



'''simple docstring'''

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


__lowerCAmelCase									=   logging.getLogger()

@unittest.skip('Temporarily disable the doc tests.'   )
@require_torch
@require_tf
@slow
class 	__magic_name__						(    unittest.TestCase   ):







							def 							__lowercase			(							self					:       str	,_UpperCAmelCase					:       Path	,_UpperCAmelCase					:       Union[str, None] = None	,_UpperCAmelCase					:       Union[List[str], None] = None	,_UpperCAmelCase					:       Union[str, List[str], None] = None	,_UpperCAmelCase					:       bool = True	,):
									_a     :      Dict        =							[file for file in os.listdir(_UpperCAmelCase		) if os.path.isfile(os.path.join(_UpperCAmelCase	,_UpperCAmelCase		)		)]

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

									if n_identifier is not None:
											if isinstance(_UpperCAmelCase	,_UpperCAmelCase		):
													for n_ in n_identifier:
															_a     :      int        =							[file for file in files if n_ not in file]
											else:
													_a     :      Optional[Any]        =							[file for file in files if n_identifier not in file]

									_a     :      Dict        =							ignore_files or []
									ignore_files.append('__init__.py'		)
									_a     :      List[str]        =							[file for file in files if file not in ignore_files]

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

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







							def 							__lowercase			(							self					:       Union[str, Any]		):
									_a     :      Optional[Any]        =							Path('src/transformers'		)
									_a     :      Optional[Any]        =							'modeling'
									_a     :      Union[str, Any]        =							[
									    'modeling_ctrl.py',
									    'modeling_tf_ctrl.py',
									]
									self.analyze_directory(_UpperCAmelCase	,identifier=_UpperCAmelCase	,ignore_files=_UpperCAmelCase		)







							def 							__lowercase			(							self					:       int		):
									_a     :      str        =							Path('src/transformers'		)
									_a     :      List[str]        =							'tokenization'
									self.analyze_directory(_UpperCAmelCase	,identifier=_UpperCAmelCase		)







							def 							__lowercase			(							self					:       int		):
									_a     :      Any        =							Path('src/transformers'		)
									_a     :      str        =							'configuration'
									self.analyze_directory(_UpperCAmelCase	,identifier=_UpperCAmelCase		)







							def 							__lowercase			(							self					:       Dict		):
									_a     :      Tuple        =							Path('src/transformers'		)
									_a     :      Optional[int]        =							['configuration', 'modeling', 'tokenization']
									self.analyze_directory(_UpperCAmelCase	,n_identifier=_UpperCAmelCase		)







							def 							__lowercase			(							self					:       Optional[Any]		):
									_a     :      Union[str, Any]        =							Path('docs/source'		)
									_a     :      List[str]        =							['favicon.ico']
									self.analyze_directory(_UpperCAmelCase	,ignore_files=_UpperCAmelCase	,only_modules=_UpperCAmelCase		)









'''simple docstring'''

from typing import TYPE_CHECKING

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


__lowerCAmelCase									=   {'''configuration_swin''': ['''SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SwinConfig''', '''SwinOnnxConfig''']}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase									=   [
							    '''SWIN_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''SwinForImageClassification''',
							    '''SwinForMaskedImageModeling''',
							    '''SwinModel''',
							    '''SwinPreTrainedModel''',
							    '''SwinBackbone''',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase									=   [
							    '''TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''TFSwinForImageClassification''',
							    '''TFSwinForMaskedImageModeling''',
							    '''TFSwinModel''',
							    '''TFSwinPreTrainedModel''',
							]

if TYPE_CHECKING:
							from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_swin import (
														    SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
														    SwinBackbone,
														    SwinForImageClassification,
														    SwinForMaskedImageModeling,
														    SwinModel,
														    SwinPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_swin import (
														    TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFSwinForImageClassification,
														    TFSwinForMaskedImageModeling,
														    TFSwinModel,
														    TFSwinPreTrainedModel,
														)

else:
							import sys

							__lowerCAmelCase									=   _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




