




'''simple docstring'''


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


_snake_case   :   int     							=	logging.get_logger(__name__)

_snake_case   :   Dict     							=	{
    'google/mobilenet_v1_1.0_224': 'https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json',
    'google/mobilenet_v1_0.75_192': 'https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json',
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}

class     A					(	_a					):
					lowercase_           =       'mobilenet_v1'







					def __init__(						self :						Union[str, Any]							,    lowerCAmelCase_ :						Union[str, Any]=3							,    lowerCAmelCase_ :						int=2_24							,    lowerCAmelCase_ :						List[str]=1.0							,    lowerCAmelCase_ :						Optional[int]=8							,    lowerCAmelCase_ :						int="relu6"							,    lowerCAmelCase_ :						List[Any]=True							,    lowerCAmelCase_ :						Optional[Any]=0.9_9_9							,    lowerCAmelCase_ :						Optional[Any]=0.0_2							,    lowerCAmelCase_ :						str=0.0_0_1							,    **lowerCAmelCase_ :						Any							,    )    ->							Dict:


												"""simple docstring"""


												super().__init__(**lowerCAmelCase_      )

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

												_a			  =       num_channels
												_a			  =       image_size
												_a			  =       depth_multiplier
												_a			  =       min_depth
												_a			  =       hidden_act
												_a			  =       tf_padding
												_a			  =       classifier_dropout_prob
												_a			  =       initializer_range
												_a			  =       layer_norm_eps



class     A					(	_a					):
					lowercase_           =       version.parse('1.11'					)







					@property
					def      __lowerCAmelCase    (						self :						Union[str, Any]      )    ->							Mapping[str, Mapping[int, str]]:


												"""simple docstring"""


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







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


												"""simple docstring"""


												return 1e-4







'''simple docstring'''


from ..utils import DummyObject, requires_backends

class     A					(	metaclass=_a					):
							lowercase_           =       ['torch', 'torchsde']







							def __init__(						self :						Optional[Any]							,    *lowerCAmelCase_ :						Any							,    **lowerCAmelCase_ :						Tuple      )    ->							Dict:


														"""simple docstring"""


														requires_backends(self							,    ['''torch''', '''torchsde''']      )







							@classmethod
							def      __lowerCAmelCase    (						cls :						Dict							,    *lowerCAmelCase_ :						Optional[int]							,    **lowerCAmelCase_ :						Optional[Any]      )    ->							int:


														"""simple docstring"""


														requires_backends(cls							,    ['''torch''', '''torchsde''']      )







							@classmethod
							def      __lowerCAmelCase    (						cls :						List[str]							,    *lowerCAmelCase_ :						str							,    **lowerCAmelCase_ :						Optional[Any]      )    ->							Any:


														"""simple docstring"""


														requires_backends(cls							,    ['''torch''', '''torchsde''']      )

