




"""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     __magic_name__							(       UpperCAmelCase__						,					unittest.TestCase				):






				'''simple docstring'''
				__UpperCamelCase			  =						RobertaTokenizer
				__UpperCamelCase			  =						RobertaTokenizerFast
				__UpperCamelCase			  =						True
				__UpperCamelCase			  =						{"cls_token": "<s>"}





				def    _lowerCAmelCase				(       self ):





							"""simple docstring"""
							super().setUp()

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

							lowerCamelCase			      =					os.path.join(self.tmpdirname		, VOCAB_FILES_NAMES["""vocab_file"""] )
							lowerCamelCase			      =					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		, **_a ):





							"""simple docstring"""
							kwargs.update(self.special_tokens_map )
							return self.tokenizer_class.from_pretrained(self.tmpdirname		, **_a )





				def    _lowerCAmelCase				(       self		, **_a ):





							"""simple docstring"""
							kwargs.update(self.special_tokens_map )
							return RobertaTokenizerFast.from_pretrained(self.tmpdirname		, **_a )





				def    _lowerCAmelCase				(       self		, _a ):





							"""simple docstring"""
							lowerCamelCase			      =					"""lower newer"""
							lowerCamelCase			      =					"""lower newer"""
							return input_text, output_text





				def    _lowerCAmelCase				(       self ):





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

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





				def    _lowerCAmelCase				(       self ):





							"""simple docstring"""
							lowerCamelCase			      =					self.get_tokenizer()

							self.assertListEqual(tokenizer.encode("""Hello world!"""		, add_special_tokens=_a )		, [0, 31_414, 232, 328, 2] )
							self.assertListEqual(
							    tokenizer.encode("""Hello world! cécé herlolip 418"""		, add_special_tokens=_a )		, [0, 31_414, 232, 328, 740, 1_140, 12_695, 69, 46_078, 1_588, 2]		, )





				@slow
				def    _lowerCAmelCase				(       self ):





							"""simple docstring"""
							lowerCamelCase			      =					self.tokenizer_class.from_pretrained("""roberta-base""" )

							lowerCamelCase			      =					tokenizer.encode("""sequence builders"""		, add_special_tokens=_a )
							lowerCamelCase			      =					tokenizer.encode("""multi-sequence build"""		, add_special_tokens=_a )

							lowerCamelCase			      =					tokenizer.encode(
							    """sequence builders"""		, add_special_tokens=_a		, add_prefix_space=_a )
							lowerCamelCase			      =					tokenizer.encode(
							    """sequence builders"""		, """multi-sequence build"""		, add_special_tokens=_a		, add_prefix_space=_a )

							lowerCamelCase			      =					tokenizer.build_inputs_with_special_tokens(_a )
							lowerCamelCase			      =					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 ):





							"""simple docstring"""
							lowerCamelCase			      =					self.get_tokenizer()

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

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

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

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

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

							lowerCamelCase			      =					"""Encode <mask> sequence"""
							lowerCamelCase			      =					"""Encode <mask>sequence"""

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

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





				def    _lowerCAmelCase				(       self ):





							"""simple docstring"""
							pass





				def    _lowerCAmelCase				(       self ):





							"""simple docstring"""
							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
										with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})' ):
													lowerCamelCase			      =					self.rust_tokenizer_class.from_pretrained(_a		, **_a )
													lowerCamelCase			      =					self.tokenizer_class.from_pretrained(_a		, **_a )
													lowerCamelCase			      =					"""A, <mask> AllenNLP sentence."""
													lowerCamelCase			      =					tokenizer_r.encode_plus(_a		, add_special_tokens=_a		, return_token_type_ids=_a )
													lowerCamelCase			      =					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			      =					tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""] )
													lowerCamelCase			      =					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, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2] )
													self.assertSequenceEqual(tokens_r["""input_ids"""]		, [0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 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 ):





							"""simple docstring"""
							for trim_offsets, add_prefix_space in itertools.product([True, False]		, repeat=2 ):
										lowerCamelCase			      =					self.rust_tokenizer_class.from_pretrained(
										    self.tmpdirname		, use_fast=_a		, add_prefix_space=_a		, trim_offsets=_a )

										lowerCamelCase			      =					json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__() )
										lowerCamelCase			      =					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 ):





							"""simple docstring"""
							# 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			      =					"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
													lowerCamelCase			      =					f'{text_of_1_token} {text_of_1_token}'

													lowerCamelCase			      =					self.rust_tokenizer_class.from_pretrained(
													    _a		, use_fast=_a		, add_prefix_space=_a		, trim_offsets=_a )
													lowerCamelCase			      =					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			      =					self.rust_tokenizer_class.from_pretrained(
													    _a		, use_fast=_a		, add_prefix_space=_a		, trim_offsets=_a )
													lowerCamelCase			      =					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			      =					self.rust_tokenizer_class.from_pretrained(
													    _a		, use_fast=_a		, add_prefix_space=_a		, trim_offsets=_a )
													lowerCamelCase			      =					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			      =					self.rust_tokenizer_class.from_pretrained(
													    _a		, use_fast=_a		, add_prefix_space=_a		, trim_offsets=_a )
													lowerCamelCase			      =					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			      =					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			      =					self.rust_tokenizer_class.from_pretrained(
													    _a		, use_fast=_a		, add_prefix_space=_a		, trim_offsets=_a )
													lowerCamelCase			      =					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			      =					self.rust_tokenizer_class.from_pretrained(
													    _a		, use_fast=_a		, add_prefix_space=_a		, trim_offsets=_a )
													lowerCamelCase			      =					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			      =					self.rust_tokenizer_class.from_pretrained(
													    _a		, use_fast=_a		, add_prefix_space=_a		, trim_offsets=_a )
													lowerCamelCase			      =					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"""




from __future__ import annotations



def     a__ (				snake_case__       , snake_case__				)						->					bool:
			if len(snake_case__				) == 0:
						return False
			lowerCamelCase			      =					len(snake_case__				) // 2
			if a_list[midpoint] == item:
						return True
			if item < a_list[midpoint]:
						return binary_search(a_list[:midpoint]       , snake_case__				)
			else:
						return binary_search(a_list[midpoint + 1 :]       , snake_case__				)


if __name__ == "__main__":
					lowerCAmelCase							:			List[Any]     							=							input("""Enter numbers separated by comma:\n""").strip()
					lowerCAmelCase							:			Optional[Any]     							=							[int(item.strip()) for item in user_input.split(""",""")]
					lowerCAmelCase							:			Optional[int]     							=							int(input("""Enter the number to be found in the list:\n""").strip())
					lowerCAmelCase							:			Union[str, Any]     							=							"""""" if binary_search(sequence, target) else """not """
					print(F"""{target} was {not_str}found in {sequence}""")



