -93,6 +95,9 @@ class JHTDB(datasets.GeneratorBasedBuilder):
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def _split_generators(self, dl_manager):
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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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named_splits = {
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"train": datasets.Split.TRAIN,
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# TODO: Add BibTeX citation
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# Find for instance the citation on arxiv or on the dataset repo/website
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_CITATION = """\
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@article{Li_2008,
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title={A public turbulence database cluster and applications to study Lagrangian evolution of velocity increments in turbulence},
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volume={9},
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ISSN={1468-5248},
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url={http://dx.doi.org/10.1080/14685240802376389},
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DOI={10.1080/14685240802376389},
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journal={Journal of Turbulence},
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publisher={Informa UK Limited},
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author={Li, Yi and Perlman, Eric and Wan, Minping and Yang, Yunke and Meneveau, Charles and Burns, Randal and Chen, Shiyi and Szalay, Alexander and Eyink, Gregory},
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year={2008},
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month=jan, pages={N31} }
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"""
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# TODO: Add description of the dataset here
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# TODO: Add the licence for the dataset here if you can find it
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_LICENSE = ""
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_BASE_URL = "https://huggingface.co/datasets/dl2-g32/jhtdb/resolve/main"
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_URLS = {
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"small_50": {
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"train": (
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"datasets/jhtdb/small_50/metadata_train.csv",
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def _split_generators(self, dl_manager):
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urls = _URLS[self.config.name]
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urls = {
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k: (f"{_BASE_URL}/{v[0]}", f"{_BASE_URL}/{v[1]}") for k, v in urls.items()
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}
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data_dir = dl_manager.download_and_extract(urls)
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named_splits = {
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"train": datasets.Split.TRAIN,
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