




"""simple docstring"""







import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__A   :  int					=      logging.get_logger(__name__)

__A   :  Optional[int]					=      {'vocab_file': 'spiece.model'}

__A   :  str					=      {
    'vocab_file': {
        'google/bigbird-roberta-base': 'https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model',
        'google/bigbird-roberta-large': (
            'https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model'
        ),
        'google/bigbird-base-trivia-itc': (
            'https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model'
        ),
    }
}

__A   :  Union[str, Any]					=      {
    'google/bigbird-roberta-base': 4_0_9_6,
    'google/bigbird-roberta-large': 4_0_9_6,
    'google/bigbird-base-trivia-itc': 4_0_9_6,
}




class       lowerCAmelCase__       (			lowerCAmelCase_    ):


				"""simple docstring"""





				__UpperCAmelCase :     str       =      VOCAB_FILES_NAMES
				__UpperCAmelCase :     List[Any]       =      PRETRAINED_VOCAB_FILES_MAP
				__UpperCAmelCase :     List[Any]       =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				__UpperCAmelCase :     str       =      ["input_ids", "attention_mask"]
				__UpperCAmelCase :     List[int]       =      []



				def __init__(     self					:	Dict    ,   lowercase__					:	Any    ,   lowercase__					:	Dict="<unk>"    ,   lowercase__					:	int="<s>"    ,   lowercase__					:	Optional[int]="</s>"    ,   lowercase__					:	Optional[int]="<pad>"    ,   lowercase__					:	Dict="[SEP]"    ,   lowercase__					:	List[Any]="[MASK]"    ,   lowercase__					:	Tuple="[CLS]"    ,   lowercase__					:	Optional[Dict[str, Any]] = None    ,   **lowercase__					:	List[str]    ,   ):
						__lowercase				:		int												=				AddedToken(lowercase__    ,   lstrip=lowercase__    ,   rstrip=lowercase__						) if isinstance(lowercase__    ,   lowercase__						) else bos_token
						__lowercase				:		Union[str, Any]												=				AddedToken(lowercase__    ,   lstrip=lowercase__    ,   rstrip=lowercase__						) if isinstance(lowercase__    ,   lowercase__						) else eos_token
						__lowercase				:		int												=				AddedToken(lowercase__    ,   lstrip=lowercase__    ,   rstrip=lowercase__						) if isinstance(lowercase__    ,   lowercase__						) else unk_token
						__lowercase				:		str												=				AddedToken(lowercase__    ,   lstrip=lowercase__    ,   rstrip=lowercase__						) if isinstance(lowercase__    ,   lowercase__						) else pad_token
						__lowercase				:		Optional[Any]												=				AddedToken(lowercase__    ,   lstrip=lowercase__    ,   rstrip=lowercase__						) if isinstance(lowercase__    ,   lowercase__						) else cls_token
						__lowercase				:		Tuple												=				AddedToken(lowercase__    ,   lstrip=lowercase__    ,   rstrip=lowercase__						) if isinstance(lowercase__    ,   lowercase__						) else sep_token

						# Mask token behave like a normal word, i.e. include the space before it
						__lowercase				:		str												=				AddedToken(lowercase__    ,   lstrip=lowercase__    ,   rstrip=lowercase__						) if isinstance(lowercase__    ,   lowercase__						) else mask_token

						__lowercase				:		Tuple												=				{} if sp_model_kwargs is None else sp_model_kwargs

						super().__init__(
						    bos_token=lowercase__    ,   eos_token=lowercase__    ,   unk_token=lowercase__    ,   pad_token=lowercase__    ,   sep_token=lowercase__    ,   mask_token=lowercase__    ,   cls_token=lowercase__    ,   sp_model_kwargs=self.sp_model_kwargs    ,   **lowercase__    ,   )

						__lowercase				:		List[str]												=				vocab_file

						__lowercase				:		Tuple												=				spm.SentencePieceProcessor(**self.sp_model_kwargs						)
						self.sp_model.Load(lowercase__						)



				@property
				def       snake_case    (     self					:	Optional[Any]						):
						return self.sp_model.get_piece_size()



				def       snake_case    (     self					:	Tuple						):
						__lowercase				:		List[Any]												=				{self.convert_ids_to_tokens(lowercase__						): i for i in range(self.vocab_size						)}
						vocab.update(self.added_tokens_encoder						)
						return vocab



				def __getstate__(     self					:	Union[str, Any]						):
						__lowercase				:		Optional[Any]												=				self.__dict__.copy()
						__lowercase				:		List[str]												=				None
						return state



				def __setstate__(     self					:	Any    ,   lowercase__					:	str						):
						__lowercase				:		List[Any]												=				d

						# for backward compatibility
						if not hasattr(self    ,   "sp_model_kwargs"						):
								__lowercase				:		Dict												=				{}

						__lowercase				:		List[str]												=				spm.SentencePieceProcessor(**self.sp_model_kwargs						)
						self.sp_model.Load(self.vocab_file						)



				def       snake_case    (     self					:	Dict    ,   lowercase__					:	str						):
						return self.sp_model.encode(lowercase__    ,   out_type=lowercase__						)



				def       snake_case    (     self					:	Any    ,   lowercase__					:	int						):
						return self.sp_model.piece_to_id(lowercase__						)



				def       snake_case    (     self					:	str    ,   lowercase__					:	int						):
						__lowercase				:		Optional[Any]												=				self.sp_model.IdToPiece(lowercase__						)
						return token



				def       snake_case    (     self					:	Optional[int]    ,   lowercase__					:	List[Any]						):
						__lowercase				:		List[str]												=				[]
						__lowercase				:		Dict												=				""
						__lowercase				:		Optional[Any]												=				False
						for token in tokens:
								# make sure that special tokens are not decoded using sentencepiece model
								if token in self.all_special_tokens:
										if not prev_is_special:
												out_string += " "
										out_string += self.sp_model.decode(lowercase__						) + token
										__lowercase				:		List[Any]												=				True
										__lowercase				:		Union[str, Any]												=				[]
								else:
										current_sub_tokens.append(lowercase__						)
										__lowercase				:		Any												=				False
						out_string += self.sp_model.decode(lowercase__						)
						return out_string.strip()



				def       snake_case    (     self					:	List[Any]    ,   lowercase__					:	List[int]    ,   lowercase__					:	bool = False    ,   lowercase__					:	bool = None    ,   lowercase__					:	bool = True    ,   **lowercase__					:	int    ,   ):
						__lowercase				:		Any												=				kwargs.pop("use_source_tokenizer"    ,   lowercase__						)

						__lowercase				:		Union[str, Any]												=				self.convert_ids_to_tokens(lowercase__    ,   skip_special_tokens=lowercase__						)

						# To avoid mixing byte-level and unicode for byte-level BPT
						# we need to build string separately for added tokens and byte-level tokens
						# cf. https://github.com/huggingface/transformers/issues/1133
						__lowercase				:		Any												=				[]
						__lowercase				:		Optional[int]												=				[]
						for token in filtered_tokens:
								if skip_special_tokens and token in self.all_special_ids:
										continue
								if token in self.added_tokens_encoder:
										if current_sub_text:
												sub_texts.append(self.convert_tokens_to_string(lowercase__						)						)
												__lowercase				:		Union[str, Any]												=				[]
										sub_texts.append(lowercase__						)
								else:
										current_sub_text.append(lowercase__						)
						if current_sub_text:
								sub_texts.append(self.convert_tokens_to_string(lowercase__						)						)

						# Mimic the behavior of the Rust tokenizer:
						# No space before [MASK] and [SEP]
						if spaces_between_special_tokens:
								__lowercase				:		Dict												=				re.sub(r" (\[(MASK|SEP)\])"    ,   r"\1"    ,   " ".join(lowercase__						)						)
						else:
								__lowercase				:		Dict												=				"".join(lowercase__						)

						__lowercase				:		List[Any]												=				(
						    clean_up_tokenization_spaces
						    if clean_up_tokenization_spaces is not None
						    else self.clean_up_tokenization_spaces
						)
						if clean_up_tokenization_spaces:
								__lowercase				:		Dict												=				self.clean_up_tokenization(lowercase__						)
								return clean_text
						else:
								return text



				def       snake_case    (     self					:	List[Any]    ,   lowercase__					:	str    ,   lowercase__					:	Optional[str] = None						):
						if not os.path.isdir(lowercase__						):
								logger.error(f'Vocabulary path ({save_directory}) should be a directory'						)
								return
						__lowercase				:		int												=				os.path.join(
						    lowercase__    ,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)

						if os.path.abspath(self.vocab_file						) != os.path.abspath(lowercase__						) and os.path.isfile(self.vocab_file						):
								copyfile(self.vocab_file    ,   lowercase__						)
						elif not os.path.isfile(self.vocab_file						):
								with open(lowercase__    ,   "wb"						) as fi:
										__lowercase				:		List[str]												=				self.sp_model.serialized_model_proto()
										fi.write(lowercase__						)

						return (out_vocab_file,)



				def       snake_case    (     self					:	Union[str, Any]    ,   lowercase__					:	List[int]    ,   lowercase__					:	Optional[List[int]] = None						):
						if token_ids_a is None:
								return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
						__lowercase				:		Union[str, Any]												=				[self.cls_token_id]
						__lowercase				:		Dict												=				[self.sep_token_id]
						return cls + token_ids_a + sep + token_ids_a + sep



				def       snake_case    (     self					:	Union[str, Any]    ,   lowercase__					:	List[int]    ,   lowercase__					:	Optional[List[int]] = None    ,   lowercase__					:	bool = False						):
						if already_has_special_tokens:
								return super().get_special_tokens_mask(
								    token_ids_a=lowercase__    ,   token_ids_a=lowercase__    ,   already_has_special_tokens=lowercase__						)

						if token_ids_a is None:
								return [1] + ([0] * len(lowercase__						)) + [1]
						return [1] + ([0] * len(lowercase__						)) + [1] + ([0] * len(lowercase__						)) + [1]



				def       snake_case    (     self					:	Optional[int]    ,   lowercase__					:	List[int]    ,   lowercase__					:	Optional[List[int]] = None						):
						__lowercase				:		Dict												=				[self.sep_token_id]
						__lowercase				:		Tuple												=				[self.cls_token_id]
						if token_ids_a is None:
								return len(cls + token_ids_a + sep						) * [0]
						return len(cls + token_ids_a + sep						) * [0] + len(token_ids_a + sep						) * [1]






"""simple docstring"""







from __future__ import annotations

import math

def 						snake_case__       (					_lowerCamelCase,  _lowerCamelCase				)			->list:






		"""simple docstring"""


		if len(_lowerCamelCase				) != 2 or len(a[0]				) != 2 or len(_lowerCamelCase				) != 2 or len(b[0]				) != 2:
				raise Exception("Matrices are not 2x2"				)
		__lowercase				:		Tuple												=				[
		    [a[0][0] * b[0][0] + a[0][1] * b[1][0], a[0][0] * b[0][1] + a[0][1] * b[1][1]],
		    [a[1][0] * b[0][0] + a[1][1] * b[1][0], a[1][0] * b[0][1] + a[1][1] * b[1][1]],
		]
		return new_matrix

def 						snake_case__       (					_lowerCamelCase,  _lowerCamelCase				)			->Dict:






		"""simple docstring"""


		return [
		    [matrix_a[row][col] + matrix_b[row][col] for col in range(len(matrix_a[row]				)				)]
		    for row in range(len(_lowerCamelCase				)				)
		]

def 						snake_case__       (					_lowerCamelCase,  _lowerCamelCase				)			->Tuple:






		"""simple docstring"""


		return [
		    [matrix_a[row][col] - matrix_b[row][col] for col in range(len(matrix_a[row]				)				)]
		    for row in range(len(_lowerCamelCase				)				)
		]

def 						snake_case__       (					_lowerCamelCase				)			->tuple[list, list, list, list]:






		"""simple docstring"""


		if len(_lowerCamelCase				) % 2 != 0 or len(a[0]				) % 2 != 0:
				raise Exception("Odd matrices are not supported!"				)

		__lowercase				:		Tuple												=				len(_lowerCamelCase				)
		__lowercase				:		Any												=				matrix_length // 2

		__lowercase				:		Dict												=				[[a[i][j] for j in range(_lowerCamelCase,  _lowerCamelCase				)] for i in range(_lowerCamelCase				)]
		__lowercase				:		List[str]												=				[
		    [a[i][j] for j in range(_lowerCamelCase,  _lowerCamelCase				)] for i in range(_lowerCamelCase,  _lowerCamelCase				)
		]

		__lowercase				:		Union[str, Any]												=				[[a[i][j] for j in range(_lowerCamelCase				)] for i in range(_lowerCamelCase				)]
		__lowercase				:		List[str]												=				[[a[i][j] for j in range(_lowerCamelCase				)] for i in range(_lowerCamelCase,  _lowerCamelCase				)]

		return top_left, top_right, bot_left, bot_right

def 						snake_case__       (					_lowerCamelCase				)			->tuple[int, int]:






		"""simple docstring"""


		return len(_lowerCamelCase				), len(matrix[0]				)

def 						snake_case__       (					_lowerCamelCase				)			->None:






		"""simple docstring"""


		print("\n".join(str(_lowerCamelCase				) for line in matrix				)				)

def 						snake_case__       (					_lowerCamelCase,  _lowerCamelCase				)			->list:






		"""simple docstring"""


		if matrix_dimensions(_lowerCamelCase				) == (2, 2):
				return default_matrix_multiplication(_lowerCamelCase,  _lowerCamelCase				)

		__lowercase						,__lowercase						,__lowercase						,__lowercase				:		Optional[Any]												=				split_matrix(_lowerCamelCase				)
		__lowercase						,__lowercase						,__lowercase						,__lowercase				:		Any												=				split_matrix(_lowerCamelCase				)

		__lowercase				:		str												=				actual_strassen(_lowerCamelCase,  matrix_subtraction(_lowerCamelCase,  _lowerCamelCase				)				)
		__lowercase				:		Dict												=				actual_strassen(matrix_addition(_lowerCamelCase,  _lowerCamelCase				),  _lowerCamelCase				)
		__lowercase				:		Union[str, Any]												=				actual_strassen(matrix_addition(_lowerCamelCase,  _lowerCamelCase				),  _lowerCamelCase				)
		__lowercase				:		Any												=				actual_strassen(_lowerCamelCase,  matrix_subtraction(_lowerCamelCase,  _lowerCamelCase				)				)
		__lowercase				:		List[Any]												=				actual_strassen(matrix_addition(_lowerCamelCase,  _lowerCamelCase				),  matrix_addition(_lowerCamelCase,  _lowerCamelCase				)				)
		__lowercase				:		Optional[int]												=				actual_strassen(matrix_subtraction(_lowerCamelCase,  _lowerCamelCase				),  matrix_addition(_lowerCamelCase,  _lowerCamelCase				)				)
		__lowercase				:		Optional[Any]												=				actual_strassen(matrix_subtraction(_lowerCamelCase,  _lowerCamelCase				),  matrix_addition(_lowerCamelCase,  _lowerCamelCase				)				)

		__lowercase				:		str												=				matrix_addition(matrix_subtraction(matrix_addition(_lowerCamelCase,  _lowerCamelCase				),  _lowerCamelCase				),  _lowerCamelCase				)
		__lowercase				:		Dict												=				matrix_addition(_lowerCamelCase,  _lowerCamelCase				)
		__lowercase				:		int												=				matrix_addition(_lowerCamelCase,  _lowerCamelCase				)
		__lowercase				:		Union[str, Any]												=				matrix_subtraction(matrix_subtraction(matrix_addition(_lowerCamelCase,  _lowerCamelCase				),  _lowerCamelCase				),  _lowerCamelCase				)

		# construct the new matrix from our 4 quadrants
		__lowercase				:		Optional[int]												=				[]
		for i in range(len(_lowerCamelCase				)				):
				new_matrix.append(top_left[i] + top_right[i]				)
		for i in range(len(_lowerCamelCase				)				):
				new_matrix.append(bot_left[i] + bot_right[i]				)
		return new_matrix

def 						snake_case__       (					_lowerCamelCase,  _lowerCamelCase				)			->list:






		"""simple docstring"""


		if matrix_dimensions(_lowerCamelCase				)[1] != matrix_dimensions(_lowerCamelCase				)[0]:
				__lowercase				:		int												=				(
				    "Unable to multiply these matrices, please check the dimensions.\n"
				    F'Matrix A: {matrixa}\n'
				    F'Matrix B: {matrixa}'
				)
				raise Exception(_lowerCamelCase				)
		__lowercase				:		List[Any]												=				matrix_dimensions(_lowerCamelCase				)
		__lowercase				:		Tuple												=				matrix_dimensions(_lowerCamelCase				)

		if dimensiona[0] == dimensiona[1] and dimensiona[0] == dimensiona[1]:
				return [matrixa, matrixa]

		__lowercase				:		int												=				max(*_lowerCamelCase,  *_lowerCamelCase				)
		__lowercase				:		Any												=				int(math.pow(2,  math.ceil(math.loga(_lowerCamelCase				)				)				)				)
		__lowercase				:		Dict												=				matrixa
		__lowercase				:		str												=				matrixa

		# Adding zeros to the matrices so that the arrays dimensions are the same and also
		# power of 2
		for i in range(0,  _lowerCamelCase				):
				if i < dimensiona[0]:
						for _ in range(dimensiona[1],  _lowerCamelCase				):
								new_matrixa[i].append(0				)
				else:
						new_matrixa.append([0] * maxim				)
				if i < dimensiona[0]:
						for _ in range(dimensiona[1],  _lowerCamelCase				):
								new_matrixa[i].append(0				)
				else:
						new_matrixa.append([0] * maxim				)

		__lowercase				:		Dict												=				actual_strassen(_lowerCamelCase,  _lowerCamelCase				)

		# Removing the additional zeros
		for i in range(0,  _lowerCamelCase				):
				if i < dimensiona[0]:
						for _ in range(dimensiona[1],  _lowerCamelCase				):
								final_matrix[i].pop()
				else:
						final_matrix.pop()
		return final_matrix


if __name__ == "__main__":
						__A   :  int					=      [
						    [2, 3, 4, 5],
						    [6, 4, 3, 1],
						    [2, 3, 6, 7],
						    [3, 1, 2, 4],
						    [2, 3, 4, 5],
						    [6, 4, 3, 1],
						    [2, 3, 6, 7],
						    [3, 1, 2, 4],
						    [2, 3, 4, 5],
						    [6, 2, 3, 1],
						]
						__A   :  Union[str, Any]					=      [[0, 2, 1, 1], [1_6, 2, 3, 3], [2, 2, 7, 7], [1_3, 1_1, 2_2, 4]]
						print(strassen(matrixa, matrixa))
