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Switch to downloading remote files
Browse files- README.md +2 -2
- arxivDIGESTables.py +5 -12
README.md
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@@ -13,6 +13,6 @@ configs:
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# ArXivDIGESTables
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# ArXivDIGESTables
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**Note**: Please use huggingface datasets as a way to preview the data only as `load_dataset` does not work well with the current data format. Instead it is recommended to directly download `tables.jsonl`, `papers.jsonl`, and `full_texts.jsonl.gz`.
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See [the github repo](https://github.com/bnewm0609/arxivDIGESTables) for more details.
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arxivDIGESTables.py
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@@ -26,12 +26,7 @@ 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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title = {A great new dataset},
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author={huggingface, Inc.
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},
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year={2020}
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}
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"""
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# TODO: Add description of the dataset 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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"high_quality": "
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"medium_quality": "
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}
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@@ -151,7 +146,6 @@ class ArxivDIGESTables(datasets.GeneratorBasedBuilder):
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)
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def _split_generators(self, dl_manager):
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print("hi", flush=True)
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# TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
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# If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
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@@ -159,9 +153,8 @@ class ArxivDIGESTables(datasets.GeneratorBasedBuilder):
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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_path = urls
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return [
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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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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TBD
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"""
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# TODO: Add description of the dataset 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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"high_quality": "https://huggingface.co/datasets/blnewman/arxivDIGESTables/resolve/main/tables.jsonl",
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"medium_quality": "https://huggingface.co/datasets/blnewman/arxivDIGESTables/resolve/main/tables_medium_quality.jsonl",
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}
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)
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def _split_generators(self, dl_manager):
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# TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
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# If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
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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_path = dl_manager.download_and_extract(urls)
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# data_path = urls
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return [
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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