






"""simple docstring"""



import math
from typing import Optional

import numpy as np

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__A						:			Optional[Any]    							=						logging.get_logger(__name__)

__A						:			Tuple    							=						{
    '''facebook/encodec_24khz''': '''https://huggingface.co/facebook/encodec_24khz/resolve/main/config.json''',
    '''facebook/encodec_48khz''': '''https://huggingface.co/facebook/encodec_48khz/resolve/main/config.json''',
}





class    _UpperCAmelCase			(					_A				):
					SCREAMING_SNAKE_CASE_						:							str				       =  "encodec"




					def __init__(							self	:		List[Any]       ,		A	:		str=[1.5, 3.0, 6.0, 12.0, 24.0]       ,		A	:		Dict=2_40_00       ,		A	:		Dict=1       ,		A	:		Any=False       ,		A	:		List[str]=None       ,		A	:		Optional[int]=None       ,		A	:		Dict=1_28       ,		A	:		Any=32       ,		A	:		List[Any]=1       ,		A	:		str=[8, 5, 4, 2]       ,		A	:		List[Any]="weight_norm"       ,		A	:		int=7       ,		A	:		Dict=7       ,		A	:		Tuple=3       ,		A	:		Dict=2       ,		A	:		Any=True       ,		A	:		Union[str, Any]="reflect"       ,		A	:		str=2       ,		A	:		int=2       ,		A	:		str=1.0       ,		A	:		Optional[Any]=10_24       ,		A	:		List[Any]=None       ,		A	:		Union[str, Any]=True       ,		**A	:		Optional[int]       ,		)    ->    List[Any]:
							lowercase_					:					Dict							=  target_bandwidths
							lowercase_					:					Optional[int]							=  sampling_rate
							lowercase_					:					Tuple							=  audio_channels
							lowercase_					:					Union[str, Any]							=  normalize
							lowercase_					:					Union[str, Any]							=  chunk_length_s
							lowercase_					:					Any							=  overlap
							lowercase_					:					int							=  hidden_size
							lowercase_					:					List[str]							=  num_filters
							lowercase_					:					List[str]							=  num_residual_layers
							lowercase_					:					Tuple							=  upsampling_ratios
							lowercase_					:					Union[str, Any]							=  norm_type
							lowercase_					:					Tuple							=  kernel_size
							lowercase_					:					Union[str, Any]							=  last_kernel_size
							lowercase_					:					Any							=  residual_kernel_size
							lowercase_					:					List[str]							=  dilation_growth_rate
							lowercase_					:					Optional[Any]							=  use_causal_conv
							lowercase_					:					int							=  pad_mode
							lowercase_					:					Dict							=  compress
							lowercase_					:					List[Any]							=  num_lstm_layers
							lowercase_					:					List[Any]							=  trim_right_ratio
							lowercase_					:					List[Any]							=  codebook_size
							lowercase_					:					Optional[int]							=  codebook_dim if codebook_dim is not None else hidden_size
							lowercase_					:					Union[str, Any]							=  use_conv_shortcut

							if self.norm_type not in ["weight_norm", "time_group_norm"]:
									raise ValueError(
									    F'''self.norm_type must be one of `"weight_norm"`, `"time_group_norm"`), got {self.norm_type}'''  )

							super().__init__(**UpperCamelCase_  )




					@property
					def     A    (							self	:		Tuple  )    ->    Optional[int]:
							if self.chunk_length_s is None:
									return None
							else:
									return int(self.chunk_length_s * self.sampling_rate  )




					@property
					def     A    (							self	:		Union[str, Any]  )    ->    Optional[int]:
							if self.chunk_length_s is None or self.overlap is None:
									return None
							else:
									return max(1       ,		int((1.0 - self.overlap) * self.chunk_length  )  )




					@property
					def     A    (							self	:		Any  )    ->    int:
							lowercase_					:					str							=  np.prod(self.upsampling_ratios  )
							return math.ceil(self.sampling_rate / hop_length  )






					@property
					def     A    (							self	:		Dict  )    ->    int:
							return int(10_00 * self.target_bandwidths[-1] // (self.frame_rate * 10)  )










'''simple docstring'''




import os




def 						__lowerCamelCase			(	UpperCAmelCase_ = "input.txt"							)   ->int:

	with open(os.path.join(os.path.dirname(UpperCAmelCase_							)					,				UpperCAmelCase_							)							) as input_file:
		snake_case__	       =   [
		    [int(UpperCAmelCase_							) for element in line.split(','							)]
		    for line in input_file.readlines()
		]

	snake_case__	       =   len(UpperCAmelCase_							)
	snake_case__	       =   len(matrix[0]							)

	snake_case__	       =   [[-1 for _ in range(UpperCAmelCase_							)] for _ in range(UpperCAmelCase_							)]
	for i in range(UpperCAmelCase_							):
		snake_case__	       =   matrix[i][0]

	for j in range(1					,				UpperCAmelCase_							):
		for i in range(UpperCAmelCase_							):
			snake_case__	       =   minimal_path_sums[i][j - 1] + matrix[i][j]

		for i in range(1					,				UpperCAmelCase_							):
			snake_case__	       =   min(
			    minimal_path_sums[i][j]					,				minimal_path_sums[i - 1][j] + matrix[i][j]							)

		for i in range(rows - 2					,				-1					,				-1							):
			snake_case__	       =   min(
			    minimal_path_sums[i][j]					,				minimal_path_sums[i + 1][j] + matrix[i][j]							)

	return min(minimal_path_sums_row[-1] for minimal_path_sums_row in minimal_path_sums							)


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



