Datasets:
| # coding=utf-8 | |
| # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. | |
| # | |
| # 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. | |
| # Lint as: python3 | |
| """author_profiling dataset""" | |
| import json | |
| import os | |
| import datasets | |
| # TODO: Add BibTeX citation | |
| # Find for instance the citation on arxiv or on the dataset repo/website | |
| _CITATION = """\ | |
| """ | |
| _LICENSE = """http://www.apache.org/licenses/LICENSE-2.0""" | |
| # TODO: Add description of the dataset here | |
| # You can copy an official description | |
| _DESCRIPTION = """\ | |
| he corpus for the author profiling analysis contains texts in Russian-language which labeled for 5 tasks: | |
| 1) gender -- 13530 texts with the labels, who wrote this: text female or male; | |
| 2) age -- 13530 texts with the labels, how old the person who wrote the text. This is a number from 12 to 80. In addition, for the classification task we added 5 age groups: 1-19; 20-29; 30-39; 40-49; 50+; | |
| 3) age imitation -- 7574 texts, where crowdsource authors is asked to write three texts: | |
| a) in their natural manner, | |
| b) imitating the style of someone younger, | |
| c) imitating the style of someone older; | |
| 4) gender imitation -- 5956 texts, where the crowdsource authors is asked to write texts: in their origin gender and pretending to be the opposite gender; | |
| 5) style imitation -- 5956 texts, where crowdsource authors is asked to write a text on behalf of another person of your own gender, with a distortion of the authors usual style. | |
| """ | |
| # TODO: Add a link to an official homepage for the dataset here | |
| _HOMEPAGE = "https://github.com/sag111/Author-Profiling" | |
| # TODO: Add link to the official dataset URLs here | |
| # The HuggingFace dataset library don't host the datasets but only point to the original files | |
| # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method) | |
| _URLs = { | |
| "main": "https://sagteam.ru/author_profiling/main.zip" | |
| } | |
| # TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case | |
| class AuthorProfiling(datasets.GeneratorBasedBuilder): | |
| """ | |
| The Corpus for the analysis of author profiling in Russian-language texts. | |
| """ | |
| VERSION = datasets.Version("2.0.1") | |
| # This is an example of a dataset with multiple configurations. | |
| # If you don't want/need to define several sub-sets in your dataset, | |
| # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes. | |
| # If you need to make complex sub-parts in the datasets with configurable options | |
| # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig | |
| # BUILDER_CONFIG_CLASS = MyBuilderConfig | |
| # You will be able to load one or the other configurations in the following list with | |
| # data = datasets.load_dataset('my_dataset', 'first_domain') | |
| # data = datasets.load_dataset('my_dataset', 'second_domain') | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name="main", version=VERSION, description="This a main version of Author Profiling dataset" | |
| ), | |
| ] | |
| DEFAULT_CONFIG_NAME = "main" # It's not mandatory to have a default configuration. Just use one if it make sense. | |
| def _info(self): | |
| # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset | |
| if self.config.name == "main": # This is the name of the configuration selected in BUILDER_CONFIGS above | |
| features = datasets.Features( | |
| { | |
| "id": datasets.Value("string"), | |
| "text": datasets.Value("string"), | |
| "account_id": datasets.Value("string"), | |
| "author_id": datasets.Value("int64"), | |
| "age": datasets.Value("int64"), | |
| "age_group": datasets.Value("string"), #.ClassLabel(names=["0-19", "20-29", "30-39", "40-49", "50+"]), | |
| "gender": datasets.Value("string"), #.ClassLabel(names=["male", "female"]), | |
| "no_imitation": datasets.Value("string"), #.ClassLabel(names=["no_any_imitation", "with_any_imitation"]), | |
| "age_imitation": datasets.Value("string"), #.ClassLabel(names=["no_age_imitation", "younger", "older", "None"]), | |
| "gender_imitation": datasets.Value("string"), #.ClassLabel(names=["no_gender_imitation", "with_gender_imitation", "None"]), | |
| "style_imitation": datasets.Value("string"), #.ClassLabel(names=["no_style_imitation", "with_style_imitation", "None"]), | |
| # These are the features of your dataset like images, labels ... | |
| } | |
| ) | |
| else: # This is an example to show how to have different features for "first_domain" and "second_domain" | |
| pass | |
| return datasets.DatasetInfo( | |
| # This is the description that will appear on the datasets page. | |
| description=_DESCRIPTION, | |
| # This defines the different columns of the dataset and their types | |
| features=features, # Here we define them above because they are different between the two configurations | |
| # If there's a common (input, target) tuple from the features, | |
| # specify them here. They'll be used if as_supervised=True in | |
| # builder.as_dataset. | |
| supervised_keys=None, | |
| # Homepage of the dataset for documentation | |
| homepage=_HOMEPAGE, | |
| # License for the dataset if available | |
| license=_LICENSE, | |
| # Citation for the dataset | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| """Returns SplitGenerators.""" | |
| # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration | |
| # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name | |
| # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs | |
| # 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. | |
| # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive | |
| my_urls = _URLs[self.config.name] | |
| data_dir = dl_manager.download_and_extract(my_urls) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "filepath": os.path.join(data_dir, self.config.name, "train.jsonl"), | |
| "split": "train", | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "filepath": os.path.join(data_dir, self.config.name, "valid.jsonl"), | |
| "split": "valid", | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| # These kwargs will be passed to _generate_examples | |
| gen_kwargs={ | |
| "filepath": os.path.join(data_dir, self.config.name, "test.jsonl"), | |
| "split": "test" | |
| }, | |
| ), | |
| ] | |
| def _generate_examples( | |
| self, filepath, split # method parameters are unpacked from `gen_kwargs` as given in `_split_generators` | |
| ): | |
| """Yields examples as (key, example) tuples.""" | |
| # This method handles input defined in _split_generators to yield (key, example) tuples from the dataset. | |
| # The `key` is here for legacy reason (tfds) and is not important in itself. | |
| with open(filepath, encoding="utf-8") as f: | |
| for id_, row in enumerate(f): | |
| data = json.loads(row.rstrip('\n|\r')) | |
| if self.config.name == "main": | |
| yield id_, data | |
| else: | |
| pass |