



'''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


_UpperCamelCase							       =		logging.get_logger(__name__)

_UpperCamelCase							       =		{
    'apple/mobilevit-small': 'https://huggingface.co/apple/mobilevit-small/resolve/main/config.json',
    'apple/mobilevit-x-small': 'https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json',
    'apple/mobilevit-xx-small': 'https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json',
    'apple/deeplabv3-mobilevit-small': (
        'https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json'
    ),
    'apple/deeplabv3-mobilevit-x-small': (
        'https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json'
    ),
    'apple/deeplabv3-mobilevit-xx-small': (
        'https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json'
    ),
    # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
}






class       lowerCamelCase_					(       SCREAMING_SNAKE_CASE_  ):
  """simple docstring"""




  a_							      ="""mobilevit"""




  def __init__(				self   :			Optional[Any]    ,			_a   :			Optional[Any]=3    ,			_a   :			List[Any]=256    ,			_a   :			Union[str, Any]=2    ,			_a   :			Any=[144, 192, 240]    ,			_a   :			Dict=[16, 32, 64, 96, 128, 160, 640]    ,			_a   :			List[str]=4    ,			_a   :			Optional[int]=2.0    ,			_a   :			List[str]=4.0    ,			_a   :			List[Any]="silu"    ,			_a   :			int=3    ,			_a   :			Optional[int]=32    ,			_a   :			Union[str, Any]=0.1    ,			_a   :			Optional[int]=0.0    ,			_a   :			Dict=0.1    ,			_a   :			Dict=0.02    ,			_a   :			Dict=1e-5    ,			_a   :			Any=True    ,			_a   :			Optional[Any]=256    ,			_a   :			Optional[Any]=[6, 12, 18]    ,			_a   :			List[str]=0.1    ,			_a   :			List[Any]=255    ,			**_a   :			Optional[Any]    ,			)      ->      Dict:
    super().__init__(**_a     )

    __lowerCamelCase : Optional[int]					 =				num_channels
    __lowerCamelCase : List[str]					 =				image_size
    __lowerCamelCase : List[Any]					 =				patch_size
    __lowerCamelCase : Optional[Any]					 =				hidden_sizes
    __lowerCamelCase : Optional[int]					 =				neck_hidden_sizes
    __lowerCamelCase : List[str]					 =				num_attention_heads
    __lowerCamelCase : List[str]					 =				mlp_ratio
    __lowerCamelCase : Optional[int]					 =				expand_ratio
    __lowerCamelCase : Optional[int]					 =				hidden_act
    __lowerCamelCase : str					 =				conv_kernel_size
    __lowerCamelCase : Tuple					 =				output_stride
    __lowerCamelCase : List[Any]					 =				hidden_dropout_prob
    __lowerCamelCase : int					 =				attention_probs_dropout_prob
    __lowerCamelCase : int					 =				classifier_dropout_prob
    __lowerCamelCase : Dict					 =				initializer_range
    __lowerCamelCase : str					 =				layer_norm_eps
    __lowerCamelCase : str					 =				qkv_bias

    # decode head attributes for semantic segmentation
    __lowerCamelCase : List[str]					 =				aspp_out_channels
    __lowerCamelCase : str					 =				atrous_rates
    __lowerCamelCase : Dict					 =				aspp_dropout_prob
    __lowerCamelCase : int					 =				semantic_loss_ignore_index






class       lowerCamelCase_					(       SCREAMING_SNAKE_CASE_  ):
  """simple docstring"""




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




  @property
  def 		_lowercase  (				self   :			Union[str, Any]     )      ->      Mapping[str, Mapping[int, str]]:
    return OrderedDict([('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'})]     )




  @property
  def 		_lowercase  (				self   :			Optional[Any]     )      ->      Mapping[str, Mapping[int, 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 		_lowercase  (				self   :			List[str]     )      ->      float:
    return 1e-4











'''simple docstring'''





from __future__ import annotations

# Define the Gravitational Constant G and the function
_UpperCamelCase							       =		6.6_743e-11  # unit of G : m^3 * kg^-1 * s^-2

def  a_  (							_lowerCAmelCase ,_lowerCAmelCase ,_lowerCAmelCase ,_lowerCAmelCase )   ->   dict[str, float]:
  __lowerCamelCase : Dict					 =				mass_a * mass_a

  if (force, mass_a, mass_a, distance).count(0 ) != 1:
    raise ValueError('One and only one argument must be 0' )
  if force < 0:
    raise ValueError('Gravitational force can not be negative' )
  if distance < 0:
    raise ValueError('Distance can not be negative' )
  if mass_a < 0 or mass_a < 0:
    raise ValueError('Mass can not be negative' )
  if force == 0:
    __lowerCamelCase : Optional[Any]					 =				GRAVITATIONAL_CONSTANT * product_of_mass / (distance**2)
    return {"force": force}
  elif mass_a == 0:
    __lowerCamelCase : Tuple					 =				(force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
    return {"mass_1": mass_a}
  elif mass_a == 0:
    __lowerCamelCase : str					 =				(force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
    return {"mass_2": mass_a}
  elif distance == 0:
    __lowerCamelCase : int					 =				(GRAVITATIONAL_CONSTANT * product_of_mass / (force)) ** 0.5
    return {"distance": distance}
  raise ValueError('One and only one argument must be 0' )


# Run doctest
if __name__ == "__main__":
   import doctest

   doctest.testmod()






