
'''simple docstring'''






import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class  UpperCAmelCase__						(       A						,	unittest.TestCase ):
    lowerCAmelCase_				    =		RobertaTokenizer
    lowerCAmelCase_				    =		RobertaTokenizerFast
    lowerCAmelCase_				    =		True
    lowerCAmelCase_				    =		{'cls_token': '<s>'}



    def   lowerCamelCase_  (	self      :       Tuple     ):
          super().setUp()

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

          _lowerCamelCase				:   List[str]								=   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",encoding="utf-8"     ) as fp:
                fp.write(json.dumps(__A     ) + "\n"     )
          with open(self.merges_file,"w",encoding="utf-8"     ) as fp:
                fp.write("\n".join(__A     )     )



    def   lowerCamelCase_  (	self      :       Dict,**__A      :       Union[str, Any]     ):
          kwargs.update(self.special_tokens_map     )
          return self.tokenizer_class.from_pretrained(self.tmpdirname,**__A     )



    def   lowerCamelCase_  (	self      :       str,**__A      :       Optional[int]     ):
          kwargs.update(self.special_tokens_map     )
          return RobertaTokenizerFast.from_pretrained(self.tmpdirname,**__A     )



    def   lowerCamelCase_  (	self      :       Optional[Any],__A      :       List[Any]     ):
          _lowerCamelCase				:   Tuple								=   "lower newer"
          _lowerCamelCase				:   Optional[int]								=   "lower newer"
          return input_text, output_text



    def   lowerCamelCase_  (	self      :       Optional[int]     ):
          _lowerCamelCase				:   List[Any]								=   self.tokenizer_class(self.vocab_file,self.merges_file,**self.special_tokens_map     )
          _lowerCamelCase				:   int								=   "lower newer"
          _lowerCamelCase				:   int								=   ["l", "o", "w", "er", "\u0120", "n", "e", "w", "er"]
          _lowerCamelCase				:   Dict								=   tokenizer.tokenize(__A     )  # , add_prefix_space=True)
          self.assertListEqual(__A,__A     )

          _lowerCamelCase				:   Tuple								=   tokens + [tokenizer.unk_token]
          _lowerCamelCase				:   Optional[Any]								=   [0, 1, 2, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(__A     ),__A     )



    def   lowerCamelCase_  (	self      :       Optional[Any]     ):
          _lowerCamelCase				:   Dict								=   self.get_tokenizer()

          self.assertListEqual(tokenizer.encode("Hello world!",add_special_tokens=__A     ),[0, 3_1_4_1_4, 2_3_2, 3_2_8, 2]     )
          self.assertListEqual(
              tokenizer.encode("Hello world! cécé herlolip 418",add_special_tokens=__A     ),[0, 3_1_4_1_4, 2_3_2, 3_2_8, 7_4_0, 1_1_4_0, 1_2_6_9_5, 6_9, 4_6_0_7_8, 1_5_8_8, 2],)



    @slow
    def   lowerCamelCase_  (	self      :       Any     ):
          _lowerCamelCase				:   int								=   self.tokenizer_class.from_pretrained("roberta-base"     )

          _lowerCamelCase				:   List[str]								=   tokenizer.encode("sequence builders",add_special_tokens=__A     )
          _lowerCamelCase				:   Tuple								=   tokenizer.encode("multi-sequence build",add_special_tokens=__A     )

          _lowerCamelCase				:   Optional[int]								=   tokenizer.encode(
              "sequence builders",add_special_tokens=__A,add_prefix_space=__A     )
          _lowerCamelCase				:   List[str]								=   tokenizer.encode(
              "sequence builders","multi-sequence build",add_special_tokens=__A,add_prefix_space=__A     )

          _lowerCamelCase				:   Tuple								=   tokenizer.build_inputs_with_special_tokens(__A     )
          _lowerCamelCase				:   Optional[Any]								=   tokenizer.build_inputs_with_special_tokens(__A,__A     )

          assert encoded_sentence == encoded_text_from_decode
          assert encoded_pair == encoded_pair_from_decode



    def   lowerCamelCase_  (	self      :       List[Any]     ):
          _lowerCamelCase				:   Union[str, Any]								=   self.get_tokenizer()

          _lowerCamelCase				:   int								=   "Encode this sequence."
          _lowerCamelCase				:   Union[str, Any]								=   tokenizer.byte_encoder[" ".encode("utf-8"     )[0]]

          # Testing encoder arguments
          _lowerCamelCase				:   Optional[Any]								=   tokenizer.encode(__A,add_special_tokens=__A,add_prefix_space=__A     )
          _lowerCamelCase				:   int								=   tokenizer.convert_ids_to_tokens(encoded[0]     )[0]
          self.assertNotEqual(__A,__A     )

          _lowerCamelCase				:   List[Any]								=   tokenizer.encode(__A,add_special_tokens=__A,add_prefix_space=__A     )
          _lowerCamelCase				:   Dict								=   tokenizer.convert_ids_to_tokens(encoded[0]     )[0]
          self.assertEqual(__A,__A     )

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

          # Testing spaces after special tokens
          _lowerCamelCase				:   str								=   "<mask>"
          tokenizer.add_special_tokens(
              {"mask_token": AddedToken(__A,lstrip=__A,rstrip=__A     )}     )  # mask token has a left space
          _lowerCamelCase				:   List[Any]								=   tokenizer.convert_tokens_to_ids(__A     )

          _lowerCamelCase				:   str								=   "Encode <mask> sequence"
          _lowerCamelCase				:   Optional[int]								=   "Encode <mask>sequence"

          _lowerCamelCase				:   int								=   tokenizer.encode(__A     )
          _lowerCamelCase				:   Any								=   encoded.index(__A     )
          _lowerCamelCase				:   Union[str, Any]								=   tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]     )[0]
          self.assertEqual(__A,__A     )

          _lowerCamelCase				:   Any								=   tokenizer.encode(__A     )
          _lowerCamelCase				:   Dict								=   encoded.index(__A     )
          _lowerCamelCase				:   List[str]								=   tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]     )[0]
          self.assertNotEqual(__A,__A     )



    def   lowerCamelCase_  (	self      :       int     ):
          pass



    def   lowerCamelCase_  (	self      :       Optional[Any]     ):
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'     ):
                      _lowerCamelCase				:   Dict								=   self.rust_tokenizer_class.from_pretrained(__A,**__A     )
                      _lowerCamelCase				:   int								=   self.tokenizer_class.from_pretrained(__A,**__A     )
                      _lowerCamelCase				:   int								=   "A, <mask> AllenNLP sentence."
                      _lowerCamelCase				:   Tuple								=   tokenizer_r.encode_plus(__A,add_special_tokens=__A,return_token_type_ids=__A     )
                      _lowerCamelCase				:   str								=   tokenizer_p.encode_plus(__A,add_special_tokens=__A,return_token_type_ids=__A     )

                      # 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"]     ),)

                      _lowerCamelCase				:   Union[str, Any]								=   tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]     )
                      _lowerCamelCase				:   str								=   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_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]     )
                      self.assertSequenceEqual(tokens_r["input_ids"],[0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]     )

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



    def   lowerCamelCase_  (	self      :       List[Any]     ):
          for trim_offsets, add_prefix_space in itertools.product([True, False],repeat=2     ):
                _lowerCamelCase				:   Any								=   self.rust_tokenizer_class.from_pretrained(
                    self.tmpdirname,use_fast=__A,add_prefix_space=__A,trim_offsets=__A     )

                _lowerCamelCase				:   Tuple								=   json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()     )
                _lowerCamelCase				:   Union[str, Any]								=   json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()     )

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

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



    def   lowerCamelCase_  (	self      :       List[Any]     ):
          # Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
          # `trim_offsets`
          for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'     ):
                      _lowerCamelCase				:   List[Any]								=   "hello"  # `hello` is a token in the vocabulary of `pretrained_name`
                      _lowerCamelCase				:   List[Any]								=   f'{text_of_1_token} {text_of_1_token}'

                      _lowerCamelCase				:   Optional[int]								=   self.rust_tokenizer_class.from_pretrained(
                          __A,use_fast=__A,add_prefix_space=__A,trim_offsets=__A     )
                      _lowerCamelCase				:   Optional[Any]								=   tokenizer_r(__A,return_offsets_mapping=__A,add_special_tokens=__A     )
                      self.assertEqual(encoding.offset_mapping[0],(0, len(__A     ))     )
                      self.assertEqual(
                          encoding.offset_mapping[1],(len(__A     ) + 1, len(__A     ) + 1 + len(__A     )),)

                      _lowerCamelCase				:   Union[str, Any]								=   self.rust_tokenizer_class.from_pretrained(
                          __A,use_fast=__A,add_prefix_space=__A,trim_offsets=__A     )
                      _lowerCamelCase				:   int								=   tokenizer_r(__A,return_offsets_mapping=__A,add_special_tokens=__A     )
                      self.assertEqual(encoding.offset_mapping[0],(0, len(__A     ))     )
                      self.assertEqual(
                          encoding.offset_mapping[1],(len(__A     ) + 1, len(__A     ) + 1 + len(__A     )),)

                      _lowerCamelCase				:   Any								=   self.rust_tokenizer_class.from_pretrained(
                          __A,use_fast=__A,add_prefix_space=__A,trim_offsets=__A     )
                      _lowerCamelCase				:   str								=   tokenizer_r(__A,return_offsets_mapping=__A,add_special_tokens=__A     )
                      self.assertEqual(encoding.offset_mapping[0],(0, len(__A     ))     )
                      self.assertEqual(
                          encoding.offset_mapping[1],(len(__A     ), len(__A     ) + 1 + len(__A     )),)

                      _lowerCamelCase				:   Dict								=   self.rust_tokenizer_class.from_pretrained(
                          __A,use_fast=__A,add_prefix_space=__A,trim_offsets=__A     )
                      _lowerCamelCase				:   List[str]								=   tokenizer_r(__A,return_offsets_mapping=__A,add_special_tokens=__A     )
                      self.assertEqual(encoding.offset_mapping[0],(0, len(__A     ))     )
                      self.assertEqual(
                          encoding.offset_mapping[1],(len(__A     ), len(__A     ) + 1 + len(__A     )),)

                      _lowerCamelCase				:   Optional[Any]								=   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)),
                      # )

                      _lowerCamelCase				:   Union[str, Any]								=   self.rust_tokenizer_class.from_pretrained(
                          __A,use_fast=__A,add_prefix_space=__A,trim_offsets=__A     )
                      _lowerCamelCase				:   Optional[Any]								=   tokenizer_r(__A,return_offsets_mapping=__A,add_special_tokens=__A     )
                      self.assertEqual(encoding.offset_mapping[0],(1, 1 + len(__A     ))     )
                      self.assertEqual(
                          encoding.offset_mapping[1],(1 + len(__A     ) + 1, 1 + len(__A     ) + 1 + len(__A     )),)

                      _lowerCamelCase				:   List[Any]								=   self.rust_tokenizer_class.from_pretrained(
                          __A,use_fast=__A,add_prefix_space=__A,trim_offsets=__A     )
                      _lowerCamelCase				:   str								=   tokenizer_r(__A,return_offsets_mapping=__A,add_special_tokens=__A     )
                      self.assertEqual(encoding.offset_mapping[0],(0, 1 + len(__A     ))     )
                      self.assertEqual(
                          encoding.offset_mapping[1],(1 + len(__A     ), 1 + len(__A     ) + 1 + len(__A     )),)

                      _lowerCamelCase				:   int								=   self.rust_tokenizer_class.from_pretrained(
                          __A,use_fast=__A,add_prefix_space=__A,trim_offsets=__A     )
                      _lowerCamelCase				:   Optional[Any]								=   tokenizer_r(__A,return_offsets_mapping=__A,add_special_tokens=__A     )
                      self.assertEqual(encoding.offset_mapping[0],(0, 1 + len(__A     ))     )
                      self.assertEqual(
                          encoding.offset_mapping[1],(1 + len(__A     ), 1 + len(__A     ) + 1 + len(__A     )),)

'''simple docstring'''






def 		A_       (	_lowerCAmelCase   :    float							):



      """simple docstring"""




      return 10 - x * x







def 		A_       (	_lowerCAmelCase   :    float				,	_lowerCAmelCase   :    float							):



      """simple docstring"""




      if equation(_lowerCAmelCase							) * equation(_lowerCAmelCase							) >= 0:
            raise ValueError("Wrong space!"							)

      _lowerCamelCase				:   List[str]								=   a
      while (b - a) >= 0.0_1:
            # Find middle point
            _lowerCamelCase				:   Union[str, Any]								=   (a + b) / 2
            # Check if middle point is root
            if equation(_lowerCAmelCase							) == 0.0:
                  break
            # Decide the side to repeat the steps
            if equation(_lowerCAmelCase							) * equation(_lowerCAmelCase							) < 0:
                  _lowerCamelCase				:   Union[str, Any]								=   c
            else:
                  _lowerCamelCase				:   Any								=   c
      return c


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 print(bisection(-2, 5))
 print(bisection(0, 6))