


'''simple docstring'''







import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


SCREAMING_SNAKE_CASE_      =			'▁'

SCREAMING_SNAKE_CASE_      =			get_tests_dir('fixtures/test_sentencepiece.model')


@require_sentencepiece
class  lowerCAmelCase_						(       snake_case__		,    unittest.TestCase      ):





  """simple docstring"""



  a_       :Union[str, Any]												=BertGenerationTokenizer
  a_       :str												=False
  a_       :Optional[Any]												=True

  def __a						(					self     :							int						):





       '''simple docstring'''

       super().setUp()

       __a       =   BertGenerationTokenizer(SCREAMING_SNAKE_CASE__				,							keep_accents=SCREAMING_SNAKE_CASE__						)
       tokenizer.save_pretrained(self.tmpdirname						)

  def __a						(					self     :							List[str]						):





       '''simple docstring'''

       __a       =   """<s>"""
       __a       =   1

       self.assertEqual(self.get_tokenizer()._convert_token_to_id(SCREAMING_SNAKE_CASE__						)				,							SCREAMING_SNAKE_CASE__						)
       self.assertEqual(self.get_tokenizer()._convert_id_to_token(SCREAMING_SNAKE_CASE__						)				,							SCREAMING_SNAKE_CASE__						)

  def __a						(					self     :							List[Any]						):





       '''simple docstring'''

       __a       =   list(self.get_tokenizer().get_vocab().keys()						)

       self.assertEqual(vocab_keys[0]				,							"""<unk>"""						)
       self.assertEqual(vocab_keys[1]				,							"""<s>"""						)
       self.assertEqual(vocab_keys[-1]				,							"""<pad>"""						)
       self.assertEqual(len(SCREAMING_SNAKE_CASE__						)				,							1_0_0_2						)

  def __a						(					self     :							int						):





       '''simple docstring'''

       self.assertEqual(self.get_tokenizer().vocab_size				,							1_0_0_0						)

  def __a						(					self     :							Tuple						):





       '''simple docstring'''

       __a       =   BertGenerationTokenizer(SCREAMING_SNAKE_CASE__				,							keep_accents=SCREAMING_SNAKE_CASE__						)

       __a       =   tokenizer.tokenize("""This is a test"""						)
       self.assertListEqual(SCREAMING_SNAKE_CASE__				,							["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]						)

       self.assertListEqual(
           tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__						)				,							[2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]				,							)

       __a       =   tokenizer.tokenize("""I was born in 92000, and this is falsé."""						)
       self.assertListEqual(
           SCREAMING_SNAKE_CASE__				,							[
               SPIECE_UNDERLINE + """I""",
               SPIECE_UNDERLINE + """was""",
               SPIECE_UNDERLINE + """b""",
               """or""",
               """n""",
               SPIECE_UNDERLINE + """in""",
               SPIECE_UNDERLINE + """""",
               """9""",
               """2""",
               """0""",
               """0""",
               """0""",
               """,""",
               SPIECE_UNDERLINE + """and""",
               SPIECE_UNDERLINE + """this""",
               SPIECE_UNDERLINE + """is""",
               SPIECE_UNDERLINE + """f""",
               """al""",
               """s""",
               """é""",
               """.""",
           ]				,							)
       __a       =   tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__						)
       self.assertListEqual(
           SCREAMING_SNAKE_CASE__				,							[8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4]				,							)

       __a       =   tokenizer.convert_ids_to_tokens(SCREAMING_SNAKE_CASE__						)
       self.assertListEqual(
           SCREAMING_SNAKE_CASE__				,							[
               SPIECE_UNDERLINE + """I""",
               SPIECE_UNDERLINE + """was""",
               SPIECE_UNDERLINE + """b""",
               """or""",
               """n""",
               SPIECE_UNDERLINE + """in""",
               SPIECE_UNDERLINE + """""",
               """<unk>""",
               """2""",
               """0""",
               """0""",
               """0""",
               """,""",
               SPIECE_UNDERLINE + """and""",
               SPIECE_UNDERLINE + """this""",
               SPIECE_UNDERLINE + """is""",
               SPIECE_UNDERLINE + """f""",
               """al""",
               """s""",
               """<unk>""",
               """.""",
           ]				,							)

  @cached_property
  def __a						(					self     :							Optional[Any]						):





       '''simple docstring'''

       return BertGenerationTokenizer.from_pretrained("""google/bert_for_seq_generation_L-24_bbc_encoder"""						)

  @slow
  def __a						(					self     :							Any						):





       '''simple docstring'''

       __a       =   """Hello World!"""
       __a       =   [1_8_5_3_6, 2_2_6_0, 1_0_1]

       self.assertListEqual(SCREAMING_SNAKE_CASE__				,							self.big_tokenizer.encode(SCREAMING_SNAKE_CASE__						)						)

  @slow
  def __a						(					self     :							Optional[Any]						):





       '''simple docstring'''

       __a       =   (
           """This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"""
           """ add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"""
       )
       __a       =   [
           8_7_1,
           4_1_9,
           3_5_8,
           9_4_6,
           9_9_1,
           2_5_2_1,
           4_5_2,
           3_5_8,
           1_3_5_7,
           3_8_7,
           7_7_5_1,
           3_5_3_6,
           1_1_2,
           9_8_5,
           4_5_6,
           1_2_6,
           8_6_5,
           9_3_8,
           5_4_0_0,
           5_7_3_4,
           4_5_8,
           1_3_6_8,
           4_6_7,
           7_8_6,
           2_4_6_2,
           5_2_4_6,
           1_1_5_9,
           6_3_3,
           8_6_5,
           4_5_1_9,
           4_5_7,
           5_8_2,
           8_5_2,
           2_5_5_7,
           4_2_7,
           9_1_6,
           5_0_8,
           4_0_5,
           3_4_3_2_4,
           4_9_7,
           3_9_1,
           4_0_8,
           1_1_3_4_2,
           1_2_4_4,
           3_8_5,
           1_0_0,
           9_3_8,
           9_8_5,
           4_5_6,
           5_7_4,
           3_6_2,
           1_2_5_9_7,
           3_2_0_0,
           3_1_2_9,
           1_1_7_2,
       ]

       self.assertListEqual(SCREAMING_SNAKE_CASE__				,							self.big_tokenizer.encode(SCREAMING_SNAKE_CASE__						)						)

  @require_torch
  @slow
  def __a						(					self     :							Tuple						):





       '''simple docstring'''

       import torch

       from transformers import BertGenerationConfig, BertGenerationEncoder

       # Build sequence
       __a       =   list(self.big_tokenizer.get_vocab().keys()						)[:1_0]
       __a       =   """ """.join(SCREAMING_SNAKE_CASE__						)
       __a       =   self.big_tokenizer.encode_plus(SCREAMING_SNAKE_CASE__				,							return_tensors="""pt"""				,							return_token_type_ids=SCREAMING_SNAKE_CASE__						)
       __a       =   self.big_tokenizer.batch_encode_plus(
           [sequence + """ """ + sequence]				,							return_tensors="""pt"""				,							return_token_type_ids=SCREAMING_SNAKE_CASE__						)

       __a       =   BertGenerationConfig()
       __a       =   BertGenerationEncoder(SCREAMING_SNAKE_CASE__						)

       assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

       with torch.no_grad():
            model(**SCREAMING_SNAKE_CASE__						)
            model(**SCREAMING_SNAKE_CASE__						)


  @slow
  def __a						(					self     :							Optional[int]						):





       '''simple docstring'''

       __a       =   {"""input_ids""": [[3_9_2_8_6, 4_5_8, 3_6_3_3_5, 2_0_0_1, 4_5_6, 1_3_0_7_3, 1_3_2_6_6, 4_5_5, 1_1_3, 7_7_4_6, 1_7_4_1, 1_1_1_5_7, 3_9_1, 1_3_0_7_3, 1_3_2_6_6, 4_5_5, 1_1_3, 3_9_6_7, 3_5_4_1_2, 1_1_3, 4_9_3_6, 1_0_9, 3_8_7_0, 2_3_7_7, 1_1_3, 3_0_0_8_4, 4_5_7_2_0, 4_5_8, 1_3_4, 1_7_4_9_6, 1_1_2, 5_0_3, 1_1_6_7_2, 1_1_3, 1_1_8, 1_1_2, 5_6_6_5, 1_3_3_4_7, 3_8_6_8_7, 1_1_2, 1_4_9_6, 3_1_3_8_9, 1_1_2, 3_2_6_8, 4_7_2_6_4, 1_3_4, 9_6_2, 1_1_2, 1_6_3_7_7, 8_0_3_5, 2_3_1_3_0, 4_3_0, 1_2_1_6_9, 1_5_5_1_8, 2_8_5_9_2, 4_5_8, 1_4_6, 4_1_6_9_7, 1_0_9, 3_9_1, 1_2_1_6_9, 1_5_5_1_8, 1_6_6_8_9, 4_5_8, 1_4_6, 4_1_3_5_8, 1_0_9, 4_5_2, 7_2_6, 4_0_3_4, 1_1_1, 7_6_3, 3_5_4_1_2, 5_0_8_2, 3_8_8, 1_9_0_3, 1_1_1, 9_0_5_1, 3_9_1, 2_8_7_0, 4_8_9_1_8, 1_9_0_0, 1_1_2_3, 5_5_0, 9_9_8, 1_1_2, 9_5_8_6, 1_5_9_8_5, 4_5_5, 3_9_1, 4_1_0, 2_2_9_5_5, 3_7_6_3_6, 1_1_4], [4_4_8, 1_7_4_9_6, 4_1_9, 3_6_6_3, 3_8_5, 7_6_3, 1_1_3, 2_7_5_3_3, 2_8_7_0, 3_2_8_3, 1_3_0_4_3, 1_6_3_9, 2_4_7_1_3, 5_2_3, 6_5_6, 2_4_0_1_3, 1_8_5_5_0, 2_5_2_1, 5_1_7, 2_7_0_1_4, 2_1_2_4_4, 4_2_0, 1_2_1_2, 1_4_6_5, 3_9_1, 9_2_7, 4_8_3_3, 3_8_8, 5_7_8, 1_1_7_8_6, 1_1_4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [4_8_4, 2_1_6_9, 7_6_8_7, 2_1_9_3_2, 1_8_1_4_6, 7_2_6, 3_6_3, 1_7_0_3_2, 3_3_9_1, 1_1_4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
       # fmt: on

       self.tokenizer_integration_test_util(
           expected_encoding=SCREAMING_SNAKE_CASE__				,							model_name="""google/bert_for_seq_generation_L-24_bbc_encoder"""				,							revision="""c817d1fd1be2ffa69431227a1fe320544943d4db"""				,							)










'''simple docstring'''







from __future__ import annotations

import os
from typing import Any

import requests

SCREAMING_SNAKE_CASE_      =			'https://api.github.com'

# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
SCREAMING_SNAKE_CASE_      =			BASE_URL + '/user'

# https://github.com/settings/tokens
SCREAMING_SNAKE_CASE_      =			os.environ.get('USER_TOKEN', '')




def        __lowercase						(      __SCREAMING_SNAKE_CASE		)				->					dict[Any, Any]:
     """simple docstring"""




     __a       =   {
         """Authorization""": F'''token {auth_token}''',
         """Accept""": """application/vnd.github.v3+json""",
     }
     return requests.get(__SCREAMING_SNAKE_CASE				,  headers=__SCREAMING_SNAKE_CASE		).json()


if __name__ == "__main__":  # pragma: no cover
 if USER_TOKEN:
  for key, value in fetch_github_info(USER_TOKEN).items():
   print(f"""{key}: {value}""")
 else:
  raise ValueError('\'USER_TOKEN\' field cannot be empty.')






