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  1. README.md +2 -2
  2. arxivDIGESTables.py +5 -12
README.md CHANGED
@@ -13,6 +13,6 @@ configs:
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  # ArXivDIGESTables
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- (In progress)
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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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  # 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.
arxivDIGESTables.py CHANGED
@@ -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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- @InProceedings{huggingface:dataset,
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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
@@ -49,8 +44,8 @@ _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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- "high_quality": "/Users/blnewman/Documents/research/projects/paper_comparison/arxivDIGESTables_hf_data/tables.jsonl", # "https://huggingface.co/datasets/blnewman/arxivDIGESTables/resolve/main/tables.jsonl",
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- "medium_quality": "/Users/blnewman/Documents/research/projects/paper_comparison/arxivDIGESTables_hf_data/tables_medium_quality.jsonl", # "https://huggingface.co/datasets/blnewman/arxivDIGESTables/resolve/main/tables_medium_quality.jsonl",
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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 = dl_manager.download_and_extract(urls)
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- print(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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  # 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,