






'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


__lowerCamelCase   :					List[str]   							=					{'''configuration_deit''': ['''DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeiTConfig''', '''DeiTOnnxConfig''']}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase   :					Tuple   							=					['''DeiTFeatureExtractor''']
		__lowerCamelCase   :					Optional[Any]   							=					['''DeiTImageProcessor''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase   :					Optional[Any]   							=					[
		    '''DEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''DeiTForImageClassification''',
		    '''DeiTForImageClassificationWithTeacher''',
		    '''DeiTForMaskedImageModeling''',
		    '''DeiTModel''',
		    '''DeiTPreTrainedModel''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase   :					Dict   							=					[
		    '''TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''TFDeiTForImageClassification''',
		    '''TFDeiTForImageClassificationWithTeacher''',
		    '''TFDeiTForMaskedImageModeling''',
		    '''TFDeiTModel''',
		    '''TFDeiTPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_deit import DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, DeiTConfig, DeiTOnnxConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_deit import DeiTFeatureExtractor
				from .image_processing_deit import DeiTImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_deit import (
				    DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    DeiTForImageClassification,
				    DeiTForImageClassificationWithTeacher,
				    DeiTForMaskedImageModeling,
				    DeiTModel,
				    DeiTPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_deit import (
				    TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFDeiTForImageClassification,
				    TFDeiTForImageClassificationWithTeacher,
				    TFDeiTForMaskedImageModeling,
				    TFDeiTModel,
				    TFDeiTPreTrainedModel,
				)


else:
		import sys

		__lowerCamelCase   :					Optional[int]   							=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)












'''simple docstring'''




import inspect
import re

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__lowerCamelCase   :					Any   							=					'''src/transformers'''


# This is to make sure the transformers module imported is the one in the repo.
__lowerCamelCase   :					List[str]   							=					direct_transformers_import(PATH_TO_TRANSFORMERS)

__lowerCamelCase   :					Optional[Any]   							=					transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
__lowerCamelCase   :					Union[str, Any]   							=					re.compile(R'''\[(.+?)\]\((https://huggingface\.co/.+?)\)''')


__lowerCamelCase   :					Any   							=					{
    '''DecisionTransformerConfig''',
    '''EncoderDecoderConfig''',
    '''MusicgenConfig''',
    '''RagConfig''',
    '''SpeechEncoderDecoderConfig''',
    '''TimmBackboneConfig''',
    '''VisionEncoderDecoderConfig''',
    '''VisionTextDualEncoderConfig''',
    '''LlamaConfig''',
}

def 	__UpperCAmelCase       ( __magic_name__						)->    List[Any]:



			"""simple docstring"""



			snake_case_				:					Tuple   =       None

			# source code of `config_class`
			snake_case_				:					List[Any]   =       inspect.getsource(__magic_name__						)
			snake_case_				:					List[str]   =       _re_checkpoint.findall(__magic_name__						)

			# Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
			# For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
			for ckpt_name, ckpt_link in checkpoints:
						# allow the link to end with `/`
						if ckpt_link.endswith("/"						):
									snake_case_				:					Optional[Any]   =       ckpt_link[:-1]

						# verify the checkpoint name corresponds to the checkpoint link
						snake_case_				:					str   =       F'''https://huggingface.co/{ckpt_name}'''
						if ckpt_link == ckpt_link_from_name:
									snake_case_				:					Dict   =       ckpt_name
									break

			return checkpoint

def 	__UpperCAmelCase       ( )->    Dict:



			"""simple docstring"""



			snake_case_				:					Optional[int]   =       []

			for config_class in list(CONFIG_MAPPING.values()						):
						# Skip deprecated models
						if "models.deprecated" in config_class.__module__:
									continue
						snake_case_				:					str   =       get_checkpoint_from_config_class(__magic_name__						)

						snake_case_				:					Union[str, Any]   =       config_class.__name__
						if checkpoint is None and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
									configs_without_checkpoint.append(__magic_name__						)

			if len(__magic_name__						) > 0:
						snake_case_				:					Tuple   =       "\n".join(sorted(__magic_name__						)						)
						raise ValueError(F'''The following configurations don\'t contain any valid checkpoint:\n{message}'''						)


if __name__ == "__main__":
		check_config_docstrings_have_checkpoints()




