'''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


_A								=   logging.get_logger(__name__)

_A								=   {
    '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			):






   """simple docstring"""
   A							:       List[str]     =    '''mobilenet_v1'''
   def __init__(self       ,				_a=3       ,				_a=224       ,				_a=1.0       ,				_a=8       ,				_a="relu6"       ,				_a=True       ,				_a=0.9_99       ,				_a=0.02       ,				_a=0.0_01       ,				**_a       ,				)    ->     Any:
        super().__init__(**_a				)

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

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


class       UpperCAmelCase__  (       _snake_case			):






   """simple docstring"""
   A							:       List[Any]     =    version.parse('''1.11'''			)
   @property
   def 		_lowerCamelCase (self				)    ->     Mapping[str, Mapping[int, str]]:
        return OrderedDict([('pixel_values', {0: 'batch'})]				)
   @property
   def 		_lowerCamelCase (self				)    ->     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 		_lowerCamelCase (self				)    ->     float:
        return 1e-4





'''simple docstring'''




from __future__ import annotations

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_							):

     # preprocessing the first row
     for i in range(1  ,       len(matrix[0]							)							):
          matrix[0][i] += matrix[0][i - 1]

     # preprocessing the first column
     for i in range(1  ,       len(SCREAMING_SNAKE_CASE_							)							):
          matrix[i][0] += matrix[i - 1][0]

     # updating the path cost for current position
     for i in range(1  ,       len(SCREAMING_SNAKE_CASE_							)							):
          for j in range(1  ,       len(matrix[0]							)							):
               matrix[i][j] += min(matrix[i - 1][j]  ,       matrix[i][j - 1]							)

     return matrix[-1][-1]


if __name__ == "__main__":
 import doctest

 doctest.testmod()




