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import json
import os
import uuid
from collections import defaultdict
from random import randint
from unittest.mock import patch
from torchtext.data.datasets_utils import _ParseSQuADQAData
from torchtext.datasets.squad1 import SQuAD1
from torchtext.datasets.squad2 import SQuAD2
from ..common.case_utils import TempDirMixin, zip_equal, get_random_unicode
from ..common.parameterized_utils import nested_params
from ..common.torchtext_test_case import TorchtextTestCase
def _get_mock_json_data():
rand_string = get_random_unicode(10)
mock_json_data = {
"data": [
{
"title": rand_string,
"paragraphs": [
{
"context": rand_string,
"qas": [
{
"answers": [
{
"answer_start": randint(1, 1000),
"text": rand_string,
}
],
"question": rand_string,
"id": uuid.uuid1().hex,
},
],
}
],
}
]
}
return mock_json_data
def _get_mock_dataset(root_dir, base_dir_name):
"""
root_dir: directory to the mocked dataset
"""
base_dir = os.path.join(root_dir, base_dir_name)
os.makedirs(base_dir, exist_ok=True)
if base_dir_name == SQuAD1.__name__:
file_names = ("train-v1.1.json", "dev-v1.1.json")
else:
file_names = ("train-v2.0.json", "dev-v2.0.json")
mocked_data = defaultdict(list)
for file_name in file_names:
txt_file = os.path.join(base_dir, file_name)
with open(txt_file, "w", encoding="utf-8") as f:
mock_json_data = _get_mock_json_data()
f.write(json.dumps(mock_json_data))
split = "train" if "train" in file_name else "dev"
dataset_line = next(iter(_ParseSQuADQAData([("file_handle", mock_json_data)])))
mocked_data[split].append(dataset_line)
return mocked_data
class TestSQuADs(TempDirMixin, TorchtextTestCase):
root_dir = None
samples = []
@classmethod
def setUpClass(cls):
super().setUpClass()
cls.root_dir = cls.get_base_temp_dir()
cls.patcher = patch("torchdata.datapipes.iter.util.cacheholder._hash_check", return_value=True)
cls.patcher.start()
@classmethod
def tearDownClass(cls):
cls.patcher.stop()
super().tearDownClass()
@nested_params([SQuAD1, SQuAD2], ["train", "dev"])
def test_squads(self, squad_dataset, split):
expected_samples = _get_mock_dataset(os.path.join(self.root_dir, "datasets"), squad_dataset.__name__)[split]
dataset = squad_dataset(root=self.root_dir, split=split)
samples = list(dataset)
for sample, expected_sample in zip_equal(samples, expected_samples):
self.assertEqual(sample, expected_sample)
@nested_params([SQuAD1, SQuAD2], ["train", "dev"])
def test_squads_split_argument(self, squad_dataset, split):
# call `_get_mock_dataset` to create mock dataset files
_ = _get_mock_dataset(self.root_dir, squad_dataset.__name__)
dataset1 = squad_dataset(root=self.root_dir, split=split)
(dataset2,) = squad_dataset(root=self.root_dir, split=(split,))
for d1, d2 in zip_equal(dataset1, dataset2):
self.assertEqual(d1, d2)
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