



"""simple docstring"""






from __future__ import annotations

import os
from typing import Any

import requests

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

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

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




def 			snake_case		(		lowerCAmelCase_	)						->				dict[Any, Any]:
  _snake_case   	=      {
      '''Authorization''': f"""token {auth_token}""",
      '''Accept''': '''application/vnd.github.v3+json''',
  }
  return requests.get(lowerCAmelCase_  ,						headers=lowerCAmelCase_	).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.''')










"""simple docstring"""






import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
     snake_case   					=				'''pt'''
elif is_tf_available():
     snake_case   					=				'''tf'''
else:
     snake_case   					=				'''jax'''



class     UpperCAmelCase    (	__SCREAMING_SNAKE_CASE,unittest.TestCase  ):
   A__		:	Union[str, Any]           =  PerceiverTokenizer
   A__		:	Optional[int]           =  False



   def    __UpperCAmelCase    (       self    :	List[Any]				):



     """simple docstring"""
     super().setUp()
     _snake_case   	=      PerceiverTokenizer()
     tokenizer.save_pretrained(self.tmpdirname				)



   @cached_property
   def    __UpperCAmelCase    (       self    :	int				):



     """simple docstring"""
     return PerceiverTokenizer.from_pretrained('''deepmind/language-perceiver'''				)



   def    __UpperCAmelCase    (       self    :	Union[str, Any]							,       **__lowerCamelCase    :	Union[str, Any]				):



     """simple docstring"""
     return self.tokenizer_class.from_pretrained(self.tmpdirname							,       **__lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Dict							,       __lowerCamelCase    :	List[Any]							,       __lowerCamelCase    :	List[str]=False							,       __lowerCamelCase    :	int=2_0							,       __lowerCamelCase    :	List[Any]=5				):



     """simple docstring"""
     # XXX The default common tokenizer tests assume that every ID is decodable on its own.
     # This assumption is invalid for Perceiver because single bytes might not be
     # valid utf-8 (byte 128 for instance).
     # Here we're overriding the smallest possible method to provide
     # a clean sequence without making the same assumption.

     _snake_case   	=      []
     for i in range(len(__lowerCamelCase				)				):
       try:
         _snake_case   	=      tokenizer.decode([i]							,       clean_up_tokenization_spaces=__lowerCamelCase				)
       except UnicodeDecodeError:
         pass
       toks.append((i, tok)				)

     _snake_case   	=      list(filter(lambda __lowerCamelCase				: re.match(R'''^[ a-zA-Z]+$'''							,       t[1]				)							,       __lowerCamelCase				)				)
     _snake_case   	=      list(filter(lambda __lowerCamelCase				: [t[0]] == tokenizer.encode(t[1]							,       add_special_tokens=__lowerCamelCase				)							,       __lowerCamelCase				)				)
     if max_length is not None and len(__lowerCamelCase				) > max_length:
       _snake_case   	=      toks[:max_length]
     if min_length is not None and len(__lowerCamelCase				) < min_length and len(__lowerCamelCase				) > 0:
       while len(__lowerCamelCase				) < min_length:
         _snake_case   	=      toks + toks
        # toks_str = [t[1] for t in toks]
     _snake_case   	=      [t[0] for t in toks]

     # Ensure consistency
     _snake_case   	=      tokenizer.decode(__lowerCamelCase							,       clean_up_tokenization_spaces=__lowerCamelCase				)
     if " " not in output_txt and len(__lowerCamelCase				) > 1:
       _snake_case   	=      (
           tokenizer.decode([toks_ids[0]]							,       clean_up_tokenization_spaces=__lowerCamelCase				)
           + ''' '''
           + tokenizer.decode(toks_ids[1:]							,       clean_up_tokenization_spaces=__lowerCamelCase				)
       )
     if with_prefix_space:
       _snake_case   	=      ''' ''' + output_txt
     _snake_case   	=      tokenizer.encode(__lowerCamelCase							,       add_special_tokens=__lowerCamelCase				)
     return output_txt, output_ids



   def    __UpperCAmelCase    (       self    :	List[str]				):



     """simple docstring"""
     _snake_case   	=      self.perceiver_tokenizer
     _snake_case   	=      '''Unicode €.'''
     _snake_case   	=      tokenizer(__lowerCamelCase				)
     _snake_case   	=      [4, 9_1, 1_1_6, 1_1_1, 1_0_5, 1_1_7, 1_0_6, 1_0_7, 3_8, 2_3_2, 1_3_6, 1_7_8, 5_2, 5]
     self.assertEqual(encoded['''input_ids''']							,       __lowerCamelCase				)

     # decoding
     _snake_case   	=      tokenizer.decode(__lowerCamelCase				)
     self.assertEqual(__lowerCamelCase							,       '''[CLS]Unicode €.[SEP]'''				)

     _snake_case   	=      tokenizer('''e è é ê ë'''				)
     _snake_case   	=      [4, 1_0_7, 3_8, 2_0_1, 1_7_4, 3_8, 2_0_1, 1_7_5, 3_8, 2_0_1, 1_7_6, 3_8, 2_0_1, 1_7_7, 5]
     self.assertEqual(encoded['''input_ids''']							,       __lowerCamelCase				)
     # decoding
     _snake_case   	=      tokenizer.decode(__lowerCamelCase				)
     self.assertEqual(__lowerCamelCase							,       '''[CLS]e è é ê ë[SEP]'''				)

     # encode/decode, but with `encode` instead of `__call__`
     self.assertEqual(tokenizer.decode(tokenizer.encode('''e è é ê ë'''				)				)							,       '''[CLS]e è é ê ë[SEP]'''				)



   def    __UpperCAmelCase    (       self    :	Optional[int]				):



     """simple docstring"""
     _snake_case   	=      self.perceiver_tokenizer
     _snake_case   	=      ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
     # fmt: off
     _snake_case   	=      [4, 7_1, 3_8, 1_1_4, 1_1_7, 1_1_6, 1_0_9, 3_8, 1_1_8, 1_0_3, 1_2_0, 1_0_3, 1_0_9, 1_2_0, 1_0_3, 1_1_8, 1_1_0, 3_8, 1_0_8, 1_1_7, 1_2_0, 3_8, 1_2_1, 1_2_3, 1_1_5, 1_1_5, 1_0_3, 1_2_0, 1_1_1, 1_2_8, 1_0_3, 1_2_2, 1_1_1, 1_1_7, 1_1_6, 5_2, 5, 0]
     # fmt: on
     _snake_case   	=      tokenizer(__lowerCamelCase							,       padding=__lowerCamelCase							,       return_tensors=__lowerCamelCase				)
     self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)

     if FRAMEWORK != "jax":
       _snake_case   	=      list(batch.input_ids.numpy()[0]				)
     else:
       _snake_case   	=      list(batch.input_ids.tolist()[0]				)

     self.assertListEqual(__lowerCamelCase							,       __lowerCamelCase				)

     self.assertEqual((2, 3_8)							,       batch.input_ids.shape				)
     self.assertEqual((2, 3_8)							,       batch.attention_mask.shape				)



   def    __UpperCAmelCase    (       self    :	Any				):



     """simple docstring"""
     _snake_case   	=      self.perceiver_tokenizer
     _snake_case   	=      ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
     _snake_case   	=      tokenizer(__lowerCamelCase							,       padding=__lowerCamelCase							,       return_tensors=__lowerCamelCase				)
     # check if input_ids are returned and no decoder_input_ids
     self.assertIn('''input_ids'''							,       __lowerCamelCase				)
     self.assertIn('''attention_mask'''							,       __lowerCamelCase				)
     self.assertNotIn('''decoder_input_ids'''							,       __lowerCamelCase				)
     self.assertNotIn('''decoder_attention_mask'''							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	int				):



     """simple docstring"""
     _snake_case   	=      self.perceiver_tokenizer
     _snake_case   	=      [
         '''Summary of the text.''',
         '''Another summary.''',
     ]
     _snake_case   	=      tokenizer(
         text_target=__lowerCamelCase							,       max_length=3_2							,       padding='''max_length'''							,       truncation=__lowerCamelCase							,       return_tensors=__lowerCamelCase				)
     self.assertEqual(3_2							,       targets['''input_ids'''].shape[1]				)



   def    __UpperCAmelCase    (       self    :	List[Any]				):



     """simple docstring"""
     # safety check on max_len default value so we are sure the test works
     _snake_case   	=      self.get_tokenizers()
     for tokenizer in tokenizers:
       with self.subTest(f"""{tokenizer.__class__.__name__}"""				):
         self.assertNotEqual(tokenizer.model_max_length							,       4_2				)

        # Now let's start the test
     _snake_case   	=      self.get_tokenizers()
     for tokenizer in tokenizers:
       with self.subTest(f"""{tokenizer.__class__.__name__}"""				):
         # Isolate this from the other tests because we save additional tokens/etc
         _snake_case   	=      tempfile.mkdtemp()

         _snake_case   	=      ''' He is very happy, UNwant\u00E9d,running'''
         _snake_case   	=      tokenizer.encode(__lowerCamelCase							,       add_special_tokens=__lowerCamelCase				)
         tokenizer.save_pretrained(__lowerCamelCase				)

         _snake_case   	=      tokenizer.__class__.from_pretrained(__lowerCamelCase				)
         _snake_case   	=      after_tokenizer.encode(__lowerCamelCase							,       add_special_tokens=__lowerCamelCase				)
         self.assertListEqual(__lowerCamelCase							,       __lowerCamelCase				)

         shutil.rmtree(__lowerCamelCase				)

     _snake_case   	=      self.get_tokenizers(model_max_length=4_2				)
     for tokenizer in tokenizers:
       with self.subTest(f"""{tokenizer.__class__.__name__}"""				):
         # Isolate this from the other tests because we save additional tokens/etc
         _snake_case   	=      tempfile.mkdtemp()

         _snake_case   	=      ''' He is very happy, UNwant\u00E9d,running'''
         tokenizer.add_tokens(['''bim''', '''bambam''']				)
         _snake_case   	=      tokenizer.additional_special_tokens
         additional_special_tokens.append('''new_additional_special_token'''				)
         tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}				)
         _snake_case   	=      tokenizer.encode(__lowerCamelCase							,       add_special_tokens=__lowerCamelCase				)
         tokenizer.save_pretrained(__lowerCamelCase				)

         _snake_case   	=      tokenizer.__class__.from_pretrained(__lowerCamelCase				)
         _snake_case   	=      after_tokenizer.encode(__lowerCamelCase							,       add_special_tokens=__lowerCamelCase				)
         self.assertListEqual(__lowerCamelCase							,       __lowerCamelCase				)
         self.assertIn('''new_additional_special_token'''							,       after_tokenizer.additional_special_tokens				)
         self.assertEqual(after_tokenizer.model_max_length							,       4_2				)

         _snake_case   	=      tokenizer.__class__.from_pretrained(__lowerCamelCase							,       model_max_length=4_3				)
         self.assertEqual(tokenizer.model_max_length							,       4_3				)

         shutil.rmtree(__lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Tuple				):



     """simple docstring"""
     _snake_case   	=      []
     if self.test_slow_tokenizer:
       tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())				)

     if self.test_rust_tokenizer:
       tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())				)

     for tokenizer_class, tokenizer_utils in tokenizer_list:
       with tempfile.TemporaryDirectory() as tmp_dir:
         tokenizer_utils.save_pretrained(__lowerCamelCase				)

         with open(os.path.join(__lowerCamelCase							,       '''special_tokens_map.json'''				)							,       encoding='''utf-8'''				) as json_file:
           _snake_case   	=      json.load(__lowerCamelCase				)

         with open(os.path.join(__lowerCamelCase							,       '''tokenizer_config.json'''				)							,       encoding='''utf-8'''				) as json_file:
           _snake_case   	=      json.load(__lowerCamelCase				)

         _snake_case   	=      [f"""<extra_id_{i}>""" for i in range(1_2_5				)]

         _snake_case   	=      added_tokens_extra_ids + [
             '''an_additional_special_token'''
         ]
         _snake_case   	=      added_tokens_extra_ids + [
             '''an_additional_special_token'''
         ]

         with open(os.path.join(__lowerCamelCase							,       '''special_tokens_map.json'''				)							,       '''w'''							,       encoding='''utf-8'''				) as outfile:
           json.dump(__lowerCamelCase							,       __lowerCamelCase				)
         with open(os.path.join(__lowerCamelCase							,       '''tokenizer_config.json'''				)							,       '''w'''							,       encoding='''utf-8'''				) as outfile:
           json.dump(__lowerCamelCase							,       __lowerCamelCase				)

         # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
         # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
         # "special_tokens_map.json" files
         _snake_case   	=      tokenizer_class.from_pretrained(
             __lowerCamelCase							,       )
         self.assertIn(
             '''an_additional_special_token'''							,       tokenizer_without_change_in_init.additional_special_tokens				)
         self.assertEqual(
             ['''an_additional_special_token''']							,       tokenizer_without_change_in_init.convert_ids_to_tokens(
                 tokenizer_without_change_in_init.convert_tokens_to_ids(['''an_additional_special_token''']				)				)							,       )

         # Now we test that we can change the value of additional_special_tokens in the from_pretrained
         _snake_case   	=      added_tokens_extra_ids + [AddedToken('''a_new_additional_special_token'''							,       lstrip=__lowerCamelCase				)]
         _snake_case   	=      tokenizer_class.from_pretrained(
             __lowerCamelCase							,       additional_special_tokens=__lowerCamelCase							,       )

         self.assertIn('''a_new_additional_special_token'''							,       tokenizer.additional_special_tokens				)
         self.assertEqual(
             ['''a_new_additional_special_token''']							,       tokenizer.convert_ids_to_tokens(
                 tokenizer.convert_tokens_to_ids(['''a_new_additional_special_token''']				)				)							,       )



   def    __UpperCAmelCase    (       self    :	Optional[int]				):



     """simple docstring"""
     _snake_case   	=      self.perceiver_tokenizer
     self.assertEqual(tokenizer.decode([1_7_8]				)							,       '''�'''				)



   def    __UpperCAmelCase    (       self    :	Any				):



     """simple docstring"""
     pass



   def    __UpperCAmelCase    (       self    :	str				):



     """simple docstring"""
     pass



   def    __UpperCAmelCase    (       self    :	str				):



     """simple docstring"""
     pass



   def    __UpperCAmelCase    (       self    :	int				):



     """simple docstring"""
     pass





   def    __UpperCAmelCase    (       self    :	List[Any]				):



     """simple docstring"""
     # The default common tokenizer tests uses invalid tokens for Perceiver that can only accept one-character
     # strings and special added tokens as tokens
     _snake_case   	=      self.get_tokenizers(fast=__lowerCamelCase							,       do_lower_case=__lowerCamelCase				)
     for tokenizer in tokenizers:
       with self.subTest(f"""{tokenizer.__class__.__name__}"""				):
         _snake_case   	=      ['''[CLS]''', '''t''', '''h''', '''i''', '''s''', ''' ''', '''i''', '''s''', ''' ''', '''a''', ''' ''', '''t''', '''e''', '''s''', '''t''', '''[SEP]''']
         _snake_case   	=      tokenizer.convert_tokens_to_string(__lowerCamelCase				)

         self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)





