





from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_SCREAMING_SNAKE_CASE 		=						logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE 		=						{
    """microsoft/beit-base-patch16-224-pt22k""": (
        """https://huggingface.co/microsoft/beit-base-patch16-224-pt22k/resolve/main/config.json"""
    ),
    # See all BEiT models at https://huggingface.co/models?filter=beit
}
class SCREAMING_SNAKE_CASE_  (   snake_case_   ):
						__magic_name__:     Any	 =    "beit"






						def __init__( self : int						,				_A : Optional[int]=8192						,				_A : Optional[Any]=768						,				_A : Dict=12						,				_A : int=12						,				_A : List[Any]=3072						,				_A : Optional[int]="gelu"						,				_A : Optional[Any]=0.0						,				_A : Union[str, Any]=0.0						,				_A : Tuple=0.0_2						,				_A : Optional[int]=1E-12						,				_A : Union[str, Any]=224						,				_A : int=16						,				_A : str=3						,				_A : Optional[Any]=False						,				_A : Any=False						,				_A : Optional[Any]=False						,				_A : List[str]=False						,				_A : Optional[int]=0.1						,				_A : Optional[int]=0.1						,				_A : List[str]=True						,				_A : List[Any]=[3, 5, 7, 11]						,				_A : Any=[1, 2, 3, 6]						,				_A : Dict=True						,				_A : int=0.4						,				_A : str=256						,				_A : int=1						,				_A : Dict=False						,				_A : Optional[Any]=255						,				**_A : List[Any]						,				)							->      str:







							"""simple docstring"""


							super().__init__(**_SCREAMING_SNAKE_CASE		)

							snake_case_						:     Dict     =		vocab_size
							snake_case_						:     Any     =		hidden_size
							snake_case_						:     Tuple     =		num_hidden_layers
							snake_case_						:     Union[str, Any]     =		num_attention_heads
							snake_case_						:     List[Any]     =		intermediate_size
							snake_case_						:     List[Any]     =		hidden_act
							snake_case_						:     Optional[int]     =		hidden_dropout_prob
							snake_case_						:     Any     =		attention_probs_dropout_prob
							snake_case_						:     str     =		initializer_range
							snake_case_						:     Any     =		layer_norm_eps

							snake_case_						:     Tuple     =		image_size
							snake_case_						:     List[str]     =		patch_size
							snake_case_						:     Dict     =		num_channels
							snake_case_						:     Optional[Any]     =		use_mask_token
							snake_case_						:     str     =		use_absolute_position_embeddings
							snake_case_						:     List[str]     =		use_relative_position_bias
							snake_case_						:     Optional[int]     =		use_shared_relative_position_bias
							snake_case_						:     List[str]     =		layer_scale_init_value
							snake_case_						:     Union[str, Any]     =		drop_path_rate
							snake_case_						:     Union[str, Any]     =		use_mean_pooling
							# decode head attributes (semantic segmentation)
							snake_case_						:     Optional[Any]     =		out_indices
							snake_case_						:     Optional[Any]     =		pool_scales
							# auxiliary head attributes (semantic segmentation)
							snake_case_						:     Tuple     =		use_auxiliary_head
							snake_case_						:     str     =		auxiliary_loss_weight
							snake_case_						:     Union[str, Any]     =		auxiliary_channels
							snake_case_						:     List[Any]     =		auxiliary_num_convs
							snake_case_						:     Tuple     =		auxiliary_concat_input
							snake_case_						:     int     =		semantic_loss_ignore_index
class SCREAMING_SNAKE_CASE_  (   snake_case_   ):
						__magic_name__:     str	 =    version.parse("1.11"   )






						@property
						def UpperCAmelCase_			( self : Optional[int]		)							->      Mapping[str, Mapping[int, str]]:







							"""simple docstring"""


							return OrderedDict(
							    [
							        ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
							    ]		)






						@property
						def UpperCAmelCase_			( self : List[Any]		)							->      float:







							"""simple docstring"""


							return 1E-4








def 							SCREAMING_SNAKE_CASE__  (      __a = 60_08_51_47_51_43				):

	try:
		snake_case_						:     Optional[Any]     =		int(__a				)
	except (TypeError, ValueError):
		raise TypeError('Parameter n must be int or castable to int.'				)
	if n <= 0:
		raise ValueError('Parameter n must be greater than or equal to one.'				)
	snake_case_						:     Any     =		2
	snake_case_						:     Any     =		0
	if n == 2:
		return 2
	while n > 2:
		while n % i != 0:
			i += 1
		snake_case_						:     Tuple     =		i
		while n % i == 0:
			snake_case_						:     List[str]     =		n // i
		i += 1
	return int(__a				)


if __name__ == "__main__":
						print(F'''{solution() = }''')

