import math



def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	int     )							-> int:







  """simple docstring"""





  if not isinstance(__UpperCamelCase			,					__UpperCamelCase     ):
    SCREAMING_SNAKE_CASE__      							=				f"""Input value of [number={number}] must be an integer"""
    raise TypeError(__UpperCamelCase     )

  if number < 1:
    SCREAMING_SNAKE_CASE__      							=				f"""Input value of [number={number}] must be > 0"""
    raise ValueError(__UpperCamelCase     )
  elif number == 1:
    return 3
  elif number == 2:
    return 5
  else:
    SCREAMING_SNAKE_CASE__      							=				int(math.log(number // 3			,					2     )     ) + 2

    SCREAMING_SNAKE_CASE__      							=				[3, 5]
    SCREAMING_SNAKE_CASE__      							=				2
    SCREAMING_SNAKE_CASE__      							=				3
    for block in range(1			,					__UpperCamelCase     ):
      for _ in range(__UpperCamelCase     ):
        proth_list.append(2 ** (block + 1) + proth_list[proth_index - 1]     )
        proth_index += 1
      increment *= 2

  return proth_list[number - 1]


if __name__ == "__main__":
   import doctest

   doctest.testmod()

   for number in range(11):
      __lowerCamelCase      :			int							       =		0
      try:
         __lowerCamelCase      :			Any							       =		proth(number)
      except ValueError:
         print(F"""ValueError: there is no {number}th Proth number""")
         continue

      print(F"""The {number}th Proth number: {value}""")

import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    FEATURE_EXTRACTOR_MAPPING,
    AutoConfig,
    AutoFeatureExtractor,
    WavaVecaConfig,
    WavaVecaFeatureExtractor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, get_tests_dir


sys.path.append(str(Path(__file__).parent.parent.parent.parent / '''utils'''))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_feature_extraction import CustomFeatureExtractor  # noqa E402


__lowerCamelCase      :			List[Any]							       =		get_tests_dir('''fixtures''')
__lowerCamelCase      :			Optional[int]							       =		get_tests_dir('''fixtures/dummy_feature_extractor_config.json''')
__lowerCamelCase      :			Any							       =		get_tests_dir('''fixtures/dummy-config.json''')







class __snake_case    (						unittest.TestCase		):




   def      __a						(   self      :    Optional[Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				0




   def      __a						(   self      :    List[Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained("""facebook/wav2vec2-base-960h"""				)
     self.assertIsInstance(_lowercase	,     _lowercase				)




   def      __a						(   self      :    Union[str, Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained(_lowercase				)
     self.assertIsInstance(_lowercase	,     _lowercase				)




   def      __a						(   self      :    Optional[int]				):



     """simple docstring"""






     with tempfile.TemporaryDirectory() as tmpdirname:
       SCREAMING_SNAKE_CASE__      							=				WavaVecaConfig()

       # remove feature_extractor_type to make sure config.json alone is enough to load feature processor locally
       SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained(_lowercase				).to_dict()

       config_dict.pop("""feature_extractor_type"""				)
       SCREAMING_SNAKE_CASE__      							=				WavaVecaFeatureExtractor(**_lowercase				)

       # save in new folder
       model_config.save_pretrained(_lowercase				)
       config.save_pretrained(_lowercase				)

       SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained(_lowercase				)

       # make sure private variable is not incorrectly saved
       SCREAMING_SNAKE_CASE__      							=				json.loads(config.to_json_string()				)
       self.assertTrue("""_processor_class""" not in dict_as_saved				)

     self.assertIsInstance(_lowercase	,     _lowercase				)




   def      __a						(   self      :    Optional[Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained(_lowercase				)
     self.assertIsInstance(_lowercase	,     _lowercase				)




   def      __a						(   self      :    Dict				):



     """simple docstring"""






     with self.assertRaisesRegex(
         _lowercase	,     """bert-base is not a local folder and is not a valid model identifier"""				):
       SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained("""bert-base"""				)




   def      __a						(   self      :    Union[str, Any]				):



     """simple docstring"""






     with self.assertRaisesRegex(
         _lowercase	,     R"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""				):
       SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained(_lowercase	,     revision="""aaaaaa"""				)




   def      __a						(   self      :    List[Any]				):



     """simple docstring"""






     with self.assertRaisesRegex(
         _lowercase	,     """hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json."""	,     ):
       SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained("""hf-internal-testing/config-no-model"""				)




   def      __a						(   self      :    str				):



     """simple docstring"""






     with self.assertRaises(_lowercase				):
       SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained(
           """hf-internal-testing/test_dynamic_feature_extractor"""				)
     # If remote code is disabled, we can't load this config.
     with self.assertRaises(_lowercase				):
       SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained(
           """hf-internal-testing/test_dynamic_feature_extractor"""	,     trust_remote_code=_lowercase				)

     SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained(
         """hf-internal-testing/test_dynamic_feature_extractor"""	,     trust_remote_code=_lowercase				)
     self.assertEqual(feature_extractor.__class__.__name__	,     """NewFeatureExtractor"""				)

     # Test feature extractor can be reloaded.
     with tempfile.TemporaryDirectory() as tmp_dir:
       feature_extractor.save_pretrained(_lowercase				)
       SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained(_lowercase	,     trust_remote_code=_lowercase				)
     self.assertEqual(reloaded_feature_extractor.__class__.__name__	,     """NewFeatureExtractor"""				)




   def      __a						(   self      :    Union[str, Any]				):



     """simple docstring"""






     try:
       AutoConfig.register("""custom"""	,     _lowercase				)
       AutoFeatureExtractor.register(_lowercase	,     _lowercase				)
       # Trying to register something existing in the Transformers library will raise an error
       with self.assertRaises(_lowercase				):
         AutoFeatureExtractor.register(_lowercase	,     _lowercase				)

       # Now that the config is registered, it can be used as any other config with the auto-API
       SCREAMING_SNAKE_CASE__      							=				CustomFeatureExtractor.from_pretrained(_lowercase				)
       with tempfile.TemporaryDirectory() as tmp_dir:
         feature_extractor.save_pretrained(_lowercase				)
         SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained(_lowercase				)
         self.assertIsInstance(_lowercase	,     _lowercase				)

     finally:
       if "custom" in CONFIG_MAPPING._extra_content:
         del CONFIG_MAPPING._extra_content["custom"]
       if CustomConfig in FEATURE_EXTRACTOR_MAPPING._extra_content:
         del FEATURE_EXTRACTOR_MAPPING._extra_content[CustomConfig]




   def      __a						(   self      :    Any				):



     """simple docstring"""






     class __snake_case    (						lowerCamelCase_		):
        lowerCAmelCase_														=							True

     try:
       AutoConfig.register("""custom"""	,     _lowercase				)
       AutoFeatureExtractor.register(_lowercase	,     _lowercase				)
       # If remote code is not set, the default is to use local
       SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained(
           """hf-internal-testing/test_dynamic_feature_extractor"""				)
       self.assertEqual(feature_extractor.__class__.__name__	,     """NewFeatureExtractor"""				)
       self.assertTrue(feature_extractor.is_local				)

       # If remote code is disabled, we load the local one.
       SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained(
           """hf-internal-testing/test_dynamic_feature_extractor"""	,     trust_remote_code=_lowercase				)
       self.assertEqual(feature_extractor.__class__.__name__	,     """NewFeatureExtractor"""				)
       self.assertTrue(feature_extractor.is_local				)

       # If remote is enabled, we load from the Hub
       SCREAMING_SNAKE_CASE__      							=				AutoFeatureExtractor.from_pretrained(
           """hf-internal-testing/test_dynamic_feature_extractor"""	,     trust_remote_code=_lowercase				)
       self.assertEqual(feature_extractor.__class__.__name__	,     """NewFeatureExtractor"""				)
       self.assertTrue(not hasattr(_lowercase	,     """is_local"""				)				)

     finally:
       if "custom" in CONFIG_MAPPING._extra_content:
         del CONFIG_MAPPING._extra_content["custom"]
       if CustomConfig in FEATURE_EXTRACTOR_MAPPING._extra_content:
         del FEATURE_EXTRACTOR_MAPPING._extra_content[CustomConfig]
