

from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType







class  lowercase				(       lowercase_			):
				__SCREAMING_SNAKE_CASE					: str       			=			['''image_processor''', '''tokenizer''']
				__SCREAMING_SNAKE_CASE					: str       			=			'''BridgeTowerImageProcessor'''
				__SCREAMING_SNAKE_CASE					: Dict       			=			('''RobertaTokenizer''', '''RobertaTokenizerFast''')




				def __init__(					self      ,   snake_case      ,   snake_case       ):
											super().__init__(snake_case      ,   snake_case       )




				def __call__(					self      ,   snake_case      ,   snake_case = None      ,   snake_case = True      ,   snake_case = False      ,   snake_case = None      ,   snake_case = None      ,   snake_case = 0      ,   snake_case = None      ,   snake_case = None      ,   snake_case = None      ,   snake_case = False      ,   snake_case = False      ,   snake_case = False      ,   snake_case = False      ,   snake_case = True      ,   snake_case = None      ,   **snake_case      ,   ):
											snake_case_							=    self.tokenizer(
											    text=snake_case      ,   add_special_tokens=snake_case      ,   padding=snake_case      ,   truncation=snake_case      ,   max_length=snake_case      ,   stride=snake_case      ,   pad_to_multiple_of=snake_case      ,   return_token_type_ids=snake_case      ,   return_attention_mask=snake_case      ,   return_overflowing_tokens=snake_case      ,   return_special_tokens_mask=snake_case      ,   return_offsets_mapping=snake_case      ,   return_length=snake_case      ,   verbose=snake_case      ,   return_tensors=snake_case      ,   **snake_case      ,   )
											# add pixel_values + pixel_mask
											snake_case_							=    self.image_processor(
											    snake_case      ,   return_tensors=snake_case      ,   do_normalize=snake_case      ,   do_center_crop=snake_case      ,   **snake_case       )
											encoding.update(snake_case       )

											return encoding




				def     a							(					self      ,   *snake_case      ,   **snake_case       ):
											return self.tokenizer.batch_decode(*snake_case      ,   **snake_case       )




				def     a							(					self      ,   *snake_case      ,   **snake_case       ):
											return self.tokenizer.decode(*snake_case      ,   **snake_case       )




				@property
				def     a							(					self       ):
											snake_case_							=    self.tokenizer.model_input_names
											snake_case_							=    self.image_processor.model_input_names
											return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names       )       )







from __future__ import annotations

import numpy as np





def 					__lowerCamelCase	( UpperCamelCase__      ):







							'''simple docstring'''






							snake_case_				,    snake_case_							=    np.shape(UpperCamelCase__      )
							if rows != columns:
														snake_case_							=    (
														    '\'table\' has to be of square shaped array but got a '
														    F'''{rows}x{columns} array:\n{table}'''
														)
														raise ValueError(UpperCamelCase__      )

							snake_case_							=    np.zeros((rows, columns)      )
							snake_case_							=    np.zeros((rows, columns)      )
							for i in range(UpperCamelCase__      ):
														for j in range(UpperCamelCase__      ):
																					snake_case_							=    sum(lower[i][k] * upper[k][j] for k in range(UpperCamelCase__      )      )
																					if upper[j][j] == 0:
																												raise ArithmeticError('No LU decomposition exists'      )
																					snake_case_							=    (table[i][j] - total) / upper[j][j]
														snake_case_							=    1
														for j in range(UpperCamelCase__   ,							UpperCamelCase__      ):
																					snake_case_							=    sum(lower[i][k] * upper[k][j] for k in range(UpperCamelCase__      )      )
																					snake_case_							=    table[i][j] - total
							return lower, upper


if __name__ == "__main__":
					import doctest

					doctest.testmod()




