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import ast |
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import csv |
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import os |
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import datasets |
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_CITATION = """\ |
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@inproceedings{bien-etal-2020-recipenlg, |
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title = "{R}ecipe{NLG}: A Cooking Recipes Dataset for Semi-Structured Text Generation", |
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author = "Bie{'n}, Micha{l} and |
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Gilski, Micha{l} and |
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Maciejewska, Martyna and |
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Taisner, Wojciech and |
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Wisniewski, Dawid and |
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Lawrynowicz, Agnieszka", |
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booktitle = "Proceedings of the 13th International Conference on Natural Language Generation", |
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month = dec, |
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year = "2020", |
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address = "Dublin, Ireland", |
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publisher = "Association for Computational Linguistics", |
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url = "https://www.aclweb.org/anthology/2020.inlg-1.4", |
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pages = "22--28" |
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} |
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""" |
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_DESCRIPTION = """\ |
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The dataset contains 2231142 cooking recipes (>2 millions). It's processed in more careful way and provides more samples than any other dataset in the area. |
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""" |
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_HOMEPAGE = "https://recipenlg.cs.put.poznan.pl/" |
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_FILENAME = "full_dataset.csv" |
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class RecipeNlg(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("1.0.0") |
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@property |
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def manual_download_instructions(self): |
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return """\ |
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You need to go to https://recipenlg.cs.put.poznan.pl/, |
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and manually download the dataset. Once it is completed, |
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a file named dataset.zip will be appeared in your Downloads folder |
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or whichever folder your browser chooses to save files to. You then have |
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to unzip the file and move full_dataset.csv under <path/to/folder>. |
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The <path/to/folder> can e.g. be "~/manual_data". |
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recipe_nlg can then be loaded using the following command `datasets.load_dataset("recipe_nlg", data_dir="<path/to/folder>")`. |
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""" |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"id": datasets.Value("int32"), |
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"title": datasets.Value("string"), |
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"ingredients": datasets.Sequence(datasets.Value("string")), |
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"directions": datasets.Sequence(datasets.Value("string")), |
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"link": datasets.Value("string"), |
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"source": datasets.ClassLabel(names=["Gathered", "Recipes1M"]), |
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"ner": datasets.Sequence(datasets.Value("string")), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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path_to_manual_file = os.path.abspath(os.path.expanduser(dl_manager.manual_dir)) |
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if not os.path.exists(path_to_manual_file): |
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raise FileNotFoundError( |
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f"{path_to_manual_file} does not exist. Make sure you insert a manual dir via `datasets.load_dataset('recipe_nlg', data_dir=...)` that includes file name {_FILENAME}. Manual download instructions: {self.manual_download_instructions}" |
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) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"filepath": os.path.join(path_to_manual_file, "full_dataset.csv"), |
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"split": "train", |
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}, |
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), |
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] |
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def _generate_examples(self, filepath, split): |
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with open(filepath, encoding="utf-8") as csv_file: |
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csv_reader = csv.reader(csv_file) |
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for idx, row in enumerate(csv_reader): |
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if idx == 0: |
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continue |
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resp = { |
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"id": row[0], |
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"title": row[1], |
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"ingredients": ast.literal_eval(row[2]), |
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"directions": ast.literal_eval(row[3]), |
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"link": row[4], |
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"source": row[5], |
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"ner": ast.literal_eval(row[6]), |
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} |
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yield idx, resp |
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