

'''simple docstring'''






from __future__ import annotations






class 			lowercase_	:




  """simple docstring"""




  def __init__(      self   :     Optional[int]					,lowercase__   :     str					,lowercase__   :     str			):
   __lowercase  ,	__lowercase							  = text, pattern
   __lowercase  ,	__lowercase							  = len(lowercase__			), len(lowercase__			)






  def 					SCREAMING_SNAKE_CASE      (      self   :     Any					,lowercase__   :     str			):

   for i in range(self.patLen - 1					,-1					,-1			):
    if char == self.pattern[i]:
     return i
   return -1






  def 					SCREAMING_SNAKE_CASE      (      self   :     int					,lowercase__   :     int			):

   for i in range(self.patLen - 1					,-1					,-1			):
    if self.pattern[i] != self.text[current_pos + i]:
     return current_pos + i
   return -1






  def 					SCREAMING_SNAKE_CASE      (      self   :     int			):
   # searches pattern in text and returns index positions
   __lowercase							  = []
   for i in range(self.textLen - self.patLen + 1			):
    __lowercase							  = self.mismatch_in_text(lowercase__			)
    if mismatch_index == -1:
     positions.append(lowercase__			)
    else:
     __lowercase							  = self.match_in_pattern(self.text[mismatch_index]			)
     __lowercase							  = (
         mismatch_index - match_index
     )  # shifting index lgtm [py/multiple-definition]
   return positions
lowerCAmelCase__											=	'''ABAABA'''
lowerCAmelCase__											=	'''AB'''
lowerCAmelCase__											=	BoyerMooreSearch(text, pattern)
lowerCAmelCase__											=	bms.bad_character_heuristic()

if len(positions) == 0:
 print('''No match found''')
else:
 print('''Pattern found in following positions: ''')
 print(positions)





import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin
class 	UpperCAmelCase_					(					UpperCamelCase		, unittest.TestCase    ):

   '''simple docstring'''




   __A :      List[Any]     		=		BioGptTokenizer
   __A :      Optional[int]     		=		False






   def _snake_case    (		self ):






     """simple docstring"""





     super().setUp()

     # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
     lowerCamelCase :					Union[str, Any]    =				[
         "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>",
         "<unk>",
     ]
     lowerCamelCase :					str    =				dict(zip(__A						,				range(len(__A ) ) ) )
     lowerCamelCase :					Dict    =				["l o 123", "lo w 1456", "e r</w> 1789", ""]

     lowerCamelCase :					Dict    =				os.path.join(self.tmpdirname						,				VOCAB_FILES_NAMES["vocab_file"] )
     lowerCamelCase :					int    =				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 _snake_case    (		self						,				__A ):






     """simple docstring"""





     lowerCamelCase :					Dict    =				"lower newer"
     lowerCamelCase :					Union[str, Any]    =				"lower newer"
     return input_text, output_text






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					List[str]    =				BioGptTokenizer(self.vocab_file						,				self.merges_file )

     lowerCamelCase :					Optional[int]    =				"lower"
     lowerCamelCase :					Any    =				["low", "er</w>"]
     lowerCamelCase :					List[str]    =				tokenizer.tokenize(__A )
     self.assertListEqual(__A						,				__A )

     lowerCamelCase :					Union[str, Any]    =				tokens + ["<unk>"]
     lowerCamelCase :					List[str]    =				[14, 15, 20]
     self.assertListEqual(tokenizer.convert_tokens_to_ids(__A )						,				__A )






   @slow
   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					List[str]    =				BioGptTokenizer.from_pretrained("microsoft/biogpt" )

     lowerCamelCase :					Optional[int]    =				tokenizer.encode("sequence builders"						,				add_special_tokens=__A )
     lowerCamelCase :					Tuple    =				tokenizer.encode("multi-sequence build"						,				add_special_tokens=__A )

     lowerCamelCase :					Tuple    =				tokenizer.build_inputs_with_special_tokens(__A )
     lowerCamelCase :					List[str]    =				tokenizer.build_inputs_with_special_tokens(__A						,				__A )

     self.assertTrue(encoded_sentence == [2] + text )
     self.assertTrue(encoded_pair == [2] + text + [2] + text_a )



