




'''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 				_a							(       SCREAMING_SNAKE_CASE__      ,	unittest.TestCase      ):





       '''simple docstring'''






       A		:							Any								=		RobertaTokenizer
       A		:							List[str]								=		RobertaTokenizerFast
       A		:							Tuple								=		True
       A		:							List[Any]								=		{'''cls_token''': '''<s>'''}







       def     UpperCamelCase_				(	self   ):







             '''simple docstring'''







             super().setUp()

             # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
             SCREAMING_SNAKE_CASE					:	int   =		[
                 '''l''',
                 '''o''',
                 '''w''',
                 '''e''',
                 '''r''',
                 '''s''',
                 '''t''',
                 '''i''',
                 '''d''',
                 '''n''',
                 '''\u0120''',
                 '''\u0120l''',
                 '''\u0120n''',
                 '''\u0120lo''',
                 '''\u0120low''',
                 '''er''',
                 '''\u0120lowest''',
                 '''\u0120newer''',
                 '''\u0120wider''',
                 '''<unk>''',
             ]
             SCREAMING_SNAKE_CASE					:	Any   =		dict(zip(__lowerCamelCase,				range(len(__lowerCamelCase   )   )   )   )
             SCREAMING_SNAKE_CASE					:	List[str]   =		['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
             SCREAMING_SNAKE_CASE					:	Optional[Any]   =		{'''unk_token''': '''<unk>'''}

             SCREAMING_SNAKE_CASE					:	Optional[int]   =		os.path.join(self.tmpdirname,				VOCAB_FILES_NAMES['vocab_file']   )
             SCREAMING_SNAKE_CASE					:	Optional[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(__lowerCamelCase   ) + '\n'   )
             with open(self.merges_file,				'w',				encoding='utf-8'   ) as fp:
                   fp.write('\n'.join(__lowerCamelCase   )   )







       def     UpperCamelCase_				(	self,				**A   ):







             '''simple docstring'''







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







       def     UpperCamelCase_				(	self,				**A   ):







             '''simple docstring'''







             kwargs.update(self.special_tokens_map   )
             return RobertaTokenizerFast.from_pretrained(self.tmpdirname,				**__lowerCamelCase   )







       def     UpperCamelCase_				(	self,				A   ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE					:	int   =		'''lower newer'''
             SCREAMING_SNAKE_CASE					:	str   =		'''lower newer'''
             return input_text, output_text







       def     UpperCamelCase_				(	self   ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE					:	List[Any]   =		self.tokenizer_class(self.vocab_file,				self.merges_file,				**self.special_tokens_map   )
             SCREAMING_SNAKE_CASE					:	Optional[Any]   =		'''lower newer'''
             SCREAMING_SNAKE_CASE					:	Union[str, Any]   =		['''l''', '''o''', '''w''', '''er''', '''\u0120''', '''n''', '''e''', '''w''', '''er''']
             SCREAMING_SNAKE_CASE					:	str   =		tokenizer.tokenize(__lowerCamelCase   )  # , add_prefix_space=True)
             self.assertListEqual(__lowerCamelCase,				__lowerCamelCase   )

             SCREAMING_SNAKE_CASE					:	List[Any]   =		tokens + [tokenizer.unk_token]
             SCREAMING_SNAKE_CASE					:	Tuple   =		[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
             self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase   ),				__lowerCamelCase   )







       def     UpperCamelCase_				(	self   ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE					:	List[Any]   =		self.get_tokenizer()

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







       @slow
       def     UpperCamelCase_				(	self   ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE					:	Union[str, Any]   =		self.tokenizer_class.from_pretrained('roberta-base'   )

             SCREAMING_SNAKE_CASE					:	Any   =		tokenizer.encode('sequence builders',				add_special_tokens=__lowerCamelCase   )
             SCREAMING_SNAKE_CASE					:	int   =		tokenizer.encode('multi-sequence build',				add_special_tokens=__lowerCamelCase   )

             SCREAMING_SNAKE_CASE					:	str   =		tokenizer.encode(
                 'sequence builders',				add_special_tokens=__lowerCamelCase,				add_prefix_space=__lowerCamelCase   )
             SCREAMING_SNAKE_CASE					:	List[Any]   =		tokenizer.encode(
                 'sequence builders',				'multi-sequence build',				add_special_tokens=__lowerCamelCase,				add_prefix_space=__lowerCamelCase   )

             SCREAMING_SNAKE_CASE					:	Dict   =		tokenizer.build_inputs_with_special_tokens(__lowerCamelCase   )
             SCREAMING_SNAKE_CASE					:	Tuple   =		tokenizer.build_inputs_with_special_tokens(__lowerCamelCase,				__lowerCamelCase   )

             assert encoded_sentence == encoded_text_from_decode
             assert encoded_pair == encoded_pair_from_decode







       def     UpperCamelCase_				(	self   ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE					:	List[str]   =		self.get_tokenizer()

             SCREAMING_SNAKE_CASE					:	Optional[int]   =		'''Encode this sequence.'''
             SCREAMING_SNAKE_CASE					:	List[Any]   =		tokenizer.byte_encoder[''' '''.encode('utf-8'   )[0]]

             # Testing encoder arguments
             SCREAMING_SNAKE_CASE					:	Tuple   =		tokenizer.encode(__lowerCamelCase,				add_special_tokens=__lowerCamelCase,				add_prefix_space=__lowerCamelCase   )
             SCREAMING_SNAKE_CASE					:	int   =		tokenizer.convert_ids_to_tokens(encoded[0]   )[0]
             self.assertNotEqual(__lowerCamelCase,				__lowerCamelCase   )

             SCREAMING_SNAKE_CASE					:	Optional[int]   =		tokenizer.encode(__lowerCamelCase,				add_special_tokens=__lowerCamelCase,				add_prefix_space=__lowerCamelCase   )
             SCREAMING_SNAKE_CASE					:	Dict   =		tokenizer.convert_ids_to_tokens(encoded[0]   )[0]
             self.assertEqual(__lowerCamelCase,				__lowerCamelCase   )

             tokenizer.add_special_tokens({'bos_token': '<s>'}   )
             SCREAMING_SNAKE_CASE					:	List[str]   =		tokenizer.encode(__lowerCamelCase,				add_special_tokens=__lowerCamelCase   )
             SCREAMING_SNAKE_CASE					:	str   =		tokenizer.convert_ids_to_tokens(encoded[1]   )[0]
             self.assertNotEqual(__lowerCamelCase,				__lowerCamelCase   )

             # Testing spaces after special tokens
             SCREAMING_SNAKE_CASE					:	Dict   =		'''<mask>'''
             tokenizer.add_special_tokens(
                 {'mask_token': AddedToken(__lowerCamelCase,				lstrip=__lowerCamelCase,				rstrip=__lowerCamelCase   )}   )  # mask token has a left space
             SCREAMING_SNAKE_CASE					:	Any   =		tokenizer.convert_tokens_to_ids(__lowerCamelCase   )

             SCREAMING_SNAKE_CASE					:	Optional[int]   =		'''Encode <mask> sequence'''
             SCREAMING_SNAKE_CASE					:	int   =		'''Encode <mask>sequence'''

             SCREAMING_SNAKE_CASE					:	Tuple   =		tokenizer.encode(__lowerCamelCase   )
             SCREAMING_SNAKE_CASE					:	str   =		encoded.index(__lowerCamelCase   )
             SCREAMING_SNAKE_CASE					:	Any   =		tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]   )[0]
             self.assertEqual(__lowerCamelCase,				__lowerCamelCase   )

             SCREAMING_SNAKE_CASE					:	Union[str, Any]   =		tokenizer.encode(__lowerCamelCase   )
             SCREAMING_SNAKE_CASE					:	Union[str, Any]   =		encoded.index(__lowerCamelCase   )
             SCREAMING_SNAKE_CASE					:	Any   =		tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]   )[0]
             self.assertNotEqual(__lowerCamelCase,				__lowerCamelCase   )







       def     UpperCamelCase_				(	self   ):







             '''simple docstring'''







             pass







       def     UpperCamelCase_				(	self   ):







             '''simple docstring'''







             for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                   with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"   ):
                         SCREAMING_SNAKE_CASE					:	Optional[int]   =		self.rust_tokenizer_class.from_pretrained(__lowerCamelCase,				**__lowerCamelCase   )
                         SCREAMING_SNAKE_CASE					:	List[Any]   =		self.tokenizer_class.from_pretrained(__lowerCamelCase,				**__lowerCamelCase   )
                         SCREAMING_SNAKE_CASE					:	int   =		'''A, <mask> AllenNLP sentence.'''
                         SCREAMING_SNAKE_CASE					:	int   =		tokenizer_r.encode_plus(__lowerCamelCase,				add_special_tokens=__lowerCamelCase,				return_token_type_ids=__lowerCamelCase   )
                         SCREAMING_SNAKE_CASE					:	Tuple   =		tokenizer_p.encode_plus(__lowerCamelCase,				add_special_tokens=__lowerCamelCase,				return_token_type_ids=__lowerCamelCase   )

                         # 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']   ),				)

                         SCREAMING_SNAKE_CASE					:	Tuple   =		tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']   )
                         SCREAMING_SNAKE_CASE					:	Optional[int]   =		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(
                             __lowerCamelCase,				['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']   )
                         self.assertSequenceEqual(
                             __lowerCamelCase,				['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']   )







       def     UpperCamelCase_				(	self   ):







             '''simple docstring'''







             for trim_offsets, add_prefix_space in itertools.product([True, False],				repeat=2   ):
                   SCREAMING_SNAKE_CASE					:	Optional[Any]   =		self.rust_tokenizer_class.from_pretrained(
                       self.tmpdirname,				use_fast=__lowerCamelCase,				add_prefix_space=__lowerCamelCase,				trim_offsets=__lowerCamelCase   )

                   SCREAMING_SNAKE_CASE					:	Dict   =		json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()   )
                   SCREAMING_SNAKE_CASE					:	Dict   =		json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()   )

                   self.assertEqual(pre_tokenizer_state['add_prefix_space'],				__lowerCamelCase   )

                   self.assertEqual(post_processor_state['add_prefix_space'],				__lowerCamelCase   )
                   self.assertEqual(post_processor_state['trim_offsets'],				__lowerCamelCase   )







       def     UpperCamelCase_				(	self   ):







             '''simple docstring'''







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

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

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

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

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

                         SCREAMING_SNAKE_CASE					:	Tuple   =		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)),
                         # )

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

                         SCREAMING_SNAKE_CASE					:	Dict   =		self.rust_tokenizer_class.from_pretrained(
                             __lowerCamelCase,				use_fast=__lowerCamelCase,				add_prefix_space=__lowerCamelCase,				trim_offsets=__lowerCamelCase   )
                         SCREAMING_SNAKE_CASE					:	Tuple   =		tokenizer_r(__lowerCamelCase,				return_offsets_mapping=__lowerCamelCase,				add_special_tokens=__lowerCamelCase   )
                         self.assertEqual(encoding.offset_mapping[0],				(0, 1 + len(__lowerCamelCase   ))   )
                         self.assertEqual(
                             encoding.offset_mapping[1],				(1 + len(__lowerCamelCase   ), 1 + len(__lowerCamelCase   ) + 1 + len(__lowerCamelCase   )),				)

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









"""simple docstring"""



def 		__lowercase     (   snake_case_  :  int						)   ->int:



    '''simple docstring'''







    assert (
        isinstance(snake_case_				,snake_case_						) and number_of_steps > 0
    ), F"""number_of_steps needs to be positive integer, your input {number_of_steps}"""
    if number_of_steps == 1:
        return 1
    __A ,       __A    :						List[Any]						 =     1, 1
    for _ in range(number_of_steps - 1						):
        __A ,       __A    :						List[str]						 =     current + previous, current
    return current


if __name__ == "__main__":
       import doctest

       doctest.testmod()




