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import os |
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from functools import partial |
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from pathlib import Path |
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from typing import Dict, Iterable |
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import datasets |
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from datasets import DatasetDict, DownloadManager, load_dataset |
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import pandas as pd |
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AVAILABLE_DATASETS = { |
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'small': 'https://files.grouplens.org/datasets/movielens/ml-latest-small.zip', |
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'full': 'https://files.grouplens.org/datasets/movielens/ml-latest.zip', |
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} |
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VERSION = datasets.Version("0.0.1") |
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class MovielensDataset(datasets.GeneratorBasedBuilder): |
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"""MovielensDataset dataset.""" |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name=data_name, version=VERSION, description=f"{data_name} movielens dataset" |
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) |
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for data_name in AVAILABLE_DATASETS |
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] |
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def _info(self) -> datasets.DatasetInfo: |
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return datasets.DatasetInfo( |
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description="", |
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features=datasets.Features( |
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{ |
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"movieId": datasets.Value("string"), |
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"title": datasets.Value("string"), |
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"genres": datasets.Sequence(datasets.Value("string")), |
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"tag": datasets.Sequence(datasets.Value("string")), |
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} |
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), |
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supervised_keys=None, |
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homepage="https://grouplens.org/datasets/movielens/latest/", |
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citation="", |
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) |
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def _split_generators( |
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self, dl_manager: DownloadManager |
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) -> Iterable[datasets.SplitGenerator]: |
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downloader = partial( |
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lambda split: dl_manager.download_and_extract( |
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AVAILABLE_DATASETS[self.config.name] |
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) |
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) |
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folder = os.path.splitext(os.path.basename(AVAILABLE_DATASETS[self.config.name]))[ |
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0 |
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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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"root_path": downloader("train"), |
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"split": "train", |
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"folder": folder, |
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}, |
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), |
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] |
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def _generate_examples( |
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self, root_path: str, split: str, folder: str |
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) -> Iterable[Dict]: |
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split_path = Path(root_path) / folder |
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movies_file = split_path / "movies.csv" |
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movies = pd.read_csv(movies_file, sep=',', encoding='utf-8') |
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movies['genres'] = movies['genres'].str.split('|') |
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tags_file = split_path / "tags.csv" |
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tags = pd.read_csv(tags_file, sep=',', encoding='utf-8') |
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tags = tags.groupby('movieId').agg({'tag': list}).reset_index() |
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movies = movies.merge(tags, on='movieId') |
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for idx, row in movies.iterrows(): |
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yield idx, { |
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'movieId': row['movieId'], |
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'title': row['title'], |
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'genres': row['genres'], |
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'tag': row['tag'], |
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} |
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