



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 	lowerCamelCase_    ( _A						):






      '''simple docstring'''
      a__   =  "beit"







      def __init__(	self      :			Dict	,	__lowerCamelCase      :			List[str]=81_92	,	__lowerCamelCase      :			List[Any]=7_68	,	__lowerCamelCase      :			int=12	,	__lowerCamelCase      :			Tuple=12	,	__lowerCamelCase      :			Optional[Any]=30_72	,	__lowerCamelCase      :			Optional[Any]="gelu"	,	__lowerCamelCase      :			Tuple=0.0	,	__lowerCamelCase      :			Dict=0.0	,	__lowerCamelCase      :			Optional[int]=0.02	,	__lowerCamelCase      :			int=1e-12	,	__lowerCamelCase      :			List[str]=2_24	,	__lowerCamelCase      :			str=16	,	__lowerCamelCase      :			Optional[int]=3	,	__lowerCamelCase      :			Dict=False	,	__lowerCamelCase      :			Union[str, Any]=False	,	__lowerCamelCase      :			Optional[Any]=False	,	__lowerCamelCase      :			Any=False	,	__lowerCamelCase      :			str=0.1	,	__lowerCamelCase      :			str=0.1	,	__lowerCamelCase      :			int=True	,	__lowerCamelCase      :			Any=[3, 5, 7, 11]	,	__lowerCamelCase      :			Optional[int]=[1, 2, 3, 6]	,	__lowerCamelCase      :			Dict=True	,	__lowerCamelCase      :			Dict=0.4	,	__lowerCamelCase      :			List[str]=2_56	,	__lowerCamelCase      :			Optional[Any]=1	,	__lowerCamelCase      :			List[Any]=False	,	__lowerCamelCase      :			Any=2_55	,	**__lowerCamelCase      :			Union[str, Any]	,	)      ->				Optional[Any]:
         super().__init__(**__lowerCamelCase )

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

         A							:					Union[str, Any]              =						image_size
         A							:					Union[str, Any]              =						patch_size
         A							:					int              =						num_channels
         A							:					str              =						use_mask_token
         A							:					Any              =						use_absolute_position_embeddings
         A							:					str              =						use_relative_position_bias
         A							:					Dict              =						use_shared_relative_position_bias
         A							:					Optional[Any]              =						layer_scale_init_value
         A							:					str              =						drop_path_rate
         A							:					Any              =						use_mean_pooling
         # decode head attributes (semantic segmentation)
         A							:					List[str]              =						out_indices
         A							:					Dict              =						pool_scales
         # auxiliary head attributes (semantic segmentation)
         A							:					Dict              =						use_auxiliary_head
         A							:					Any              =						auxiliary_loss_weight
         A							:					Optional[int]              =						auxiliary_channels
         A							:					int              =						auxiliary_num_convs
         A							:					str              =						auxiliary_concat_input
         A							:					int              =						semantic_loss_ignore_index







class 	lowerCamelCase_    ( _A						):






      '''simple docstring'''
      a__   =  version.parse("1.11"						)







      @property
      def 			SCREAMING_SNAKE_CASE__		(	self      :			str )      ->				Mapping[str, Mapping[int, str]]:
         return OrderedDict(
             [
                 ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
             ] )







      @property
      def 			SCREAMING_SNAKE_CASE__		(	self      :			Any )      ->				float:
         return 1e-4




from sympy import diff, lambdify, symbols
from sympy.functions import *  # noqa: F403




def 	UpperCAmelCase   (						_lowerCamelCase ,    _lowerCamelCase ,    _lowerCamelCase = "x" ,    _lowerCamelCase = 10**-10 ,    _lowerCamelCase = 1 ,    ):
			A							:					str              =						symbols(_lowerCamelCase    )
			A							:					int              =						lambdify(_lowerCamelCase ,    _lowerCamelCase    )
			A							:					List[str]              =						lambdify(_lowerCamelCase ,    diff(_lowerCamelCase ,    _lowerCamelCase    )    )

			A							:					Optional[int]              =						starting_point

			while True:
						if diff_function(_lowerCamelCase    ) != 0:
									A							:					Optional[Any]              =						prev_guess - multiplicity * func(_lowerCamelCase    ) / diff_function(
									    _lowerCamelCase    )
						else:
									raise ZeroDivisionError("Could not find root"    ) from None

						# Precision is checked by comparing the difference of consecutive guesses
						if abs(next_guess - prev_guess    ) < precision:
									return next_guess

						A							:					int              =						next_guess


# Let's Execute
if __name__ == "__main__":
							# Find root of trigonometric function
							# Find value of pi
							print(F"""The root of sin(x) = 0 is {newton_raphson('sin(x)', 2)}""")

							# Find root of polynomial
							# Find fourth Root of 5
							print(F"""The root of x**4 - 5 = 0 is {newton_raphson('x**4 -5', 0.4 +5j)}""")

							# Find value of e
							print(
							    """The root of log(y) - 1 = 0 is """,
							    F"""{newton_raphson('log(y) - 1', 2, variable='y')}""",
							)

							# Exponential Roots
							print(
							    """The root of exp(x) - 1 = 0 is""",
							    F"""{newton_raphson('exp(x) - 1', 10, precision=0.005)}""",
							)

							# Find root of cos(x)
							print(F"""The root of cos(x) = 0 is {newton_raphson('cos(x)', 0)}""")