

import re
from pathlib import Path
from unittest import TestCase

import pytest







@pytest.mark.integration
class 	__A    (				_UpperCamelCase							):


		"""simple docstring"""




		def 		A__					(				self	,       __snake_case):

			with open(__a	,       encoding='utf-8') as input_file:
				_UpperCamelCase   :		Dict			=						re.compile(r'(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)')
				_UpperCamelCase   :		Dict			=						input_file.read()
				_UpperCamelCase   :		List[str]			=						regexp.search(__a)

			return match


		def 		A__					(				self	,       __snake_case):

			with open(__a	,       encoding='utf-8') as input_file:
				_UpperCamelCase   :		str			=						re.compile(r'#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()'	,       re.DOTALL)
				_UpperCamelCase   :		Optional[int]			=						input_file.read()
				# use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
				_UpperCamelCase   :		int			=						regexp.finditer(__a)

			_UpperCamelCase   :		Tuple			=						[match for match in matches if match is not None and match.group(1) is not None]
			return matches[0] if matches else None


		def 		A__					(				self):
			_UpperCamelCase   :		Dict			=						Path('./datasets')
			_UpperCamelCase   :		List[str]			=						list(dataset_paths.absolute().glob('**/*.py'))

			for dataset in dataset_files:
				if self._no_encoding_on_file_open(str(__a)):
					raise AssertionError(f'''open(...) must use utf-8 encoding in {dataset}''')






		def 		A__					(				self):
			_UpperCamelCase   :		List[str]			=						Path('./datasets')
			_UpperCamelCase   :		str			=						list(dataset_paths.absolute().glob('**/*.py'))

			for dataset in dataset_files:
				if self._no_print_statements(str(__a)):
					raise AssertionError(f'''print statement found in {dataset}. Use datasets.logger/logging instead.''')







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCAmelCase__								=		{
    """configuration_canine""": ["""CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CanineConfig"""],
    """tokenization_canine""": ["""CanineTokenizer"""],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase__								=		[
							    """CANINE_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """CanineForMultipleChoice""",
							    """CanineForQuestionAnswering""",
							    """CanineForSequenceClassification""",
							    """CanineForTokenClassification""",
							    """CanineLayer""",
							    """CanineModel""",
							    """CaninePreTrainedModel""",
							    """load_tf_weights_in_canine""",
							]


if TYPE_CHECKING:
							from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
							from .tokenization_canine import CanineTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_canine import (
														    CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
														    CanineForMultipleChoice,
														    CanineForQuestionAnswering,
														    CanineForSequenceClassification,
														    CanineForTokenClassification,
														    CanineLayer,
														    CanineModel,
														    CaninePreTrainedModel,
														    load_tf_weights_in_canine,
														)


else:
							import sys

							lowerCAmelCase__								=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




