






import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union

import transformers
from transformers.testing_utils import require_tf, require_torch, slow


_UpperCAmelCase			:		List[Any]   				=    logging.getLogger()
@unittest.skip('Temporarily disable the doc tests.'					)
@require_torch
@require_tf
@slow
class  lowerCAmelCase_       (				unittest.TestCase					):




							def 						__snake_case					(   self     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   Path ,							SCREAMING_SNAKE_CASE_     :   Union[str, None] = None ,							SCREAMING_SNAKE_CASE_     :   Union[List[str], None] = None ,							SCREAMING_SNAKE_CASE_     :   Union[str, List[str], None] = None ,							SCREAMING_SNAKE_CASE_     :   bool = True ,							):
											lowerCAmelCase__      			=						[file for file in os.listdir(SCREAMING_SNAKE_CASE_	) if os.path.isfile(os.path.join(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)	)]

											if identifier is not None:
															lowerCAmelCase__      			=						[file for file in files if identifier in file]

											if n_identifier is not None:
															if isinstance(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	):
																			for n_ in n_identifier:
																							lowerCAmelCase__      			=						[file for file in files if n_ not in file]
															else:
																			lowerCAmelCase__      			=						[file for file in files if n_identifier not in file]

											lowerCAmelCase__      			=						ignore_files or []
											ignore_files.append('''__init__.py'''	)
											lowerCAmelCase__      			=						[file for file in files if file not in ignore_files]

											for file in files:
															# Open all files
															print('''Testing''' ,							SCREAMING_SNAKE_CASE_	)

															if only_modules:
																			lowerCAmelCase__      			=						file.split('''.'''	)[0]
																			try:
																							lowerCAmelCase__      			=						getattr(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)
																							lowerCAmelCase__      			=						doctest.DocTestSuite(SCREAMING_SNAKE_CASE_	)
																							lowerCAmelCase__      			=						unittest.TextTestRunner().run(SCREAMING_SNAKE_CASE_	)
																							self.assertIs(len(result.failures	) ,							0	)
																			except AttributeError:
																							logger.info(f'{module_identifier} is not a module.'	)
															else:
																			lowerCAmelCase__      			=						doctest.testfile(str('''..''' / directory / file	) ,							optionflags=doctest.ELLIPSIS	)
																			self.assertIs(result.failed ,							0	)




							def 						__snake_case					(   self     :   Optional[Any]	):
											lowerCAmelCase__      			=						Path('''src/transformers'''	)
											lowerCAmelCase__      			=						'''modeling'''
											lowerCAmelCase__      			=						[
											    '''modeling_ctrl.py''',
											    '''modeling_tf_ctrl.py''',
											]
											self.analyze_directory(SCREAMING_SNAKE_CASE_ ,							identifier=SCREAMING_SNAKE_CASE_ ,							ignore_files=SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   Dict	):
											lowerCAmelCase__      			=						Path('''src/transformers'''	)
											lowerCAmelCase__      			=						'''tokenization'''
											self.analyze_directory(SCREAMING_SNAKE_CASE_ ,							identifier=SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   Tuple	):
											lowerCAmelCase__      			=						Path('''src/transformers'''	)
											lowerCAmelCase__      			=						'''configuration'''
											self.analyze_directory(SCREAMING_SNAKE_CASE_ ,							identifier=SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   Optional[Any]	):
											lowerCAmelCase__      			=						Path('''src/transformers'''	)
											lowerCAmelCase__      			=						['''configuration''', '''modeling''', '''tokenization''']
											self.analyze_directory(SCREAMING_SNAKE_CASE_ ,							n_identifier=SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   Tuple	):
											lowerCAmelCase__      			=						Path('''docs/source'''	)
											lowerCAmelCase__      			=						['''favicon.ico''']
											self.analyze_directory(SCREAMING_SNAKE_CASE_ ,							ignore_files=SCREAMING_SNAKE_CASE_ ,							only_modules=SCREAMING_SNAKE_CASE_	)













from typing import TYPE_CHECKING

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


_UpperCAmelCase			:		Optional[Any]   				=    {
    "configuration_ernie": ["ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieConfig", "ErnieOnnxConfig"],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_UpperCAmelCase			:		Any   				=    [
			    "ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "ErnieForCausalLM",
			    "ErnieForMaskedLM",
			    "ErnieForMultipleChoice",
			    "ErnieForNextSentencePrediction",
			    "ErnieForPreTraining",
			    "ErnieForQuestionAnswering",
			    "ErnieForSequenceClassification",
			    "ErnieForTokenClassification",
			    "ErnieModel",
			    "ErniePreTrainedModel",
			]

if TYPE_CHECKING:
			from .configuration_ernie import ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieConfig, ErnieOnnxConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_ernie import (
						    ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST,
						    ErnieForCausalLM,
						    ErnieForMaskedLM,
						    ErnieForMultipleChoice,
						    ErnieForNextSentencePrediction,
						    ErnieForPreTraining,
						    ErnieForQuestionAnswering,
						    ErnieForSequenceClassification,
						    ErnieForTokenClassification,
						    ErnieModel,
						    ErniePreTrainedModel,
						)

else:
			import sys

			_UpperCAmelCase			:		Dict   				=    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





