


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


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

a__			:    Any			      =		{
    "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 UpperCAmelCase_							(   SCREAMING_SNAKE_CASE__   ):
  __lowerCAmelCase      :	Any  	=      'mobilevit'


  def __init__(       self   ,__snake_case=3   ,__snake_case=2_5_6   ,__snake_case=2   ,__snake_case=[1_4_4, 1_9_2, 2_4_0]   ,__snake_case=[1_6, 3_2, 6_4, 9_6, 1_2_8, 1_6_0, 6_4_0]   ,__snake_case=4   ,__snake_case=2.0   ,__snake_case=4.0   ,__snake_case="silu"   ,__snake_case=3   ,__snake_case=3_2   ,__snake_case=0.1   ,__snake_case=0.0   ,__snake_case=0.1   ,__snake_case=0.02   ,__snake_case=1E-5   ,__snake_case=True   ,__snake_case=2_5_6   ,__snake_case=[6, 1_2, 1_8]   ,__snake_case=0.1   ,__snake_case=2_5_5   ,**__snake_case   ,):



       """simple docstring"""





       super().__init__(**a_   )

       A_					      =					num_channels
       A_					      =					image_size
       A_					      =					patch_size
       A_					      =					hidden_sizes
       A_					      =					neck_hidden_sizes
       A_					      =					num_attention_heads
       A_					      =					mlp_ratio
       A_					      =					expand_ratio
       A_					      =					hidden_act
       A_					      =					conv_kernel_size
       A_					      =					output_stride
       A_					      =					hidden_dropout_prob
       A_					      =					attention_probs_dropout_prob
       A_					      =					classifier_dropout_prob
       A_					      =					initializer_range
       A_					      =					layer_norm_eps
       A_					      =					qkv_bias

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





class UpperCAmelCase_							(   SCREAMING_SNAKE_CASE__   ):
  __lowerCAmelCase      :	Optional[Any]  	=      version.parse("""1.11"""   )


  @property
  def 	__UpperCAmelCase    (       self   ):



       """simple docstring"""





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


  @property
  def 	__UpperCAmelCase    (       self   ):



       """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 	__UpperCAmelCase    (       self   ):



       """simple docstring"""





       return 1E-4










from transformers import HfArgumentParser, PyTorchBenchmark, PyTorchBenchmarkArguments

def     UpperCAmelCase_						(						)  ->							Optional[int]:
     '''simple docstring'''


     A_					      =					HfArgumentParser(_UpperCAmelCase							)
     try:
          A_					      =					parser.parse_args_into_dataclasses()[0]
     except ValueError as e:
          A_					      =					'''Arg --no_{0} is no longer used, please use --no-{0} instead.'''
          A_					      =					''' '''.join(str(_UpperCAmelCase							).split(''' '''							)[:-1]							)
          A_					      =					''''''
          A_					      =					eval(str(_UpperCAmelCase							).split(''' '''							)[-1]							)
          A_					      =					[]
          for arg in depreciated_args:
               # arg[2:] removes '--'
               if arg[2:] in PyTorchBenchmarkArguments.deprecated_args:
                    # arg[5:] removes '--no_'
                    full_error_msg += arg_error_msg.format(arg[5:]							)
               else:
                    wrong_args.append(_UpperCAmelCase							)
          if len(_UpperCAmelCase							) > 0:
               A_					      =					full_error_msg + begin_error_msg + str(_UpperCAmelCase							)
          raise ValueError(_UpperCAmelCase							)

     A_					      =					PyTorchBenchmark(args=_UpperCAmelCase							)
     benchmark.run()


if __name__ == "__main__":
      main()



