File size: 4,161 Bytes
c13737d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 | import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
from datasets.iterable_dataset import IterableDataset
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.file_utils import cached_path
DATASETS_ON_HF_GCP = [
{"dataset": "wikipedia", "config_name": "20220301.de"},
{"dataset": "wikipedia", "config_name": "20220301.en"},
{"dataset": "wikipedia", "config_name": "20220301.fr"},
{"dataset": "wikipedia", "config_name": "20220301.frr"},
{"dataset": "wikipedia", "config_name": "20220301.it"},
{"dataset": "wikipedia", "config_name": "20220301.simple"},
{"dataset": "snli", "config_name": "plain_text"},
{"dataset": "eli5", "config_name": "LFQA_reddit"},
{"dataset": "wiki40b", "config_name": "en"},
{"dataset": "wiki_dpr", "config_name": "psgs_w100.nq.compressed"},
{"dataset": "wiki_dpr", "config_name": "psgs_w100.nq.no_index"},
{"dataset": "wiki_dpr", "config_name": "psgs_w100.multiset.no_index"},
{"dataset": "natural_questions", "config_name": "default"},
]
def list_datasets_on_hf_gcp_parameters(with_config=True):
if with_config:
return [
{
"testcase_name": d["dataset"] + "/" + d["config_name"],
"dataset": d["dataset"],
"config_name": d["config_name"],
}
for d in DATASETS_ON_HF_GCP
]
else:
return [
{"testcase_name": dataset, "dataset": dataset} for dataset in {d["dataset"] for d in DATASETS_ON_HF_GCP}
]
@parameterized.named_parameters(list_datasets_on_hf_gcp_parameters(with_config=True))
class TestDatasetOnHfGcp(TestCase):
dataset = None
config_name = None
def test_dataset_info_available(self, dataset, config_name):
with TemporaryDirectory() as tmp_dir:
dataset_module = dataset_module_factory(dataset, cache_dir=tmp_dir)
builder_cls = import_main_class(dataset_module.module_path, dataset=True)
builder_instance: DatasetBuilder = builder_cls(
cache_dir=tmp_dir,
config_name=config_name,
hash=dataset_module.hash,
)
dataset_info_url = "/".join(
[
HF_GCP_BASE_URL,
builder_instance._relative_data_dir(with_hash=False).replace(os.sep, "/"),
config.DATASET_INFO_FILENAME,
]
)
datset_info_path = cached_path(dataset_info_url, cache_dir=tmp_dir)
self.assertTrue(os.path.exists(datset_info_path))
@pytest.mark.integration
def test_as_dataset_from_hf_gcs(tmp_path_factory):
tmp_dir = tmp_path_factory.mktemp("test_hf_gcp") / "test_wikipedia_simple"
dataset_module = dataset_module_factory("wikipedia", cache_dir=tmp_dir)
builder_cls = import_main_class(dataset_module.module_path)
builder_instance: DatasetBuilder = builder_cls(
cache_dir=tmp_dir,
config_name="20220301.frr",
hash=dataset_module.hash,
)
# use the HF cloud storage, not the original download_and_prepare that uses apache-beam
builder_instance._download_and_prepare = None
builder_instance.download_and_prepare()
ds = builder_instance.as_dataset()
assert ds
@pytest.mark.integration
def test_as_streaming_dataset_from_hf_gcs(tmp_path):
dataset_module = dataset_module_factory("wikipedia", cache_dir=tmp_path)
builder_cls = import_main_class(dataset_module.module_path, dataset=True)
builder_instance: DatasetBuilder = builder_cls(
cache_dir=tmp_path,
config_name="20220301.frr",
hash=dataset_module.hash,
)
ds = builder_instance.as_streaming_dataset()
assert ds
assert isinstance(ds, IterableDatasetDict)
assert "train" in ds
assert isinstance(ds["train"], IterableDataset)
assert next(iter(ds["train"]))
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