






'''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_    (    UpperCamelCase_		,      unittest.TestCase							):
   _snake_case        =							RobertaTokenizer
   _snake_case        =							RobertaTokenizerFast
   _snake_case        =							True
   _snake_case        =							{"""cls_token""": """<s>"""}







   def     SCREAMING_SNAKE_CASE__					(self)			->      Optional[Any]:
      """simple docstring"""






      super().setUp()

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

      __snake_case				:      Tuple     							= os.path.join(self.tmpdirname					,   VOCAB_FILES_NAMES['vocab_file'])
      __snake_case				:      Tuple     							= 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     SCREAMING_SNAKE_CASE__					(self					,   **__a)			->      int:
      """simple docstring"""






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







   def     SCREAMING_SNAKE_CASE__					(self					,   **__a)			->      Optional[Any]:
      """simple docstring"""






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







   def     SCREAMING_SNAKE_CASE__					(self					,   __a)			->      Optional[int]:
      """simple docstring"""






      __snake_case				:      Any     							= 'lower newer'
      __snake_case				:      Optional[int]     							= 'lower newer'
      return input_text, output_text







   def     SCREAMING_SNAKE_CASE__					(self)			->      int:
      """simple docstring"""






      __snake_case				:      Dict     							= self.tokenizer_class(self.vocab_file					,   self.merges_file					,   **self.special_tokens_map)
      __snake_case				:      Optional[Any]     							= 'lower newer'
      __snake_case				:      Optional[int]     							= ['l', 'o', 'w', 'er', '\u0120', 'n', 'e', 'w', 'er']
      __snake_case				:      Optional[int]     							= tokenizer.tokenize(__a)  # , add_prefix_space=True)
      self.assertListEqual(__a					,   __a)

      __snake_case				:      List[Any]     							= tokens + [tokenizer.unk_token]
      __snake_case				:      Optional[int]     							= [0, 1, 2, 1_5, 1_0, 9, 3, 2, 1_5, 1_9]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(__a)					,   __a)







   def     SCREAMING_SNAKE_CASE__					(self)			->      Optional[int]:
      """simple docstring"""






      __snake_case				:      Union[str, Any]     							= 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     SCREAMING_SNAKE_CASE__					(self)			->      Union[str, Any]:
      """simple docstring"""






      __snake_case				:      Tuple     							= self.tokenizer_class.from_pretrained('roberta-base')

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

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

      __snake_case				:      str     							= tokenizer.build_inputs_with_special_tokens(__a)
      __snake_case				:      Union[str, Any]     							= tokenizer.build_inputs_with_special_tokens(__a					,   __a)

      assert encoded_sentence == encoded_text_from_decode
      assert encoded_pair == encoded_pair_from_decode







   def     SCREAMING_SNAKE_CASE__					(self)			->      List[str]:
      """simple docstring"""






      __snake_case				:      str     							= self.get_tokenizer()

      __snake_case				:      Any     							= 'Encode this sequence.'
      __snake_case				:      Dict     							= tokenizer.byte_encoder[' '.encode('utf-8')[0]]

      # Testing encoder arguments
      __snake_case				:      List[str]     							= tokenizer.encode(__a					,   add_special_tokens=__a					,   add_prefix_space=__a)
      __snake_case				:      Union[str, Any]     							= tokenizer.convert_ids_to_tokens(encoded[0])[0]
      self.assertNotEqual(__a					,   __a)

      __snake_case				:      Tuple     							= tokenizer.encode(__a					,   add_special_tokens=__a					,   add_prefix_space=__a)
      __snake_case				:      Union[str, Any]     							= tokenizer.convert_ids_to_tokens(encoded[0])[0]
      self.assertEqual(__a					,   __a)

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

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

      __snake_case				:      int     							= 'Encode <mask> sequence'
      __snake_case				:      List[Any]     							= 'Encode <mask>sequence'

      __snake_case				:      str     							= tokenizer.encode(__a)
      __snake_case				:      str     							= encoded.index(__a)
      __snake_case				:      Optional[Any]     							= tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1])[0]
      self.assertEqual(__a					,   __a)

      __snake_case				:      Dict     							= tokenizer.encode(__a)
      __snake_case				:      int     							= encoded.index(__a)
      __snake_case				:      Optional[int]     							= tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1])[0]
      self.assertNotEqual(__a					,   __a)







   def     SCREAMING_SNAKE_CASE__					(self)			->      int:
      """simple docstring"""






      pass







   def     SCREAMING_SNAKE_CASE__					(self)			->      str:
      """simple docstring"""






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

            __snake_case				:      List[str]     							= tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids'])
            __snake_case				:      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, 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     SCREAMING_SNAKE_CASE__					(self)			->      List[Any]:
      """simple docstring"""






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

         __snake_case				:      Union[str, Any]     							= json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__())
         __snake_case				:      Dict     							= 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     SCREAMING_SNAKE_CASE__					(self)			->      Optional[int]:
      """simple docstring"""






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

            __snake_case				:      Optional[Any]     							= self.rust_tokenizer_class.from_pretrained(
                __a					,   use_fast=__a					,   add_prefix_space=__a					,   trim_offsets=__a)
            __snake_case				:      Dict     							= 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))					,   )

            __snake_case				:      str     							= self.rust_tokenizer_class.from_pretrained(
                __a					,   use_fast=__a					,   add_prefix_space=__a					,   trim_offsets=__a)
            __snake_case				:      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))					,   )

            __snake_case				:      Dict     							= self.rust_tokenizer_class.from_pretrained(
                __a					,   use_fast=__a					,   add_prefix_space=__a					,   trim_offsets=__a)
            __snake_case				:      Optional[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), len(__a) + 1 + len(__a))					,   )

            __snake_case				:      Optional[Any]     							= self.rust_tokenizer_class.from_pretrained(
                __a					,   use_fast=__a					,   add_prefix_space=__a					,   trim_offsets=__a)
            __snake_case				:      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))					,   )

            __snake_case				:      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)),
            # )

            __snake_case				:      List[str]     							= self.rust_tokenizer_class.from_pretrained(
                __a					,   use_fast=__a					,   add_prefix_space=__a					,   trim_offsets=__a)
            __snake_case				:      List[str]     							= 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))					,   )

            __snake_case				:      List[str]     							= self.rust_tokenizer_class.from_pretrained(
                __a					,   use_fast=__a					,   add_prefix_space=__a					,   trim_offsets=__a)
            __snake_case				:      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))					,   )

            __snake_case				:      Union[str, Any]     							= self.rust_tokenizer_class.from_pretrained(
                __a					,   use_fast=__a					,   add_prefix_space=__a					,   trim_offsets=__a)
            __snake_case				:      Dict     							= 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'''






# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import sys
import warnings
from os.path import abspath, dirname, join


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
__A    	=   abspath(join(dirname(dirname(__file__)), '''src'''))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action='''ignore''', category=FutureWarning)




def        _SCREAMING_SNAKE_CASE  (				A  :       Tuple  )    -> str:







   """simple docstring"""
   from diffusers.utils.testing_utils import pytest_addoption_shared

   pytest_addoption_shared(A  )





def        _SCREAMING_SNAKE_CASE  (				A  :       int  )    -> Optional[int]:







   """simple docstring"""
   from diffusers.utils.testing_utils import pytest_terminal_summary_main

   __snake_case				:      Any     							= terminalreporter.config.getoption('--make-reports'  )
   if make_reports:
      pytest_terminal_summary_main(A  ,		id=A  )