

import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class     __snake_case    (				snake_case__			,	unittest.TestCase  ):
       """simple docstring"""







       __SCREAMING_SNAKE_CASE				    =							LongformerTokenizer
       __SCREAMING_SNAKE_CASE				    =							True
       __SCREAMING_SNAKE_CASE				    =							LongformerTokenizerFast
       __SCREAMING_SNAKE_CASE				    =							True


       def 			a		(		self   )      ->							List[str]:






              """simple docstring"""


              super().setUp()

              # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
              __snake_case       	=							[
                  """l""",
                  """o""",
                  """w""",
                  """e""",
                  """r""",
                  """s""",
                  """t""",
                  """i""",
                  """d""",
                  """n""",
                  """\u0120""",
                  """\u0120l""",
                  """\u0120n""",
                  """\u0120lo""",
                  """\u0120low""",
                  """er""",
                  """\u0120lowest""",
                  """\u0120newer""",
                  """\u0120wider""",
                  """<unk>""",
              ]
              __snake_case       	=							dict(zip(_UpperCamelCase      , range(len(_UpperCamelCase   )   )   )   )
              __snake_case       	=							["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
              __snake_case       	=							{"""unk_token""": """<unk>"""}

              __snake_case       	=							os.path.join(self.tmpdirname      , VOCAB_FILES_NAMES["""vocab_file"""]   )
              __snake_case       	=							os.path.join(self.tmpdirname      , VOCAB_FILES_NAMES["""merges_file"""]   )
              with open(self.vocab_file      , """w"""      , encoding="""utf-8"""   ) as fp:
                     fp.write(json.dumps(_UpperCamelCase   ) + """\n"""   )
              with open(self.merges_file      , """w"""      , encoding="""utf-8"""   ) as fp:
                     fp.write("""\n""".join(_UpperCamelCase   )   )


       def 			a		(		self      , **_UpperCamelCase   )      ->							Dict:






              """simple docstring"""


              kwargs.update(self.special_tokens_map   )
              return self.tokenizer_class.from_pretrained(self.tmpdirname      , **_UpperCamelCase   )


       def 			a		(		self      , **_UpperCamelCase   )      ->							int:






              """simple docstring"""


              kwargs.update(self.special_tokens_map   )
              return self.rust_tokenizer_class.from_pretrained(self.tmpdirname      , **_UpperCamelCase   )


       def 			a		(		self      , _UpperCamelCase   )      ->							List[str]:






              """simple docstring"""


              __snake_case       	=							"""lower newer"""
              __snake_case       	=							"""lower newer"""
              return input_text, output_text


       def 			a		(		self   )      ->							Tuple:






              """simple docstring"""


              __snake_case       	=							self.tokenizer_class(self.vocab_file      , self.merges_file      , **self.special_tokens_map   )
              __snake_case       	=							"""lower newer"""
              __snake_case       	=							["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
              __snake_case       	=							tokenizer.tokenize(_UpperCamelCase   )  # , add_prefix_space=True)
              self.assertListEqual(_UpperCamelCase      , _UpperCamelCase   )

              __snake_case       	=							tokens + [tokenizer.unk_token]
              __snake_case       	=							[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
              self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCamelCase   )      , _UpperCamelCase   )


       def 			a		(		self   )      ->							Any:






              """simple docstring"""


              __snake_case       	=							self.get_tokenizer()

              self.assertListEqual(tokenizer.encode("""Hello world!"""      , add_special_tokens=_UpperCamelCase   )      , [0, 3_14_14, 2_32, 3_28, 2]   )
              self.assertListEqual(
                  tokenizer.encode("""Hello world! cécé herlolip 418"""      , add_special_tokens=_UpperCamelCase   )      , [0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2]      , )


       @slow
       def 			a		(		self   )      ->							Optional[int]:






              """simple docstring"""


              __snake_case       	=							self.tokenizer_class.from_pretrained("""allenai/longformer-base-4096"""   )

              __snake_case       	=							tokenizer.encode("""sequence builders"""      , add_special_tokens=_UpperCamelCase   )
              __snake_case       	=							tokenizer.encode("""multi-sequence build"""      , add_special_tokens=_UpperCamelCase   )

              __snake_case       	=							tokenizer.encode(
                  """sequence builders"""      , add_special_tokens=_UpperCamelCase      , add_prefix_space=_UpperCamelCase   )
              __snake_case       	=							tokenizer.encode(
                  """sequence builders"""      , """multi-sequence build"""      , add_special_tokens=_UpperCamelCase      , add_prefix_space=_UpperCamelCase   )

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

              assert encoded_sentence == encoded_text_from_decode
              assert encoded_pair == encoded_pair_from_decode


       def 			a		(		self   )      ->							Union[str, Any]:






              """simple docstring"""


              __snake_case       	=							self.get_tokenizer()

              __snake_case       	=							"""Encode this sequence."""
              __snake_case       	=							tokenizer.byte_encoder[""" """.encode("""utf-8"""   )[0]]

              # Testing encoder arguments
              __snake_case       	=							tokenizer.encode(_UpperCamelCase      , add_special_tokens=_UpperCamelCase      , add_prefix_space=_UpperCamelCase   )
              __snake_case       	=							tokenizer.convert_ids_to_tokens(encoded[0]   )[0]
              self.assertNotEqual(_UpperCamelCase      , _UpperCamelCase   )

              __snake_case       	=							tokenizer.encode(_UpperCamelCase      , add_special_tokens=_UpperCamelCase      , add_prefix_space=_UpperCamelCase   )
              __snake_case       	=							tokenizer.convert_ids_to_tokens(encoded[0]   )[0]
              self.assertEqual(_UpperCamelCase      , _UpperCamelCase   )

              tokenizer.add_special_tokens({"""bos_token""": """<s>"""}   )
              __snake_case       	=							tokenizer.encode(_UpperCamelCase      , add_special_tokens=_UpperCamelCase   )
              __snake_case       	=							tokenizer.convert_ids_to_tokens(encoded[1]   )[0]
              self.assertNotEqual(_UpperCamelCase      , _UpperCamelCase   )

              # Testing spaces after special tokens
              __snake_case       	=							"""<mask>"""
              tokenizer.add_special_tokens(
                  {"""mask_token""": AddedToken(_UpperCamelCase      , lstrip=_UpperCamelCase      , rstrip=_UpperCamelCase   )}   )  # mask token has a left space
              __snake_case       	=							tokenizer.convert_tokens_to_ids(_UpperCamelCase   )

              __snake_case       	=							"""Encode <mask> sequence"""
              __snake_case       	=							"""Encode <mask>sequence"""

              __snake_case       	=							tokenizer.encode(_UpperCamelCase   )
              __snake_case       	=							encoded.index(_UpperCamelCase   )
              __snake_case       	=							tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]   )[0]
              self.assertEqual(_UpperCamelCase      , _UpperCamelCase   )

              __snake_case       	=							tokenizer.encode(_UpperCamelCase   )
              __snake_case       	=							encoded.index(_UpperCamelCase   )
              __snake_case       	=							tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]   )[0]
              self.assertNotEqual(_UpperCamelCase      , _UpperCamelCase   )


       def 			a		(		self   )      ->							Dict:






              """simple docstring"""


              pass


       def 			a		(		self   )      ->							Union[str, Any]:






              """simple docstring"""


              for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                     with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'   ):
                            __snake_case       	=							self.rust_tokenizer_class.from_pretrained(_UpperCamelCase      , **_UpperCamelCase   )
                            __snake_case       	=							self.tokenizer_class.from_pretrained(_UpperCamelCase      , **_UpperCamelCase   )
                            __snake_case       	=							"""A, <mask> AllenNLP sentence."""
                            __snake_case       	=							tokenizer_r.encode_plus(_UpperCamelCase      , add_special_tokens=_UpperCamelCase      , return_token_type_ids=_UpperCamelCase   )
                            __snake_case       	=							tokenizer_p.encode_plus(_UpperCamelCase      , add_special_tokens=_UpperCamelCase      , return_token_type_ids=_UpperCamelCase   )

                            # token_type_ids should put 0 everywhere
                            self.assertEqual(sum(tokens_r["""token_type_ids"""]   )      , sum(tokens_p["""token_type_ids"""]   )   )

                            # attention_mask should put 1 everywhere, so sum over length should be 1
                            self.assertEqual(
                                sum(tokens_r["""attention_mask"""]   ) / len(tokens_r["""attention_mask"""]   )      , sum(tokens_p["""attention_mask"""]   ) / len(tokens_p["""attention_mask"""]   )      , )

                            __snake_case       	=							tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]   )
                            __snake_case       	=							tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]   )

                            # Rust correctly handles the space before the mask while python doesnt
                            self.assertSequenceEqual(tokens_p["""input_ids"""]      , [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]   )
                            self.assertSequenceEqual(tokens_r["""input_ids"""]      , [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]   )

                            self.assertSequenceEqual(
                                _UpperCamelCase      , ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]   )
                            self.assertSequenceEqual(
                                _UpperCamelCase      , ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]   )


       def 			a		(		self   )      ->							int:






              """simple docstring"""


              for trim_offsets, add_prefix_space in itertools.product([True, False]      , repeat=2   ):
                     __snake_case       	=							self.rust_tokenizer_class.from_pretrained(
                         self.tmpdirname      , use_fast=_UpperCamelCase      , add_prefix_space=_UpperCamelCase      , trim_offsets=_UpperCamelCase   )

                     __snake_case       	=							json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()   )
                     __snake_case       	=							json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()   )

                     self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]      , _UpperCamelCase   )

                     self.assertEqual(post_processor_state["""add_prefix_space"""]      , _UpperCamelCase   )
                     self.assertEqual(post_processor_state["""trim_offsets"""]      , _UpperCamelCase   )






       def 			a		(		self   )      ->							Optional[Any]:






              """simple docstring"""


              for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                     with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'   ):
                            __snake_case       	=							"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
                            __snake_case       	=							F'{text_of_1_token} {text_of_1_token}'

                            __snake_case       	=							self.rust_tokenizer_class.from_pretrained(
                                _UpperCamelCase      , use_fast=_UpperCamelCase      , add_prefix_space=_UpperCamelCase      , trim_offsets=_UpperCamelCase   )
                            __snake_case       	=							tokenizer_r(_UpperCamelCase      , return_offsets_mapping=_UpperCamelCase      , add_special_tokens=_UpperCamelCase   )
                            self.assertEqual(encoding.offset_mapping[0]      , (0, len(_UpperCamelCase   ))   )
                            self.assertEqual(
                                encoding.offset_mapping[1]      , (len(_UpperCamelCase   ) + 1, len(_UpperCamelCase   ) + 1 + len(_UpperCamelCase   ))      , )

                            __snake_case       	=							self.rust_tokenizer_class.from_pretrained(
                                _UpperCamelCase      , use_fast=_UpperCamelCase      , add_prefix_space=_UpperCamelCase      , trim_offsets=_UpperCamelCase   )
                            __snake_case       	=							tokenizer_r(_UpperCamelCase      , return_offsets_mapping=_UpperCamelCase      , add_special_tokens=_UpperCamelCase   )
                            self.assertEqual(encoding.offset_mapping[0]      , (0, len(_UpperCamelCase   ))   )
                            self.assertEqual(
                                encoding.offset_mapping[1]      , (len(_UpperCamelCase   ) + 1, len(_UpperCamelCase   ) + 1 + len(_UpperCamelCase   ))      , )

                            __snake_case       	=							self.rust_tokenizer_class.from_pretrained(
                                _UpperCamelCase      , use_fast=_UpperCamelCase      , add_prefix_space=_UpperCamelCase      , trim_offsets=_UpperCamelCase   )
                            __snake_case       	=							tokenizer_r(_UpperCamelCase      , return_offsets_mapping=_UpperCamelCase      , add_special_tokens=_UpperCamelCase   )
                            self.assertEqual(encoding.offset_mapping[0]      , (0, len(_UpperCamelCase   ))   )
                            self.assertEqual(
                                encoding.offset_mapping[1]      , (len(_UpperCamelCase   ), len(_UpperCamelCase   ) + 1 + len(_UpperCamelCase   ))      , )

                            __snake_case       	=							self.rust_tokenizer_class.from_pretrained(
                                _UpperCamelCase      , use_fast=_UpperCamelCase      , add_prefix_space=_UpperCamelCase      , trim_offsets=_UpperCamelCase   )
                            __snake_case       	=							tokenizer_r(_UpperCamelCase      , return_offsets_mapping=_UpperCamelCase      , add_special_tokens=_UpperCamelCase   )
                            self.assertEqual(encoding.offset_mapping[0]      , (0, len(_UpperCamelCase   ))   )
                            self.assertEqual(
                                encoding.offset_mapping[1]      , (len(_UpperCamelCase   ), len(_UpperCamelCase   ) + 1 + len(_UpperCamelCase   ))      , )

                            __snake_case       	=							F' {text}'

                            # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
                            #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
                            # )
                            # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
                            # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
                            # self.assertEqual(
                            #     encoding.offset_mapping[1],
                            #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
                            # )

                            __snake_case       	=							self.rust_tokenizer_class.from_pretrained(
                                _UpperCamelCase      , use_fast=_UpperCamelCase      , add_prefix_space=_UpperCamelCase      , trim_offsets=_UpperCamelCase   )
                            __snake_case       	=							tokenizer_r(_UpperCamelCase      , return_offsets_mapping=_UpperCamelCase      , add_special_tokens=_UpperCamelCase   )
                            self.assertEqual(encoding.offset_mapping[0]      , (1, 1 + len(_UpperCamelCase   ))   )
                            self.assertEqual(
                                encoding.offset_mapping[1]      , (1 + len(_UpperCamelCase   ) + 1, 1 + len(_UpperCamelCase   ) + 1 + len(_UpperCamelCase   ))      , )

                            __snake_case       	=							self.rust_tokenizer_class.from_pretrained(
                                _UpperCamelCase      , use_fast=_UpperCamelCase      , add_prefix_space=_UpperCamelCase      , trim_offsets=_UpperCamelCase   )
                            __snake_case       	=							tokenizer_r(_UpperCamelCase      , return_offsets_mapping=_UpperCamelCase      , add_special_tokens=_UpperCamelCase   )
                            self.assertEqual(encoding.offset_mapping[0]      , (0, 1 + len(_UpperCamelCase   ))   )
                            self.assertEqual(
                                encoding.offset_mapping[1]      , (1 + len(_UpperCamelCase   ), 1 + len(_UpperCamelCase   ) + 1 + len(_UpperCamelCase   ))      , )

                            __snake_case       	=							self.rust_tokenizer_class.from_pretrained(
                                _UpperCamelCase      , use_fast=_UpperCamelCase      , add_prefix_space=_UpperCamelCase      , trim_offsets=_UpperCamelCase   )
                            __snake_case       	=							tokenizer_r(_UpperCamelCase      , return_offsets_mapping=_UpperCamelCase      , add_special_tokens=_UpperCamelCase   )
                            self.assertEqual(encoding.offset_mapping[0]      , (0, 1 + len(_UpperCamelCase   ))   )
                            self.assertEqual(
                                encoding.offset_mapping[1]      , (1 + len(_UpperCamelCase   ), 1 + len(_UpperCamelCase   ) + 1 + len(_UpperCamelCase   ))      , )




from __future__ import annotations

class     __snake_case    :
       """simple docstring"""







       def __init__(		self      , _UpperCamelCase      , _UpperCamelCase   )      ->							Tuple:






              """simple docstring"""


              __snake_case	,    __snake_case       	=							text, pattern
              __snake_case	,    __snake_case       	=							len(_UpperCamelCase   ), len(_UpperCamelCase   )


       def 			a		(		self      , _UpperCamelCase   )      ->							int:






              """simple docstring"""


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


       def 			a		(		self      , _UpperCamelCase   )      ->							int:






              """simple docstring"""


              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 			a		(		self   )      ->							list[int]:






              """simple docstring"""


              __snake_case       	=							[]
              for i in range(self.textLen - self.patLen + 1   ):
                     __snake_case       	=							self.mismatch_in_text(_UpperCamelCase   )
                     if mismatch_index == -1:
                            positions.append(_UpperCamelCase   )
                     else:
                            __snake_case       	=							self.match_in_pattern(self.text[mismatch_index]   )
                            __snake_case       	=							(
                                mismatch_index - match_index
                            )  # shifting index lgtm [py/multiple-definition]
              return positions






UpperCamelCase__		 =     '''ABAABA'''
UpperCamelCase__		 =     '''AB'''
UpperCamelCase__		 =     BoyerMooreSearch(text, pattern)
UpperCamelCase__		 =     bms.bad_character_heuristic()

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

