


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


lowerCAmelCase__			:      int								=logging.get_logger(__name__)

lowerCAmelCase__			:      Optional[int]								={
    '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 	__lowercase    (__SCREAMING_SNAKE_CASE  ):





							"""simple docstring"""







							_UpperCAmelCase      =						"""mobilenet_v2"""






							def __init__(      self			,						lowerCAmelCase__=3			,						lowerCAmelCase__=2_2_4			,						lowerCAmelCase__=1.0			,						lowerCAmelCase__=8			,						lowerCAmelCase__=8			,						lowerCAmelCase__=6			,						lowerCAmelCase__=3_2			,						lowerCAmelCase__=True			,						lowerCAmelCase__=True			,						lowerCAmelCase__="relu6"			,						lowerCAmelCase__=True			,						lowerCAmelCase__=0.8			,						lowerCAmelCase__=0.02			,						lowerCAmelCase__=0.001			,						lowerCAmelCase__=2_5_5			,						**lowerCAmelCase__			,						):





										"""simple docstring"""




										super().__init__(**lowerCAmelCase__       )

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

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







class 	__lowercase    (__SCREAMING_SNAKE_CASE  ):





							"""simple docstring"""







							_UpperCAmelCase      =						version.parse("""1.11"""  )






							@property
							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										return OrderedDict([('pixel_values', {0: 'batch'})]       )






							@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









'''simple docstring'''
from __future__ import annotations

from typing import Any







def       a_				(	UpperCamelCase_ ):
							create_state_space_tree(UpperCamelCase_						,  []						,  0 )







def       a_				(	UpperCamelCase_						,  UpperCamelCase_						,  UpperCamelCase_ ):

							if index == len(UpperCamelCase_ ):
														print(UpperCamelCase_ )
														return

							create_state_space_tree(UpperCamelCase_						,  UpperCamelCase_						,  index + 1 )
							current_subsequence.append(sequence[index] )
							create_state_space_tree(UpperCamelCase_						,  UpperCamelCase_						,  index + 1 )
							current_subsequence.pop()


if __name__ == "__main__":
							__SCREAMING_SNAKE_CASE					:				list[Any]									=		[3, 1, 2, 4]
							generate_all_subsequences(seq)

							seq.clear()
							seq.extend(['''A''', '''B''', '''C'''])
							generate_all_subsequences(seq)





