


'''simple docstring'''






import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin
class 						__UpperCamelCase	(						lowercase__						,  unittest.TestCase							):
							lowercase			:		List[Any]   		=  CanineTokenizer
							lowercase			:		str   		=  False





							def 		a__   (  self		:Optional[Any]			):
									super().setUp()
									snake_case_		:							int			       =						CanineTokenizer()
									tokenizer.save_pretrained(self.tmpdirname			)





							@cached_property
							def 		a__   (  self		:Optional[int]			):
									return CanineTokenizer.from_pretrained("""google/canine-s"""			)





							def 		a__   (  self		:int  ,**_UpperCamelCase		:Dict			):
									snake_case_		:							Dict			       =						self.tokenizer_class.from_pretrained(self.tmpdirname  ,**_UpperCamelCase			)
									snake_case_		:							Optional[Any]			       =						1_0_2_4
									return tokenizer





							@require_torch
							def 		a__   (  self		:List[str]			):
									snake_case_		:							Union[str, Any]			       =						self.canine_tokenizer
									snake_case_		:							Optional[int]			       =						["""Life is like a box of chocolates.""", """You never know what you're gonna get."""]
									# fmt: off
									snake_case_		:							Dict			       =						[5_7_3_4_4, 7_6, 1_0_5, 1_0_2, 1_0_1, 3_2, 1_0_5, 1_1_5, 3_2, 1_0_8, 1_0_5, 1_0_7, 1_0_1, 3_2, 9_7, 3_2, 9_8, 1_1_1, 1_2_0, 3_2, 1_1_1, 1_0_2, 3_2, 9_9, 1_0_4, 1_1_1, 9_9, 1_1_1, 1_0_8, 9_7, 1_1_6, 1_0_1, 1_1_5, 4_6, 5_7_3_4_5, 0, 0, 0, 0]
									# fmt: on
									snake_case_		:							Any			       =						tokenizer(_UpperCamelCase  ,padding=_UpperCamelCase  ,return_tensors="""pt"""			)
									self.assertIsInstance(_UpperCamelCase  ,_UpperCamelCase			)

									snake_case_		:							Optional[Any]			       =						list(batch.input_ids.numpy()[0]			)

									self.assertListEqual(_UpperCamelCase  ,_UpperCamelCase			)

									self.assertEqual((2, 3_9)  ,batch.input_ids.shape			)
									self.assertEqual((2, 3_9)  ,batch.attention_mask.shape			)





							@require_torch
							def 		a__   (  self		:int			):
									snake_case_		:							Union[str, Any]			       =						self.canine_tokenizer
									snake_case_		:							Dict			       =						["""Once there was a man.""", """He wrote a test in HuggingFace Tranformers."""]
									snake_case_		:							int			       =						tokenizer(_UpperCamelCase  ,padding=_UpperCamelCase  ,return_tensors="""pt"""			)
									# check if input_ids, attention_mask and token_type_ids are returned
									self.assertIn("""input_ids"""  ,_UpperCamelCase			)
									self.assertIn("""attention_mask"""  ,_UpperCamelCase			)
									self.assertIn("""token_type_ids"""  ,_UpperCamelCase			)





							@require_torch
							def 		a__   (  self		:Tuple			):
									snake_case_		:							Union[str, Any]			       =						self.canine_tokenizer
									snake_case_		:							Tuple			       =						[
									    """What's the weater?""",
									    """It's about 25 degrees.""",
									]
									snake_case_		:							Optional[int]			       =						tokenizer(
									    text_target=_UpperCamelCase  ,max_length=3_2  ,padding="""max_length"""  ,truncation=_UpperCamelCase  ,return_tensors="""pt"""			)
									self.assertEqual(3_2  ,targets["""input_ids"""].shape[1]			)





							def 		a__   (  self		:List[str]			):
									# safety check on max_len default value so we are sure the test works
									snake_case_		:							Optional[int]			       =						self.get_tokenizers()
									for tokenizer in tokenizers:
											with self.subTest(F'''{tokenizer.__class__.__name__}'''			):
													self.assertNotEqual(tokenizer.model_max_length  ,4_2			)

        # Now let's start the test
									snake_case_		:							List[Any]			       =						self.get_tokenizers()
									for tokenizer in tokenizers:
											with self.subTest(F'''{tokenizer.__class__.__name__}'''			):
													# Isolate this from the other tests because we save additional tokens/etc
													snake_case_		:							Dict			       =						tempfile.mkdtemp()

													snake_case_		:							Optional[int]			       =						""" He is very happy, UNwant\u00E9d,running"""
													snake_case_		:							Optional[Any]			       =						tokenizer.encode(_UpperCamelCase  ,add_special_tokens=_UpperCamelCase			)
													tokenizer.save_pretrained(_UpperCamelCase			)

													snake_case_		:							Union[str, Any]			       =						tokenizer.__class__.from_pretrained(_UpperCamelCase			)
													snake_case_		:							Dict			       =						after_tokenizer.encode(_UpperCamelCase  ,add_special_tokens=_UpperCamelCase			)
													self.assertListEqual(_UpperCamelCase  ,_UpperCamelCase			)

													shutil.rmtree(_UpperCamelCase			)

									snake_case_		:							Optional[int]			       =						self.get_tokenizers(model_max_length=4_2			)
									for tokenizer in tokenizers:
											with self.subTest(F'''{tokenizer.__class__.__name__}'''			):
													# Isolate this from the other tests because we save additional tokens/etc
													snake_case_		:							List[Any]			       =						tempfile.mkdtemp()

													snake_case_		:							List[str]			       =						""" He is very happy, UNwant\u00E9d,running"""

													snake_case_		:							Any			       =						tokenizer.additional_special_tokens

													# We can add a new special token for Canine as follows:
													snake_case_		:							List[Any]			       =						chr(0xE_0_0_7			)
													additional_special_tokens.append(_UpperCamelCase			)
													tokenizer.add_special_tokens({"""additional_special_tokens""": additional_special_tokens}			)
													snake_case_		:							Tuple			       =						tokenizer.encode(_UpperCamelCase  ,add_special_tokens=_UpperCamelCase			)
													tokenizer.save_pretrained(_UpperCamelCase			)

													snake_case_		:							Optional[Any]			       =						tokenizer.__class__.from_pretrained(_UpperCamelCase			)
													snake_case_		:							Tuple			       =						after_tokenizer.encode(_UpperCamelCase  ,add_special_tokens=_UpperCamelCase			)
													self.assertListEqual(_UpperCamelCase  ,_UpperCamelCase			)
													self.assertIn(_UpperCamelCase  ,after_tokenizer.additional_special_tokens			)
													self.assertEqual(after_tokenizer.model_max_length  ,4_2			)

													snake_case_		:							str			       =						tokenizer.__class__.from_pretrained(_UpperCamelCase  ,model_max_length=4_3			)
													self.assertEqual(tokenizer.model_max_length  ,4_3			)

													shutil.rmtree(_UpperCamelCase			)





							def 		a__   (  self		:Union[str, Any]			):
									snake_case_		:							Dict			       =						self.get_tokenizers(do_lower_case=_UpperCamelCase			)
									for tokenizer in tokenizers:
											with self.subTest(F'''{tokenizer.__class__.__name__}'''			):
													snake_case_       ,      snake_case_		:							List[str]			       =						self.get_clean_sequence(_UpperCamelCase			)

													# a special token for Canine can be defined as follows:
													snake_case_		:							Optional[int]			       =						0xE_0_0_5
													snake_case_		:							int			       =						chr(_UpperCamelCase			)

													tokenizer.add_special_tokens({"""cls_token""": special_token}			)
													snake_case_		:							str			       =						tokenizer.encode(_UpperCamelCase  ,add_special_tokens=_UpperCamelCase			)
													self.assertEqual(len(_UpperCamelCase			)  ,1			)

													snake_case_		:							List[str]			       =						tokenizer.decode(ids + encoded_special_token  ,clean_up_tokenization_spaces=_UpperCamelCase			)
													snake_case_		:							Any			       =						tokenizer.encode(_UpperCamelCase  ,add_special_tokens=_UpperCamelCase			)

													snake_case_		:							List[str]			       =						tokenizer.encode(_UpperCamelCase  ,add_special_tokens=_UpperCamelCase			)
													snake_case_		:							Optional[Any]			       =						tokenizer.encode(_UpperCamelCase  ,add_special_tokens=_UpperCamelCase			)
													self.assertEqual(_UpperCamelCase  ,input_encoded + special_token_id			)

													snake_case_		:							Optional[Any]			       =						tokenizer.decode(_UpperCamelCase  ,skip_special_tokens=_UpperCamelCase			)
													self.assertTrue(special_token not in decoded			)





							def 		a__   (  self		:Any			):
									snake_case_		:							str			       =						self.get_tokenizers(do_lower_case=_UpperCamelCase			)
									for tokenizer in tokenizers:
											with self.subTest(F'''{tokenizer.__class__.__name__}'''			):
													snake_case_		:							Optional[Any]			       =						chr(0xE_0_0_5			)
													snake_case_		:							List[str]			       =						chr(0xE_0_0_6			)

													# `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
													tokenizer.add_tokens([SPECIAL_TOKEN_1]  ,special_tokens=_UpperCamelCase			)
													# `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
													# which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
													tokenizer.add_special_tokens({"""additional_special_tokens""": [SPECIAL_TOKEN_2]}			)

													snake_case_		:							Optional[int]			       =						tokenizer.tokenize(_UpperCamelCase			)
													snake_case_		:							int			       =						tokenizer.tokenize(_UpperCamelCase			)

													self.assertEqual(len(_UpperCamelCase			)  ,1			)
													self.assertEqual(len(_UpperCamelCase			)  ,1			)
													self.assertEqual(token_a[0]  ,_UpperCamelCase			)
													self.assertEqual(token_a[0]  ,_UpperCamelCase			)





							@require_tokenizers
							def 		a__   (  self		:int			):
									snake_case_		:							Tuple			       =						self.get_tokenizers(do_lower_case=_UpperCamelCase			)
									for tokenizer in tokenizers:
											with self.subTest(F'''{tokenizer.__class__.__name__}'''			):
													# a special token for Canine can be defined as follows:
													snake_case_		:							Tuple			       =						0xE_0_0_6
													snake_case_		:							str			       =						chr(_UpperCamelCase			)

													snake_case_		:							List[Any]			       =						AddedToken(_UpperCamelCase  ,lstrip=_UpperCamelCase			)
													tokenizer.add_special_tokens({"""additional_special_tokens""": [new_token]}			)

													with tempfile.TemporaryDirectory() as tmp_dir_name:
															tokenizer.save_pretrained(_UpperCamelCase			)
															tokenizer.from_pretrained(_UpperCamelCase			)





							def 		a__   (  self		:int			):
									snake_case_		:							List[Any]			       =						[]
									if self.test_slow_tokenizer:
											tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())			)

									if self.test_rust_tokenizer:
											tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())			)

									for tokenizer_class, tokenizer_utils in tokenizer_list:
											with tempfile.TemporaryDirectory() as tmp_dir:
													tokenizer_utils.save_pretrained(_UpperCamelCase			)

													with open(os.path.join(_UpperCamelCase  ,"""special_tokens_map.json"""			)  ,encoding="""utf-8"""			) as json_file:
															snake_case_		:							Dict			       =						json.load(_UpperCamelCase			)

													with open(os.path.join(_UpperCamelCase  ,"""tokenizer_config.json"""			)  ,encoding="""utf-8"""			) as json_file:
															snake_case_		:							Optional[int]			       =						json.load(_UpperCamelCase			)

													# a special token for Canine can be defined as follows:
													snake_case_		:							int			       =						0xE_0_0_6
													snake_case_		:							List[str]			       =						chr(_UpperCamelCase			)

													snake_case_		:							Union[str, Any]			       =						[new_token_a]
													snake_case_		:							List[str]			       =						[new_token_a]

													with open(os.path.join(_UpperCamelCase  ,"""special_tokens_map.json"""			)  ,"""w"""  ,encoding="""utf-8"""			) as outfile:
															json.dump(_UpperCamelCase  ,_UpperCamelCase			)
													with open(os.path.join(_UpperCamelCase  ,"""tokenizer_config.json"""			)  ,"""w"""  ,encoding="""utf-8"""			) as outfile:
															json.dump(_UpperCamelCase  ,_UpperCamelCase			)

													# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
													# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
													# "special_tokens_map.json" files
													snake_case_		:							List[str]			       =						tokenizer_class.from_pretrained(_UpperCamelCase  ,extra_ids=0			)
													self.assertIn(_UpperCamelCase  ,tokenizer_without_change_in_init.additional_special_tokens			)
													# self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
													self.assertEqual(
													    [new_token_a]  ,tokenizer_without_change_in_init.convert_ids_to_tokens(
													        tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]			)			)  ,)

													snake_case_		:							Dict			       =						0xE_0_0_7
													snake_case_		:							Optional[int]			       =						chr(_UpperCamelCase			)
													# Now we test that we can change the value of additional_special_tokens in the from_pretrained
													snake_case_		:							Optional[int]			       =						[AddedToken(_UpperCamelCase  ,lstrip=_UpperCamelCase			)]
													snake_case_		:							List[Any]			       =						tokenizer_class.from_pretrained(
													    _UpperCamelCase  ,additional_special_tokens=_UpperCamelCase  ,extra_ids=0			)

													self.assertIn(_UpperCamelCase  ,tokenizer.additional_special_tokens			)
													# self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
													self.assertEqual(
													    [new_token_a]  ,tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]			)			)			)





							@require_tokenizers
							def 		a__   (  self		:List[str]			):
									snake_case_		:							Union[str, Any]			       =						self.get_tokenizers(do_lower_case=_UpperCamelCase			)
									for tokenizer in tokenizers:
											with self.subTest(F'''{tokenizer.__class__.__name__}'''			):
													snake_case_		:							Any			       =						"""hello world"""
													if self.space_between_special_tokens:
															snake_case_		:							int			       =						"""[CLS] hello world [SEP]"""
													else:
															snake_case_		:							List[str]			       =						input
													snake_case_		:							Any			       =						tokenizer.encode(_UpperCamelCase  ,add_special_tokens=_UpperCamelCase			)
													snake_case_		:							Union[str, Any]			       =						tokenizer.decode(_UpperCamelCase  ,spaces_between_special_tokens=self.space_between_special_tokens			)
													self.assertIn(_UpperCamelCase  ,[output, output.lower()]			)





							def 		a__   (  self		:Dict			):
									snake_case_		:							Optional[Any]			       =						self.get_tokenizers()
									for tokenizer in tokenizers:
											with self.subTest(F'''{tokenizer.__class__.__name__}'''			):
													snake_case_		:							Tuple			       =						[
													    """bos_token""",
													    """eos_token""",
													    """unk_token""",
													    """sep_token""",
													    """pad_token""",
													    """cls_token""",
													    """mask_token""",
													]

									snake_case_		:							Tuple			       =						"""a"""
									snake_case_		:							Optional[Any]			       =						ord(_UpperCamelCase			)

									for attr in attributes_list:
											setattr(_UpperCamelCase  ,attr + """_id"""  ,_UpperCamelCase			)
											self.assertEqual(getattr(_UpperCamelCase  ,_UpperCamelCase			)  ,_UpperCamelCase			)
											self.assertEqual(getattr(_UpperCamelCase  ,attr + """_id"""			)  ,_UpperCamelCase			)

											setattr(_UpperCamelCase  ,attr + """_id"""  ,_UpperCamelCase			)
											self.assertEqual(getattr(_UpperCamelCase  ,_UpperCamelCase			)  ,_UpperCamelCase			)
											self.assertEqual(getattr(_UpperCamelCase  ,attr + """_id"""			)  ,_UpperCamelCase			)

									setattr(_UpperCamelCase  ,"""additional_special_tokens_ids"""  ,[]			)
									self.assertListEqual(getattr(_UpperCamelCase  ,"""additional_special_tokens"""			)  ,[]			)
									self.assertListEqual(getattr(_UpperCamelCase  ,"""additional_special_tokens_ids"""			)  ,[]			)

									snake_case_		:							Optional[int]			       =						0xE_0_0_6
									snake_case_		:							Union[str, Any]			       =						chr(_UpperCamelCase			)
									setattr(_UpperCamelCase  ,"""additional_special_tokens_ids"""  ,[additional_special_token_id]			)
									self.assertListEqual(getattr(_UpperCamelCase  ,"""additional_special_tokens"""			)  ,[additional_special_token]			)
									self.assertListEqual(getattr(_UpperCamelCase  ,"""additional_special_tokens_ids"""			)  ,[additional_special_token_id]			)





							def 		a__   (  self		:Dict			):
									pass





							def 		a__   (  self		:Tuple			):
									pass





							def 		a__   (  self		:Tuple			):
									pass





							def 		a__   (  self		:Any			):
									pass





							def 		a__   (  self		:List[Any]			):
									pass





							def 		a__   (  self		:Optional[Any]			):
									pass





							def 		a__   (  self		:Dict			):
									pass





							def 		a__   (  self		:Optional[int]			):
									pass



'''simple docstring'''






from __future__ import annotations

import math





def      UpperCAmelCase      (		lowerCamelCase_  :list				,      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""" )
		snake_case_		:							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      UpperCAmelCase      (		lowerCamelCase_  :list				,      lowerCamelCase_  :list ):







		'''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      UpperCAmelCase      (		lowerCamelCase_  :list				,      lowerCamelCase_  :list ):







		'''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      UpperCAmelCase      (		lowerCamelCase_  :list ):







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

		snake_case_		:							Optional[int]			       =						len(lowerCamelCase_ )
		snake_case_		:							List[str]			       =						matrix_length // 2

		snake_case_		:							Union[str, Any]			       =						[[a[i][j] for j in range(lowerCamelCase_				,      lowerCamelCase_ )] for i in range(lowerCamelCase_ )]
		snake_case_		:							Dict			       =						[
		    [a[i][j] for j in range(lowerCamelCase_				,      lowerCamelCase_ )] for i in range(lowerCamelCase_				,      lowerCamelCase_ )
		]

		snake_case_		:							str			       =						[[a[i][j] for j in range(lowerCamelCase_ )] for i in range(lowerCamelCase_ )]
		snake_case_		:							Dict			       =						[[a[i][j] for j in range(lowerCamelCase_ )] for i in range(lowerCamelCase_				,      lowerCamelCase_ )]

		return top_left, top_right, bot_left, bot_right





def      UpperCAmelCase      (		lowerCamelCase_  :list ):







		'''simple docstring'''
		return len(lowerCamelCase_ ), len(matrix[0] )





def      UpperCAmelCase      (		lowerCamelCase_  :list ):







		'''simple docstring'''
		print("""\n""".join(str(lowerCamelCase_ ) for line in matrix ) )





def      UpperCAmelCase      (		lowerCamelCase_  :list				,      lowerCamelCase_  :list ):







		'''simple docstring'''
		if matrix_dimensions(lowerCamelCase_ ) == (2, 2):
				return default_matrix_multiplication(lowerCamelCase_				,      lowerCamelCase_ )

		snake_case_       ,      snake_case_       ,      snake_case_       ,      snake_case_		:							Any			       =						split_matrix(lowerCamelCase_ )
		snake_case_       ,      snake_case_       ,      snake_case_       ,      snake_case_		:							List[Any]			       =						split_matrix(lowerCamelCase_ )

		snake_case_		:							Any			       =						actual_strassen(lowerCamelCase_				,      matrix_subtraction(lowerCamelCase_				,      lowerCamelCase_ ) )
		snake_case_		:							str			       =						actual_strassen(matrix_addition(lowerCamelCase_				,      lowerCamelCase_ )				,      lowerCamelCase_ )
		snake_case_		:							str			       =						actual_strassen(matrix_addition(lowerCamelCase_				,      lowerCamelCase_ )				,      lowerCamelCase_ )
		snake_case_		:							List[str]			       =						actual_strassen(lowerCamelCase_				,      matrix_subtraction(lowerCamelCase_				,      lowerCamelCase_ ) )
		snake_case_		:							Optional[int]			       =						actual_strassen(matrix_addition(lowerCamelCase_				,      lowerCamelCase_ )				,      matrix_addition(lowerCamelCase_				,      lowerCamelCase_ ) )
		snake_case_		:							Dict			       =						actual_strassen(matrix_subtraction(lowerCamelCase_				,      lowerCamelCase_ )				,      matrix_addition(lowerCamelCase_				,      lowerCamelCase_ ) )
		snake_case_		:							int			       =						actual_strassen(matrix_subtraction(lowerCamelCase_				,      lowerCamelCase_ )				,      matrix_addition(lowerCamelCase_				,      lowerCamelCase_ ) )

		snake_case_		:							List[Any]			       =						matrix_addition(matrix_subtraction(matrix_addition(lowerCamelCase_				,      lowerCamelCase_ )				,      lowerCamelCase_ )				,      lowerCamelCase_ )
		snake_case_		:							List[Any]			       =						matrix_addition(lowerCamelCase_				,      lowerCamelCase_ )
		snake_case_		:							str			       =						matrix_addition(lowerCamelCase_				,      lowerCamelCase_ )
		snake_case_		:							Any			       =						matrix_subtraction(matrix_subtraction(matrix_addition(lowerCamelCase_				,      lowerCamelCase_ )				,      lowerCamelCase_ )				,      lowerCamelCase_ )

		# construct the new matrix from our 4 quadrants
		snake_case_		:							Dict			       =						[]
		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      UpperCAmelCase      (		lowerCamelCase_  :list				,      lowerCamelCase_  :list ):







		'''simple docstring'''
		if matrix_dimensions(lowerCamelCase_ )[1] != matrix_dimensions(lowerCamelCase_ )[0]:
				snake_case_		:							Optional[int]			       =						(
				    """Unable to multiply these matrices, please check the dimensions.\n"""
				    F'''Matrix A: {matrixa}\n'''
				    F'''Matrix B: {matrixa}'''
				)
				raise Exception(lowerCamelCase_ )
		snake_case_		:							Tuple			       =						matrix_dimensions(lowerCamelCase_ )
		snake_case_		:							Union[str, Any]			       =						matrix_dimensions(lowerCamelCase_ )

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

		snake_case_		:							int			       =						max(*lowerCamelCase_				,      *lowerCamelCase_ )
		snake_case_		:							Union[str, Any]			       =						int(math.pow(2				,      math.ceil(math.loga(lowerCamelCase_ ) ) ) )
		snake_case_		:							Dict			       =						matrixa
		snake_case_		:							Optional[int]			       =						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 )

		snake_case_		:							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	:	Optional[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	:	List[str]     =     [[0, 2, 1, 1], [16, 2, 3, 3], [2, 2, 7, 7], [13, 11, 22, 4]]
							print(strassen(matrixa, matrixa))