

'''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


lowerCAmelCase__      		=			logging.get_logger(__name__)

lowerCAmelCase__      		=			{
    '''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     lowercase_			(lowerCamelCase__   ):




  """simple docstring"""




  SCREAMING_SNAKE_CASE					:						List[Any]           =    'mobilenet_v1'






  def __init__(   self     :  Tuple      ,lowercase__     :  Tuple=3      ,lowercase__     :  List[Any]=2_2_4      ,lowercase__     :  str=1.0      ,lowercase__     :  List[str]=8      ,lowercase__     :  Tuple="relu6"      ,lowercase__     :  Optional[Any]=True      ,lowercase__     :  int=0.9_9_9      ,lowercase__     :  Optional[int]=0.0_2      ,lowercase__     :  List[str]=0.0_0_1      ,**lowercase__     :  Union[str, Any]      ,):
   super().__init__(**lowercase__    )

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

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






class     lowercase_			(lowerCamelCase__   ):




  """simple docstring"""




  SCREAMING_SNAKE_CASE					:						Dict           =    version.parse('1.11'   )






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






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






  @property
  def       SCREAMING_SNAKE_CASE   (   self     :  Optional[Any]    ):
   return 1e-4








'''simple docstring'''






from argparse import ArgumentParser

from . import BaseTransformersCLICommand


def 	_A  (					A__   ):






 """simple docstring"""



 return DownloadCommand(args.model  ,       args.cache_dir  ,       args.force  ,       args.trust_remote_code   )






class     lowercase_			(lowerCamelCase__   ):




  """simple docstring"""




  @staticmethod
  def       SCREAMING_SNAKE_CASE   (   lowercase__     :  ArgumentParser    ):
   __lowercase													=				parser.add_parser('''download'''    )
   download_parser.add_argument(
       '''--cache-dir'''      ,type=lowercase__      ,default=lowercase__      ,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=lowercase__      ,help='''Name of the model to download'''    )
   download_parser.set_defaults(func=lowercase__    )






  def __init__(   self     :  str      ,lowercase__     :  str      ,lowercase__     :  str      ,lowercase__     :  bool      ,lowercase__     :  bool    ):
   __lowercase													=				model
   __lowercase													=				cache
   __lowercase													=				force
   __lowercase													=				trust_remote_code






  def       SCREAMING_SNAKE_CASE   (   self     :  Any    ):
   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    )

