
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


_a      :			Any					=							logging.get_logger(__name__)

_a      :			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      _UpperCAmelCase				(					_snake_case):
    __lowercase							: int  =					"""mobilenet_v1"""
    def __init__(    self						,    snake_case_=3						,    snake_case_=2_24						,    snake_case_=1.0						,    snake_case_=8						,    snake_case_="relu6"						,    snake_case_=True						,    snake_case_=0.999						,    snake_case_=0.02						,    snake_case_=0.001						,    **snake_case_						,    ):
      super().__init__(**snake_case_     )

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

      _snake_case     :						List[str]						=   num_channels
      _snake_case     :						str						=   image_size
      _snake_case     :						Optional[Any]						=   depth_multiplier
      _snake_case     :						List[Any]						=   min_depth
      _snake_case     :						Any						=   hidden_act
      _snake_case     :						Optional[int]						=   tf_padding
      _snake_case     :						Tuple						=   classifier_dropout_prob
      _snake_case     :						List[Any]						=   initializer_range
      _snake_case     :						Optional[int]						=   layer_norm_eps






class      _UpperCAmelCase				(					_snake_case):
    __lowercase							: Optional[Any]  =					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"""
from __future__ import annotations

from collections import namedtuple
def 				a__   (   a   :				float       ,     a   :				float       ,     a   :				float		):

  """simple docstring"""







  _snake_case     :						Optional[Any]						=   namedtuple("result"       ,     "name value"		)
  if (voltage, current, power).count(0		) != 1:
    raise ValueError("Only one argument must be 0"		)
  elif power < 0:
    raise ValueError(
        "Power cannot be negative in any electrical/electronics system"		)
  elif voltage == 0:
    return result("voltage"       ,     power / current		)
  elif current == 0:
    return result("current"       ,     power / voltage		)
  elif power == 0:
    return result("power"       ,     float(round(abs(voltage * current		)       ,     2		)		)		)
  else:
    raise ValueError("Exactly one argument must be 0"		)


if __name__ == "__main__":
    import doctest

    doctest.testmod()

