






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 : List[str]						   =       logging.get_logger(__name__)

lowerCamelCase : Union[str, Any]						   =       {
    '''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 		lowerCAmelCase     ( _lowercase			):

					'''simple docstring'''

					_A						:			List[str]									=      '''mobilenet_v1'''



					def __init__(  self				:	str		,     __a				:	Optional[Any]=3		,     __a				:	int=224		,     __a				:	int=1.0		,     __a				:	Optional[Any]=8		,     __a				:	int="relu6"		,     __a				:	Any=True		,     __a				:	str=0.999		,     __a				:	Union[str, Any]=0.02		,     __a				:	List[Any]=0.001		,     **__a				:	Tuple		,     )			->  int:


												"""simple docstring"""

												super().__init__(**A_							)

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

												__lowercase      :							Dict				=     num_channels
												__lowercase      :							Optional[int]				=     image_size
												__lowercase      :							List[str]				=     depth_multiplier
												__lowercase      :							str				=     min_depth
												__lowercase      :							Any				=     hidden_act
												__lowercase      :							Union[str, Any]				=     tf_padding
												__lowercase      :							Dict				=     classifier_dropout_prob
												__lowercase      :							Dict				=     initializer_range
												__lowercase      :							Any				=     layer_norm_eps







class 		lowerCAmelCase     ( _lowercase			):

					'''simple docstring'''

					_A						:			Any									=      version.parse('''1.11'''			)



					@property
					def       lowerCAmelCase				(  self				:	Optional[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				:	Optional[Any]							)			->  float:


												"""simple docstring"""

												return 1E-4







from argparse import ArgumentParser

from . import BaseTransformersCLICommand
def       snake_case_		(     lowerCAmelCase_       :						Dict      ):
							return DownloadCommand(args.model       ,       args.cache_dir       ,       args.force       ,       args.trust_remote_code      )



class 		lowerCAmelCase     ( __a			):

					'''simple docstring'''

					@staticmethod
					def       lowerCAmelCase				(  __a				:	ArgumentParser							)			->  Optional[Any]:


												"""simple docstring"""

												__lowercase      :							Union[str, Any]				=     parser.add_parser("""download"""							)
												download_parser.add_argument(
												    """--cache-dir"""		,     type=__a		,     default=__a		,     help="""Path to location to store the models"""							)
												download_parser.add_argument(
												    """--force"""		,     action="""store_true"""		,     help="""Force the model to be download even if already in cache-dir"""							)
												download_parser.add_argument(
												    """--trust-remote-code"""		,     action="""store_true"""		,     help="""Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you've reviewed the code as it will execute on your local machine"""		,     )
												download_parser.add_argument("""model"""		,     type=__a		,     help="""Name of the model to download"""							)
												download_parser.set_defaults(func=__a							)



					def __init__(  self				:	Dict		,     __a				:	str		,     __a				:	str		,     __a				:	bool		,     __a				:	bool							)			->  Union[str, Any]:


												"""simple docstring"""

												__lowercase      :							Dict				=     model
												__lowercase      :							List[Any]				=     cache
												__lowercase      :							Any				=     force
												__lowercase      :							Optional[int]				=     trust_remote_code



					def       lowerCAmelCase				(  self				:	str							)			->  List[str]:


												"""simple docstring"""

												from ..models.auto import AutoModel, AutoTokenizer

												AutoModel.from_pretrained(
												    self._model		,     cache_dir=self._cache		,     force_download=self._force		,     trust_remote_code=self._trust_remote_code							)
												AutoTokenizer.from_pretrained(
												    self._model		,     cache_dir=self._cache		,     force_download=self._force		,     trust_remote_code=self._trust_remote_code							)