






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       							=  {
    'apple/mobilevit-small': 'https://huggingface.co/apple/mobilevit-small/resolve/main/config.json',
    'apple/mobilevit-x-small': 'https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json',
    'apple/mobilevit-xx-small': 'https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json',
    'apple/deeplabv3-mobilevit-small': (
        'https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json'
    ),
    'apple/deeplabv3-mobilevit-x-small': (
        'https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json'
    ),
    'apple/deeplabv3-mobilevit-xx-small': (
        'https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json'
    ),
    # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
}
class 							A_			(  UpperCAmelCase_	):






 '''simple docstring'''




 _SCREAMING_SNAKE_CASE							:	List[Any]       =    """mobilevit"""


 def __init__(		self							,     _A=3							,     _A=256							,     _A=2							,     _A=[144, 192, 240]							,     _A=[16, 32, 64, 96, 128, 160, 640]							,     _A=4							,     _A=2.0							,     _A=4.0							,     _A="silu"							,     _A=3							,     _A=32							,     _A=0.1							,     _A=0.0							,     _A=0.1							,     _A=0.02							,     _A=1e-5							,     _A=True							,     _A=256							,     _A=[6, 12, 18]							,     _A=0.1							,     _A=255							,     **_A							,     )       ->						Optional[int]:

     """simple docstring"""



     super().__init__(**_A)

     _UpperCAmelCase :					Tuple	     = num_channels
     _UpperCAmelCase :					Optional[int]	     = image_size
     _UpperCAmelCase :					List[Any]	     = patch_size
     _UpperCAmelCase :					Optional[Any]	     = hidden_sizes
     _UpperCAmelCase :					List[str]	     = neck_hidden_sizes
     _UpperCAmelCase :					str	     = num_attention_heads
     _UpperCAmelCase :					int	     = mlp_ratio
     _UpperCAmelCase :					Optional[Any]	     = expand_ratio
     _UpperCAmelCase :					str	     = hidden_act
     _UpperCAmelCase :					Tuple	     = conv_kernel_size
     _UpperCAmelCase :					List[Any]	     = output_stride
     _UpperCAmelCase :					Optional[Any]	     = hidden_dropout_prob
     _UpperCAmelCase :					Optional[int]	     = attention_probs_dropout_prob
     _UpperCAmelCase :					int	     = classifier_dropout_prob
     _UpperCAmelCase :					List[Any]	     = initializer_range
     _UpperCAmelCase :					Optional[int]	     = layer_norm_eps
     _UpperCAmelCase :					Optional[Any]	     = qkv_bias

     # decode head attributes for semantic segmentation
     _UpperCAmelCase :					str	     = aspp_out_channels
     _UpperCAmelCase :					Tuple	     = atrous_rates
     _UpperCAmelCase :					List[Any]	     = aspp_dropout_prob
     _UpperCAmelCase :					List[Any]	     = semantic_loss_ignore_index



class 							A_			(  UpperCAmelCase_	):






 '''simple docstring'''




 _SCREAMING_SNAKE_CASE							:	Dict       =    version.parse("1.11"	)


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

     """simple docstring"""



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


 @property
 def        snake_case__ (		self)       ->						int:

     """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        snake_case__ (		self)       ->						Union[str, Any]:

     """simple docstring"""



     return 1e-4











def 			lowerCamelCase_		(					lowerCAmelCase:		list			,							lowerCAmelCase:		list )->						list:
  _snake_case      : int														=		len(lowerCAmelCase )
  _snake_case      : int														=		len(lowerCAmelCase )
  _snake_case      : int														=		(
      first_input_list_length
      if first_input_list_length > second_input_list_length
      else second_input_list_length
  )
  _snake_case      : list														=		[]
  for char_count in range(lowerCAmelCase ):
    if char_count < first_input_list_length:
      output_result_list.append(first_input_list[char_count] )
    if char_count < second_input_list_length:
      output_result_list.append(second_input_list[char_count] )

  return output_result_list


if __name__ == "__main__":
      print(alternative_list_arrange(["""A""", """B""", """C"""], [1, 2, 3, 4, 5]), end=""" """)




