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				( __lowercase   ,  unittest.TestCase ):

     '''simple docstring'''

     A_										=  RobertaTokenizer
     A_										=  RobertaTokenizerFast
     A_										=  True
     A_										=  {'cls_token': '<s>'}



     def 		UpperCamelCase_						(					self						) ->				Tuple:






           """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 		UpperCamelCase_						(					self				,				**A_						) ->				Optional[int]:






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



     def 		UpperCamelCase_						(					self				,				**A_						) ->				Union[str, Any]:






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



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






           """simple docstring"""
           _lowerCamelCase			    =				'''lower newer'''
           _lowerCamelCase			    =				'''lower newer'''
           return input_text, output_text



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






           """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 		UpperCamelCase_						(					self						) ->				Dict:






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

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



     @slow
     def 		UpperCamelCase_						(					self						) ->				Tuple:






           """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 		UpperCamelCase_						(					self						) ->				Optional[Any]:






           """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 		UpperCamelCase_						(					self						) ->				Any:






           """simple docstring"""
           pass



     def 		UpperCamelCase_						(					self						) ->				List[Any]:






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



     def 		UpperCamelCase_						(					self						) ->				List[Any]:






           """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 		UpperCamelCase_						(					self						) ->				Union[str, Any]:






           """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_						))				,				)
from .testing import (
    are_the_same_tensors,
    execute_subprocess_async,
    require_bnb,
    require_cpu,
    require_cuda,
    require_huggingface_suite,
    require_mps,
    require_multi_gpu,
    require_multi_xpu,
    require_safetensors,
    require_single_gpu,
    require_single_xpu,
    require_torch_min_version,
    require_tpu,
    require_xpu,
    skip,
    slow,
)
from .training import RegressionDataset, RegressionModel, RegressionModelaXPU


from .scripts import test_script, test_sync, test_ops  # isort: skip