





'''simple docstring'''







from typing import TYPE_CHECKING

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


lowerCAmelCase_					:    Any      	=			{'configuration_vit': ['VIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTConfig', 'ViTOnnxConfig']}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_					:    str      	=			['ViTFeatureExtractor']
					lowerCAmelCase_					:    Tuple      	=			['ViTImageProcessor']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_					:    List[Any]      	=			[
					    'VIT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'ViTForImageClassification',
					    'ViTForMaskedImageModeling',
					    'ViTModel',
					    'ViTPreTrainedModel',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_					:    List[Any]      	=			[
					    'TFViTForImageClassification',
					    'TFViTModel',
					    'TFViTPreTrainedModel',
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCAmelCase_					:    Any      	=			[
					    'FlaxViTForImageClassification',
					    'FlaxViTModel',
					    'FlaxViTPreTrainedModel',
					]

if TYPE_CHECKING:
					from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_vit import ViTFeatureExtractor
										from .image_processing_vit import ViTImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_vit import (
										    VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ViTForImageClassification,
										    ViTForMaskedImageModeling,
										    ViTModel,
										    ViTPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel


else:
					import sys

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







'''simple docstring'''







def  _lowerCamelCase				( lowercase						:      bytes						)	->	str:
				return "".join([hex(lowercase						)[2:].zfill(2						).upper() for byte in list(lowercase						)]						)






def  _lowerCamelCase				( lowercase						:      str						)	->	bytes:
				# Check data validity, following RFC3548
				# https://www.ietf.org/rfc/rfc3548.txt
				if (len(lowercase						) % 2) != 0:
								raise ValueError(
								    "Base16 encoded data is invalid:\nData does not have an even number of hex digits."						)
				# Check the character set - the standard base16 alphabet
				# is uppercase according to RFC3548 section 6
				if not set(lowercase						) <= set("0123456789ABCDEF"						):
								raise ValueError(
								    "Base16 encoded data is invalid:\nData is not uppercase hex or it contains invalid characters."						)
				# For every two hexadecimal digits (= a byte), turn it into an integer.
				# Then, string the result together into bytes, and return it.
				return bytes(int(data[i] + data[i + 1]    ,							16						) for i in range(0    ,							len(lowercase						)    ,							2						)						)


if __name__ == "__main__":
					import doctest

					doctest.testmod()
