




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_    :       List[Any]       =							logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_    :       Tuple       =							{
    '''apple/mobilevitv2-1.0''': '''https://huggingface.co/apple/mobilevitv2-1.0/resolve/main/config.json''',
}







class 		__UpperCAmelCase(		lowercase__			):





     """simple docstring"""



     __UpperCAmelCase						:			Optional[int]							=     """mobilevitv2"""

     def __init__(   self			:							str    ,					A			:							Optional[Any]=3    ,					A			:							Any=2_56    ,					A			:							Optional[int]=2    ,					A			:							str=2.0    ,					A			:							Tuple="swish"    ,					A			:							str=3    ,					A			:							int=32    ,					A			:							int=0.1    ,					A			:							List[Any]=0.0_2    ,					A			:							Union[str, Any]=1E-5    ,					A			:							str=5_12    ,					A			:							Union[str, Any]=[6, 12, 18]    ,					A			:							Optional[Any]=0.1    ,					A			:							List[Any]=2_55    ,					A			:							int=[2, 4, 3]    ,					A			:							Any=[1_28, 1_92, 2_56]    ,					A			:							int=1.0    ,					A			:							Union[str, Any]=2    ,					A			:							Optional[int]=0.0    ,					A			:							Union[str, Any]=0.0    ,					**A			:							List[Any]    ,					)      ->      Tuple:






         """simple docstring"""
         super().__init__(**A     )

         a__  			=							num_channels
         a__  			=							image_size
         a__  			=							patch_size
         a__  			=							expand_ratio
         a__  			=							hidden_act
         a__  			=							conv_kernel_size
         a__  			=							output_stride
         a__  			=							initializer_range
         a__  			=							layer_norm_eps
         a__  			=							n_attn_blocks
         a__  			=							base_attn_unit_dims
         a__  			=							width_multiplier
         a__  			=							ffn_multiplier
         a__  			=							ffn_dropout
         a__  			=							attn_dropout
         a__  			=							classifier_dropout_prob

         # decode head attributes for semantic segmentation
         a__  			=							aspp_out_channels
         a__  			=							atrous_rates
         a__  			=							aspp_dropout_prob
         a__  			=							semantic_loss_ignore_index







class 		__UpperCAmelCase(		lowercase__			):





     """simple docstring"""



     __UpperCAmelCase						:			List[Any]							=     version.parse("""1.11"""			)

     @property
     def 					__SCREAMING_SNAKE_CASE		(   self			:							List[str]     )      ->      Mapping[str, Mapping[int, str]]:






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

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






         """simple docstring"""
         if self.task == "image-classification":
             return OrderedDict([("""logits""", {0: """batch"""})]     )
         else:
             return OrderedDict([("""last_hidden_state""", {0: """batch"""}), ("""pooler_output""", {0: """batch"""})]     )






     @property
     def 					__SCREAMING_SNAKE_CASE		(   self			:							str     )      ->      float:






         """simple docstring"""
         return 1E-4












from __future__ import annotations

import sys
def 							__lowerCAmelCase			(UpperCAmelCase_		):
    if n < 0:
        raise ValueError("""Negative arguments are not supported"""		)
    return _fib(UpperCAmelCase_		)[0]
def 							__lowerCAmelCase			(UpperCAmelCase_		):
    if n == 0:  # (F(0), F(1))
        return (0, 1)

    # F(2n) = F(n)[2F(n+1) − F(n)]
    # F(2n+1) = F(n+1)^2+F(n)^2
    a__			,		a__  			=							_fib(n // 2		)
    a__  			=							a * (b * 2 - a)
    a__  			=							a * a + b * b
    return (d, c + d) if n % 2 else (c, d)


if __name__ == "__main__":
 SCREAMING_SNAKE_CASE_    :       Dict       =							int(sys.argv[1])
 print(F"fibonacci({n}) is {fibonacci(n)}")






