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test_dataset_common.py
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test_dataset_common.py
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# coding=utf-8
# Copyright 2020 HuggingFace Inc.
#
# 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.
import glob
import logging
import os
import tempfile
import requests
from absl.testing import parameterized
from nlp import (
BuilderConfig,
DatasetBuilder,
DownloadConfig,
GenerateMode,
MockDownloadManager,
hf_api,
hf_bucket_url,
import_main_class,
load_dataset,
prepare_module,
)
from .utils import aws, local, slow
logging.basicConfig(level=logging.INFO)
class DatasetTester(object):
def __init__(self, parent):
self.parent = parent
def load_builder_class(self, dataset_name, is_local=False):
# Download/copy dataset script
if is_local is True:
module_path, _ = prepare_module("./datasets/" + dataset_name)
else:
module_path, _ = prepare_module(dataset_name, download_config=DownloadConfig(force_download=True))
# Get dataset builder class
builder_cls = import_main_class(module_path)
# Instantiate dataset builder
return builder_cls
def load_all_configs(self, dataset_name, is_local=False):
# get builder class
builder_cls = self.load_builder_class(dataset_name, is_local=is_local)
builder = builder_cls
if len(builder.BUILDER_CONFIGS) == 0:
return [None]
return builder.BUILDER_CONFIGS
def check_load_dataset(self, dataset_name, configs, is_local=False):
# test only first config to speed up testing
for config in configs:
with tempfile.TemporaryDirectory() as processed_temp_dir, tempfile.TemporaryDirectory() as raw_temp_dir:
# create config and dataset
dataset_builder_cls = self.load_builder_class(dataset_name, is_local=is_local)
name = config.name if config is not None else None
dataset_builder = dataset_builder_cls(name=name, cache_dir=processed_temp_dir)
# TODO: skip Beam datasets and datasets that lack dummy data for now
if not dataset_builder.test_dummy_data:
logging.info("Skip tests for this dataset for now")
return
if config is not None:
version = config.version
else:
version = dataset_builder.VERSION
# create mock data loader manager that has a special download_and_extract() method to download dummy data instead of real data
mock_dl_manager = MockDownloadManager(
dataset_name=dataset_name,
config=config,
version=version,
cache_dir=raw_temp_dir,
is_local=is_local,
)
if dataset_builder.__class__.__name__ == "Csv":
# need slight adoption for csv dataset
mock_dl_manager.download_dummy_data()
path_to_dummy_data = mock_dl_manager.dummy_file
dataset_builder.config.data_files = {
"train": os.path.join(path_to_dummy_data, "train.csv"),
"test": os.path.join(path_to_dummy_data, "test.csv"),
"dev": os.path.join(path_to_dummy_data, "dev.csv"),
}
elif dataset_builder.__class__.__name__ == "Json":
# need slight adoption for json dataset
mock_dl_manager.download_dummy_data()
path_to_dummy_data = mock_dl_manager.dummy_file
dataset_builder.config.data_files = {
"train": os.path.join(path_to_dummy_data, "train.json"),
"test": os.path.join(path_to_dummy_data, "test.json"),
"dev": os.path.join(path_to_dummy_data, "dev.json"),
}
elif dataset_builder.__class__.__name__ == "Pandas":
# need slight adoption for json dataset
mock_dl_manager.download_dummy_data()
path_to_dummy_data = mock_dl_manager.dummy_file
dataset_builder.config.data_files = {
"train": os.path.join(path_to_dummy_data, "train.pkl"),
"test": os.path.join(path_to_dummy_data, "test.pkl"),
"dev": os.path.join(path_to_dummy_data, "dev.pkl"),
}
elif dataset_builder.__class__.__name__ == "Text":
mock_dl_manager.download_dummy_data()
path_to_dummy_data = mock_dl_manager.dummy_file
dataset_builder.config.data_files = {
"train": os.path.join(path_to_dummy_data, "train.txt"),
"test": os.path.join(path_to_dummy_data, "test.txt"),
"dev": os.path.join(path_to_dummy_data, "dev.txt"),
}
# mock size needed for dummy data instead of actual dataset
if dataset_builder.info is not None:
# approximate upper bound of order of magnitude of dummy data files
one_mega_byte = 2 << 19
dataset_builder.info.size_in_bytes = 2 * one_mega_byte
dataset_builder.info.download_size = one_mega_byte
dataset_builder.info.dataset_size = one_mega_byte
# generate examples from dummy data
dataset_builder.download_and_prepare(
dl_manager=mock_dl_manager,
download_mode=GenerateMode.FORCE_REDOWNLOAD,
ignore_verifications=True,
try_from_hf_gcs=False,
)
# get dataset
dataset = dataset_builder.as_dataset()
# check that dataset is not empty
for split in dataset_builder.info.splits.keys():
# check that loaded datset is not empty
self.parent.assertTrue(len(dataset[split]) > 0)
def get_local_dataset_names():
datasets = [dataset_dir.split("/")[-2] for dataset_dir in glob.glob("./datasets/*/")]
return [{"testcase_name": x, "dataset_name": x} for x in datasets]
@parameterized.named_parameters(get_local_dataset_names())
@local
class LocalDatasetTest(parameterized.TestCase):
dataset_name = None
def setUp(self):
self.dataset_tester = DatasetTester(self)
def test_load_dataset(self, dataset_name):
configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)[:1]
self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True)
def test_builder_class(self, dataset_name):
builder_cls = self.dataset_tester.load_builder_class(dataset_name, is_local=True)
name = builder_cls.BUILDER_CONFIGS[0].name if builder_cls.BUILDER_CONFIGS else None
with tempfile.TemporaryDirectory() as tmp_cache_dir:
builder = builder_cls(name=name, cache_dir=tmp_cache_dir)
self.assertTrue(isinstance(builder, DatasetBuilder))
def test_builder_configs(self, dataset_name):
builder_configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)
self.assertTrue(len(builder_configs) > 0)
if builder_configs[0] is not None:
all(self.assertTrue(isinstance(config, BuilderConfig)) for config in builder_configs)
@slow
def test_load_dataset_all_configs(self, dataset_name):
configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)
self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True)
@slow
def test_load_real_dataset(self, dataset_name):
with tempfile.TemporaryDirectory() as temp_data_dir:
download_config = DownloadConfig()
download_config.download_mode = GenerateMode.FORCE_REDOWNLOAD
dataset = load_dataset(
"./datasets/" + dataset_name, data_dir=temp_data_dir, download_config=download_config
)
for split in dataset.keys():
self.assertTrue(len(dataset[split]) > 0)
def get_aws_dataset_names():
api = hf_api.HfApi()
# fetch all dataset names
datasets = [x.id for x in api.dataset_list(with_community_datasets=False)]
return [{"testcase_name": x, "dataset_name": x} for x in datasets]
@parameterized.named_parameters(get_aws_dataset_names())
@aws
class AWSDatasetTest(parameterized.TestCase):
dataset_name = None
def setUp(self):
self.dataset_tester = DatasetTester(self)
def test_dataset_has_valid_etag(self, dataset_name):
py_script_path = list(filter(lambda x: x, dataset_name.split("/")))[-1] + ".py"
dataset_url = hf_bucket_url(dataset_name, filename=py_script_path, dataset=True)
etag = None
try:
response = requests.head(dataset_url, allow_redirects=True, proxies=None, timeout=10)
if response.status_code == 200:
etag = response.headers.get("Etag")
except (EnvironmentError, requests.exceptions.Timeout):
pass
self.assertIsNotNone(etag)
def test_builder_class(self, dataset_name):
builder_cls = self.dataset_tester.load_builder_class(dataset_name)
name = builder_cls.BUILDER_CONFIGS[0].name if builder_cls.BUILDER_CONFIGS else None
with tempfile.TemporaryDirectory() as tmp_cache_dir:
builder = builder_cls(name=name, cache_dir=tmp_cache_dir)
self.assertTrue(isinstance(builder, DatasetBuilder))
def test_builder_configs(self, dataset_name):
builder_configs = self.dataset_tester.load_all_configs(dataset_name)
self.assertTrue(len(builder_configs) > 0)
if builder_configs[0] is not None:
all(self.assertTrue(isinstance(config, BuilderConfig)) for config in builder_configs)
def test_load_dataset(self, dataset_name):
configs = self.dataset_tester.load_all_configs(dataset_name)[:1]
self.dataset_tester.check_load_dataset(dataset_name, configs)
@slow
def test_load_dataset_all_configs(self, dataset_name):
configs = self.dataset_tester.load_all_configs(dataset_name)
self.dataset_tester.check_load_dataset(dataset_name, configs)
@slow
def test_load_real_dataset(self, dataset_name):
with tempfile.TemporaryDirectory() as temp_data_dir:
download_config = DownloadConfig()
download_config.download_mode = GenerateMode.FORCE_REDOWNLOAD
dataset = load_dataset(dataset_name, data_dir=temp_data_dir, download_config=download_config)
for split in dataset.keys():
self.assertTrue(len(dataset[split]) > 0)