
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						      =				logging.get_logger(__name__)

_A						      =				{
    "google/mobilenet_v2_1.4_224": "https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json",
    "google/mobilenet_v2_1.0_224": "https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json",
    "google/mobilenet_v2_0.75_160": "https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json",
    "google/mobilenet_v2_0.35_96": "https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json",
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}







class   lowerCamelCase	(						A_						):
     UpperCAmelCase__       :							Union[str, Any]     =	"mobilenet_v2"





     def __init__(self   :					Union[str, Any]       ,					_A   :					int=3       ,					_A   :					Tuple=2_2_4       ,					_A   :					List[Any]=1.0       ,					_A   :					List[str]=8       ,					_A   :					Union[str, Any]=8       ,					_A   :					Tuple=6       ,					_A   :					str=3_2       ,					_A   :					str=True       ,					_A   :					List[Any]=True       ,					_A   :					Any="relu6"       ,					_A   :					List[Any]=True       ,					_A   :					List[Any]=0.8       ,					_A   :					Tuple=0.02       ,					_A   :					Dict=0.0_01       ,					_A   :					Any=2_5_5       ,					**_A   :					Union[str, Any]       ,					)		->		Any:
         super().__init__(**_A     )

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

         snake_case				  =      num_channels
         snake_case				  =      image_size
         snake_case				  =      depth_multiplier
         snake_case				  =      depth_divisible_by
         snake_case				  =      min_depth
         snake_case				  =      expand_ratio
         snake_case				  =      output_stride
         snake_case				  =      first_layer_is_expansion
         snake_case				  =      finegrained_output
         snake_case				  =      hidden_act
         snake_case				  =      tf_padding
         snake_case				  =      classifier_dropout_prob
         snake_case				  =      initializer_range
         snake_case				  =      layer_norm_eps
         snake_case				  =      semantic_loss_ignore_index







class   lowerCamelCase	(						A_						):
     UpperCAmelCase__       :							List[Any]     =	version.parse("1.11"						)





     @property
     def 	UpperCAmelCase(self   :					Tuple     )		->		Union[str, Any]:
         return OrderedDict([("pixel_values", {0: "batch"})]     )





     @property
     def 	UpperCAmelCase(self   :					Any     )		->		Optional[int]:
         if self.task == "image-classification":
             return OrderedDict([("logits", {0: "batch"})]     )
         else:
             return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]     )





     @property
     def 	UpperCAmelCase(self   :					Tuple     )		->		Tuple:
         return 1E-4



def 		lowercase_    (     A__ = 1000	)							->							int:
    """simple docstring"""

    snake_case				  =      -1
    snake_case				  =      0
    for a in range(1				,	n // 3	):
        # Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
        snake_case				  =      (n * n - 2 * a * n) // (2 * n - 2 * a)
        snake_case				  =      n - a - b
        if c * c == (a * a + b * b):
            snake_case				  =      a * b * c
            if candidate >= product:
                snake_case				  =      candidate
    return product


if __name__ == "__main__":
   print(f"{solution() = }")

