
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						       =						{
    'google/mobilenet_v2_1.4_224': 'https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json',
    'google/mobilenet_v2_1.0_224': 'https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json',
    'google/mobilenet_v2_0.75_160': 'https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json',
    'google/mobilenet_v2_0.35_96': 'https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json',
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}





class 							lowerCAmelCase_						(    __A							):




			'''simple docstring'''


			_lowercase      =							'mobilenet_v2'







			def __init__(	self    ,							__UpperCAmelCase=3    ,							__UpperCAmelCase=224    ,							__UpperCAmelCase=1.0    ,							__UpperCAmelCase=8    ,							__UpperCAmelCase=8    ,							__UpperCAmelCase=6    ,							__UpperCAmelCase=32    ,							__UpperCAmelCase=True    ,							__UpperCAmelCase=True    ,							__UpperCAmelCase="relu6"    ,							__UpperCAmelCase=True    ,							__UpperCAmelCase=0.8    ,							__UpperCAmelCase=0.02    ,							__UpperCAmelCase=0.001    ,							__UpperCAmelCase=255    ,							**__UpperCAmelCase    ,							):
										super().__init__(**__UpperCAmelCase  )

										if depth_multiplier <= 0:
																	raise ValueError('depth_multiplier must be greater than zero.'  )

										SCREAMING_SNAKE_CASE_	:							Union[str, Any]											=num_channels
										SCREAMING_SNAKE_CASE_	:							List[Any]											=image_size
										SCREAMING_SNAKE_CASE_	:							Tuple											=depth_multiplier
										SCREAMING_SNAKE_CASE_	:							List[str]											=depth_divisible_by
										SCREAMING_SNAKE_CASE_	:							Union[str, Any]											=min_depth
										SCREAMING_SNAKE_CASE_	:							str											=expand_ratio
										SCREAMING_SNAKE_CASE_	:							List[str]											=output_stride
										SCREAMING_SNAKE_CASE_	:							str											=first_layer_is_expansion
										SCREAMING_SNAKE_CASE_	:							str											=finegrained_output
										SCREAMING_SNAKE_CASE_	:							List[Any]											=hidden_act
										SCREAMING_SNAKE_CASE_	:							List[Any]											=tf_padding
										SCREAMING_SNAKE_CASE_	:							str											=classifier_dropout_prob
										SCREAMING_SNAKE_CASE_	:							List[Any]											=initializer_range
										SCREAMING_SNAKE_CASE_	:							str											=layer_norm_eps
										SCREAMING_SNAKE_CASE_	:							Dict											=semantic_loss_ignore_index





class 							lowerCAmelCase_						(    __A							):




			'''simple docstring'''


			_lowercase      =							version.parse('1.11'							)







			@property
			def      __lowerCamelCase    (	self  ):
										return OrderedDict([('pixel_values', {0: 'batch'})]  )







			@property
			def      __lowerCamelCase    (	self  ):





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







			@property
			def      __lowerCamelCase    (	self  ):
										return 1E-4









'''simple docstring'''


def 		_lowercase (SCREAMING_SNAKE_CASE       ,					SCREAMING_SNAKE_CASE = " "							):




     '''simple docstring'''





     __A	:       List[str]      =							[]

     __A	:       Tuple      =							0
     for index, char in enumerate(SCREAMING_SNAKE_CASE							):
          if char == separator:
               split_words.append(string[last_index:index]							)
               __A	:       Union[str, Any]      =							index + 1
          elif index + 1 == len(SCREAMING_SNAKE_CASE							):
               split_words.append(string[last_index : index + 1]							)
     return split_words


if __name__ == "__main__":
      from doctest import testmod

      testmod()

