



from collections import OrderedDict
from typing import List, 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/efficientnet-b7""": """https://huggingface.co/google/efficientnet-b7/resolve/main/config.json""",
}






class    SCREAMING_SNAKE_CASE			(							lowerCamelCase__					):
							__lowerCamelCase	:	Tuple    ='efficientnet'





							def __init__(   self		:		Union[str, Any]      ,				__lowercase		:		int = 3      ,				__lowercase		:		int = 600      ,				__lowercase		:		float = 2.0      ,				__lowercase		:		float = 3.1      ,				__lowercase		:		int = 8      ,				__lowercase		:		List[int] = [3, 3, 5, 3, 5, 5, 3]      ,				__lowercase		:		List[int] = [32, 16, 24, 40, 80, 112, 192]      ,				__lowercase		:		List[int] = [16, 24, 40, 80, 112, 192, 320]      ,				__lowercase		:		List[int] = []      ,				__lowercase		:		List[int] = [1, 2, 2, 2, 1, 2, 1]      ,				__lowercase		:		List[int] = [1, 2, 2, 3, 3, 4, 1]      ,				__lowercase		:		List[int] = [1, 6, 6, 6, 6, 6, 6]      ,				__lowercase		:		float = 0.25      ,				__lowercase		:		str = "swish"      ,				__lowercase		:		int = 2560      ,				__lowercase		:		str = "mean"      ,				__lowercase		:		float = 0.02      ,				__lowercase		:		float = 0.001      ,				__lowercase		:		float = 0.99      ,				__lowercase		:		float = 0.5      ,				__lowercase		:		float = 0.2      ,				**__lowercase		:		List[Any]      ,				):

											'''simple docstring'''
											super().__init__(**__lowercase	)

											__a       =		num_channels
											__a       =		image_size
											__a       =		width_coefficient
											__a       =		depth_coefficient
											__a       =		depth_divisor
											__a       =		kernel_sizes
											__a       =		in_channels
											__a       =		out_channels
											__a       =		depthwise_padding
											__a       =		strides
											__a       =		num_block_repeats
											__a       =		expand_ratios
											__a       =		squeeze_expansion_ratio
											__a       =		hidden_act
											__a       =		hidden_dim
											__a       =		pooling_type
											__a       =		initializer_range
											__a       =		batch_norm_eps
											__a       =		batch_norm_momentum
											__a       =		dropout_rate
											__a       =		drop_connect_rate
											__a       =		sum(__lowercase	) * 4






class    SCREAMING_SNAKE_CASE			(							lowerCamelCase__					):
							__lowerCamelCase	:	Optional[Any]    =version.parse('1.11'					)





							@property
							def 						UpperCamelCase_					(   self		:		Tuple	):

											'''simple docstring'''
											return OrderedDict(
											    [
											        ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
											    ]	)







							@property
							def 						UpperCamelCase_					(   self		:		Any	):

											'''simple docstring'''
											return 1E-5





import os

def   lowerCAmelCase__						(							):
				"""simple docstring"""







				__a       =		os.path.dirname(os.path.realpath(_SCREAMING_SNAKE_CASE    )    )
				__a       =		os.path.join(_SCREAMING_SNAKE_CASE				,     """triangle.txt"""    )

				with open(_SCREAMING_SNAKE_CASE    ) as f:
								__a       =		f.readlines()

				__a       =		[]
				for line in triangle:
								__a       =		[]
								for number in line.strip().split(""" """    ):
												numbers_from_line.append(int(_SCREAMING_SNAKE_CASE    )    )
								a.append(_SCREAMING_SNAKE_CASE    )

				for i in range(1				,     len(_SCREAMING_SNAKE_CASE    )    ):
								for j in range(len(a[i]    )    ):
												__a       =		a[i - 1][j] if j != len(a[i - 1]    ) else 0
												__a       =		a[i - 1][j - 1] if j > 0 else 0
												a[i][j] += max(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE    )
				return max(a[-1]    )


if __name__ == "__main__":
						print(solution())
