Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- found
+language_creators:
+- found
+languages:
+- en
+licenses:
+- unknown
+multilinguality:
+- monolingual
+size_categories:
+- n>1M
+source_datasets:
+- original
+task_categories:
+- conditional-text-generation
+- sequence-modeling
+- text-retrieval
+task_ids:
+- document-retrieval
+- entity-linking-retrieval
+- explanation-generation
+- language-modeling
+- summarization
+---
+
+
+# Dataset Card Creation Guide
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** https://recipenlg.cs.put.poznan.pl/
+- **Repository:** https://github.com/Glorf/recipenlg
+- **Paper:** https://www.aclweb.org/anthology/volumes/2020.inlg-1/
+- **Leaderboard:** [More Information Needed]
+- **Point of Contact:** [More Information Needed]
+
+### Dataset Summary
+
+[More Information Needed]
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+[More Information Needed]
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+[More Information Needed]
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]

dataset_infos.json

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+{"default": {"description": "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.\n", "citation": "@inproceedings{bien-etal-2020-recipenlg,\ntitle = \"{R}ecipe{NLG}: A Cooking Recipes Dataset for Semi-Structured Text Generation\",\nauthor = \"Bie{'n}, Micha{l}  and\n  Gilski, Micha{l}  and\n  Maciejewska, Martyna  and\n  Taisner, Wojciech  and\n  Wisniewski, Dawid  and\n  Lawrynowicz, Agnieszka\",\nbooktitle = \"Proceedings of the 13th International Conference on Natural Language Generation\",\nmonth = dec,\nyear = \"2020\",\naddress = \"Dublin, Ireland\",\npublisher = \"Association for Computational Linguistics\",\nurl = \"https://www.aclweb.org/anthology/2020.inlg-1.4\",\npages = \"22--28\"\n}\n", "homepage": "https://recipenlg.cs.put.poznan.pl/", "license": "", "features": {"id": {"dtype": "int32", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "ingredients": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "directions": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "link": {"dtype": "string", "id": null, "_type": "Value"}, "source": {"num_classes": 2, "names": ["Gathered", "Recipes1M"], "names_file": null, "id": null, "_type": "ClassLabel"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "recipe_nlg", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2194783815, "num_examples": 2231142, "dataset_name": "recipe_nlg"}}, "download_checksums": {}, "download_size": 0, "post_processing_size": null, "dataset_size": 2194783815, "size_in_bytes": 2194783815}}

dummy/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ee123547c4e727144cf6e60dfa897d38d86eda371659d53925e24f8eb874e098
+size 1421

recipe_nlg.py

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+# coding=utf-8
+# Copyright 2020 The HuggingFace Datasets Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import ast
+import csv
+import os
+
+import datasets
+
+
+_CITATION = """\
+@inproceedings{bien-etal-2020-recipenlg,
+title = "{R}ecipe{NLG}: A Cooking Recipes Dataset for Semi-Structured Text Generation",
+author = "Bie{'n}, Micha{l}  and
+  Gilski, Micha{l}  and
+  Maciejewska, Martyna  and
+  Taisner, Wojciech  and
+  Wisniewski, Dawid  and
+  Lawrynowicz, Agnieszka",
+booktitle = "Proceedings of the 13th International Conference on Natural Language Generation",
+month = dec,
+year = "2020",
+address = "Dublin, Ireland",
+publisher = "Association for Computational Linguistics",
+url = "https://www.aclweb.org/anthology/2020.inlg-1.4",
+pages = "22--28"
+}
+"""
+
+_DESCRIPTION = """\
+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.
+"""
+
+_HOMEPAGE = "https://recipenlg.cs.put.poznan.pl/"
+
+_FILENAME = "full_dataset.csv"
+
+
+class RecipeNlg(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    @property
+    def manual_download_instructions(self):
+        return """\
+    You need to go to https://recipenlg.cs.put.poznan.pl/,
+    and manually download the dataset. Once it is completed,
+    a file named dataset.zip will be appeared in your Downloads folder
+    or whichever folder your browser chooses to save files to. You then have
+    to unzip the file and move full_dataset.csv under <path/to/folder>.
+    The <path/to/folder> can e.g. be "~/manual_data".
+    recipe_nlg can then be loaded using the following command `datasets.load_dataset("recipe_nlg", data_dir="<path/to/folder>")`.
+    """
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "id": datasets.Value("int32"),
+                "title": datasets.Value("string"),
+                "ingredients": datasets.Sequence(datasets.Value("string")),
+                "directions": datasets.Sequence(datasets.Value("string")),
+                "link": datasets.Value("string"),
+                "source": datasets.ClassLabel(names=["Gathered", "Recipes1M"]),
+                "ner": datasets.Sequence(datasets.Value("string")),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        path_to_manual_file = os.path.abspath(os.path.expanduser(dl_manager.manual_dir))
+        if not os.path.exists(path_to_manual_file):
+            raise FileNotFoundError(
+                "{} does not exist. Make sure you insert a manual dir via `datasets.load_dataset('recipe_nlg', data_dir=...)` that includes file name {}. Manual download instructions: {}".format(
+                    path_to_manual_file,
+                    _FILENAME,
+                    self.manual_download_instructions,
+                )
+            )
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(path_to_manual_file, "full_dataset.csv"),
+                    "split": "train",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        with open(filepath, encoding="utf-8") as csv_file:
+            csv_reader = csv.reader(csv_file)
+            for idx, row in enumerate(csv_reader):
+                if idx == 0:
+                    continue
+                resp = {
+                    "id": row[0],
+                    "title": row[1],
+                    "ingredients": ast.literal_eval(row[2]),
+                    "directions": ast.literal_eval(row[3]),
+                    "link": row[4],
+                    "source": row[5],
+                    "ner": ast.literal_eval(row[6]),
+                }
+                yield idx, resp