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Source code for torchtext.datasets.ag_news

from torchtext.utils import download_from_url, unicode_csv_reader
from torchtext.data.datasets_utils import _RawTextIterableDataset
from torchtext.data.datasets_utils import _wrap_split_argument
from torchtext.data.datasets_utils import _add_docstring_header
import os
import io

URL = {
    'train': "https://raw.githubusercontent.com/mhjabreel/CharCnn_Keras/master/data/ag_news_csv/train.csv",
    'test': "https://raw.githubusercontent.com/mhjabreel/CharCnn_Keras/master/data/ag_news_csv/test.csv",
}

MD5 = {
    'train': "b1a00f826fdfbd249f79597b59e1dc12",
    'test': "d52ea96a97a2d943681189a97654912d",
}

NUM_LINES = {
    'train': 120000,
    'test': 7600,
}


[docs]@_add_docstring_header(num_lines=NUM_LINES, num_classes=4) @_wrap_split_argument(('train', 'test')) def AG_NEWS(root, split): def _create_data_from_csv(data_path): with io.open(data_path, encoding="utf8") as f: reader = unicode_csv_reader(f) for row in reader: yield int(row[0]), ' '.join(row[1:]) path = download_from_url(URL[split], root=root, path=os.path.join(root, split + ".csv"), hash_value=MD5[split], hash_type='md5') return _RawTextIterableDataset("AG_NEWS", NUM_LINES[split], _create_data_from_csv(path))

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