





'''simple docstring'''



import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class     A_ (  lowerCAmelCase_    ,			unittest.TestCase  ):

			'''simple docstring'''





			_lowerCAmelCase						=    HerbertTokenizer
			_lowerCAmelCase						=    HerbertTokenizerFast
			_lowerCAmelCase						=    True




			def       a	(					self   ):
								super().setUp()

								# Use a simpler test file without japanese/chinese characters
								with open(F"{get_tests_dir()}/fixtures/sample_text_no_unicode.txt"			,     encoding="utf-8"   ) as f_data:
													_UpperCamelCase											=   f_data.read().replace("\n\n"			,     "\n"   ).strip()

								_UpperCamelCase											=   [
								    "<s>",
								    "</s>",
								    "l",
								    "o",
								    "w",
								    "e",
								    "r",
								    "s",
								    "t",
								    "i",
								    "d",
								    "n",
								    "w</w>",
								    "r</w>",
								    "t</w>",
								    "lo",
								    "low",
								    "er</w>",
								    "low</w>",
								    "lowest</w>",
								    "newer</w>",
								    "wider</w>",
								    ",</w>",
								    "<unk>",
								]
								_UpperCamelCase											=   dict(zip(A_			,     range(len(A_   )   )   )   )
								_UpperCamelCase											=   ["l o 123", "lo w 1456", "e r</w> 1789", ""]

								_UpperCamelCase											=   os.path.join(self.tmpdirname			,     VOCAB_FILES_NAMES["vocab_file"]   )
								_UpperCamelCase											=   os.path.join(self.tmpdirname			,     VOCAB_FILES_NAMES["merges_file"]   )
								with open(self.vocab_file			,     "w"   ) as fp:
													fp.write(json.dumps(A_   )   )
								with open(self.merges_file			,     "w"   ) as fp:
													fp.write("\n".join(A_   )   )




			def       a	(					self			,     A_   ):
								_UpperCamelCase											=   "lower newer"
								_UpperCamelCase											=   "lower newer"
								return input_text, output_text




			def       a	(					self   ):
								_UpperCamelCase											=   self.tokenizer_class(vocab_file=self.vocab_file			,     merges_file=self.merges_file   )

								_UpperCamelCase											=   "lower"
								_UpperCamelCase											=   ["low", "er</w>"]
								_UpperCamelCase											=   tokenizer.tokenize(A_   )
								self.assertListEqual(A_			,     A_   )

								_UpperCamelCase											=   tokens + ["<unk>"]
								_UpperCamelCase											=   [16, 17, 23]
								self.assertListEqual(tokenizer.convert_tokens_to_ids(A_   )			,     A_   )




			def       a	(					self   ):
								if not self.test_rust_tokenizer:
													return

								_UpperCamelCase											=   self.get_tokenizer()
								_UpperCamelCase											=   self.get_rust_tokenizer()

								_UpperCamelCase											=   "lower,newer"

								_UpperCamelCase											=   tokenizer.tokenize(A_   )
								_UpperCamelCase											=   rust_tokenizer.tokenize(A_   )
								self.assertListEqual(A_			,     A_   )

								_UpperCamelCase											=   tokenizer.encode(A_			,     add_special_tokens=A_   )
								_UpperCamelCase											=   rust_tokenizer.encode(A_			,     add_special_tokens=A_   )
								self.assertListEqual(A_			,     A_   )

								_UpperCamelCase											=   self.get_rust_tokenizer()
								_UpperCamelCase											=   tokenizer.encode(A_   )
								_UpperCamelCase											=   rust_tokenizer.encode(A_   )
								self.assertListEqual(A_			,     A_   )




			@slow
			def       a	(					self   ):
								_UpperCamelCase											=   self.tokenizer_class.from_pretrained("allegro/herbert-base-cased"   )

								_UpperCamelCase											=   tokenizer.encode("konstruowanie sekwencji"			,     add_special_tokens=A_   )
								_UpperCamelCase											=   tokenizer.encode("konstruowanie wielu sekwencji"			,     add_special_tokens=A_   )

								_UpperCamelCase											=   tokenizer.build_inputs_with_special_tokens(A_   )
								_UpperCamelCase											=   tokenizer.build_inputs_with_special_tokens(A_			,     A_   )

								assert encoded_sentence == [0] + text + [2]
								assert encoded_pair == [0] + text + [2] + text_a + [2]










'''simple docstring'''



from __future__ import annotations



def  lowercase__(		_UpperCamelCase  : list[list[int]] ,   _UpperCamelCase  : int ,   _UpperCamelCase  : int ,   _UpperCamelCase  : int | float				)->   None:






					"""simple docstring"""

					_UpperCamelCase				,	_UpperCamelCase											=   m - 1, 0
					while i >= 0 and j < n:
										if key == mat[i][j]:
															print(f"Key {key} found at row- {i + 1} column- {j + 1}"				)
															return
										if key < mat[i][j]:
															i -= 1
										else:
															j += 1
					print(f"Key {key} not found"				)



def  lowercase__(		)->   None:






					"""simple docstring"""

					_UpperCamelCase											=   [[2, 5, 7], [4, 8, 13], [9, 11, 15], [12, 17, 20]]
					_UpperCamelCase											=   int(input("Enter the element to be searched:"				)				)
					print(_UpperCamelCase				)
					search_in_a_sorted_matrix(_UpperCamelCase ,   len(_UpperCamelCase				) ,   len(mat[0]				) ,   _UpperCamelCase				)


if __name__ == "__main__":
			import doctest

			doctest.testmod()
			main()



