


import re
from pathlib import Path
from unittest import TestCase

import pytest

@pytest.mark.integration
class 		__a				(    UpperCAmelCase      ):
		def      UpperCAmelCase__    (      self      ,   _SCREAMING_SNAKE_CASE						)			->	str:




									"""simple docstring"""





									with open(_SCREAMING_SNAKE_CASE      ,   encoding='utf-8'						) as input_file:
																_UpperCAmelCase					=      re.compile(R'(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)'						)
																_UpperCAmelCase					=      input_file.read()
																_UpperCAmelCase					=      regexp.search(_SCREAMING_SNAKE_CASE						)

									return match
		def      UpperCAmelCase__    (      self      ,   _SCREAMING_SNAKE_CASE						)			->	str:




									"""simple docstring"""





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

									_UpperCAmelCase					=      [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      UpperCAmelCase__    (      self						)			->	int:




									"""simple docstring"""





									_UpperCAmelCase					=      Path('./datasets'						)
									_UpperCAmelCase					=      list(dataset_paths.absolute().glob('**/*.py'						)						)

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






		def      UpperCAmelCase__    (      self						)			->	Dict:




									"""simple docstring"""





									_UpperCAmelCase					=      Path('./datasets'						)
									_UpperCAmelCase					=      list(dataset_paths.absolute().glob('**/*.py'						)						)

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




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCAmelCase__  :Any             =							{'''configuration_xglm''': ['''XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XGLMConfig''']}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__  :Optional[Any]             =							['''XGLMTokenizer''']

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__  :str             =							['''XGLMTokenizerFast''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__  :List[str]             =							[
		    '''XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''XGLMForCausalLM''',
		    '''XGLMModel''',
		    '''XGLMPreTrainedModel''',
		]


try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__  :str             =							[
		    '''FlaxXGLMForCausalLM''',
		    '''FlaxXGLMModel''',
		    '''FlaxXGLMPreTrainedModel''',
		]


try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowerCAmelCase__  :List[Any]             =							[
		    '''TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''TFXGLMForCausalLM''',
		    '''TFXGLMModel''',
		    '''TFXGLMPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_xglm import XGLMTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_xglm_fast import XGLMTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_xglm import (
				    TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFXGLMForCausalLM,
				    TFXGLMModel,
				    TFXGLMPreTrainedModel,
				)


else:
		import sys

		lowerCAmelCase__  :Any             =							_LazyModule(__name__, globals()['''__file__'''], _import_structure)
