






'''simple docstring'''







from typing import TYPE_CHECKING

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


_A     :      int   					={'''configuration_vit''': ['''VIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTConfig''', '''ViTOnnxConfig''']}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A     :      Tuple   					=['''ViTFeatureExtractor''']
			_A     :      List[Any]   					=['''ViTImageProcessor''']

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

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

try:
			if not is_flax_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_A     :      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

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









'''simple docstring'''







from math import asin, atan, cos, radians, sin, sqrt, tan

_A     :      List[str]   					=637_8137.0
_A     :      Dict   					=635_6752.31_4245
_A     :      int   					=6_378_137





def 			SCREAMING_SNAKE_CASE_	(UpperCamelCase    ,      UpperCamelCase    ,      UpperCamelCase    ,      UpperCamelCase				)				->	float:
							lowerCamelCase__ :     str	  =	(AXIS_A - AXIS_B) / AXIS_A
							lowerCamelCase__ :     Dict	  =	atan((1 - flattening) * tan(radians(UpperCamelCase				)				)				)
							lowerCamelCase__ :     Dict	  =	atan((1 - flattening) * tan(radians(UpperCamelCase				)				)				)
							lowerCamelCase__ :     Optional[Any]	  =	radians(UpperCamelCase				)
							lowerCamelCase__ :     List[Any]	  =	radians(UpperCamelCase				)
							# Equation
							lowerCamelCase__ :     Tuple	  =	sin((phi_a - phi_a) / 2				)
							lowerCamelCase__ :     List[Any]	  =	sin((lambda_a - lambda_a) / 2				)
							# Square both values
							sin_sq_phi *= sin_sq_phi
							sin_sq_lambda *= sin_sq_lambda
							lowerCamelCase__ :     Tuple	  =	sqrt(sin_sq_phi + (cos(UpperCamelCase				) * cos(UpperCamelCase				) * sin_sq_lambda)				)
							return 2 * RADIUS * asin(UpperCamelCase				)


if __name__ == "__main__":
			import doctest

			doctest.testmod()

