



"""simple docstring"""

import math




def __lowercase    (							_a	,    _a					):
    return math.pow(_a	,    2					) - a




def __lowercase    (							_a					):
    return 2 * x




def __lowercase    (							_a					):
    snake_case_				:  Tuple       =			2.0

    while start <= a:
        snake_case_				:  Union[str, Any]       =			math.pow(_a	,    2					)

    return start




def __lowercase    (							_a	,    _a = 9_999	,    _a = 0.00_0000_0000_0001					):

    if a < 0:
        raise ValueError('''math domain error'''					)

    snake_case_				:  Optional[int]       =			get_initial_point(_a					)

    for _ in range(_a					):
        snake_case_				:  int       =			value
        snake_case_				:  int       =			value - fx(_a	,    _a					) / fx_derivative(_a					)
        if abs(prev_value - value					) < tolerance:
            return value

    return value


if __name__ == "__main__":
     from doctest import testmod

     testmod()










"""simple docstring"""

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


lowercase__					:						Tuple												=			get_tests_dir('''fixtures''')
lowercase__					:						List[str]												=			get_tests_dir('''fixtures/dummy_feature_extractor_config.json''')
lowercase__					:						Dict												=			get_tests_dir('''fixtures/dummy-config.json''')




class  _UpperCAmelCase (    unittest.TestCase):

 def 		_snake_case      (  self	: Tuple       ):
     snake_case_				:  Optional[Any]       =			0

 def 		_snake_case      (  self	: int       ):
     snake_case_				:  str       =			AutoFeatureExtractor.from_pretrained('''facebook/wav2vec2-base-960h'''       )
     self.assertIsInstance(lowercase_						,  lowercase_       )

 def 		_snake_case      (  self	: Optional[Any]       ):
     snake_case_				:  Dict       =			AutoFeatureExtractor.from_pretrained(lowercase_       )
     self.assertIsInstance(lowercase_						,  lowercase_       )

 def 		_snake_case      (  self	: int       ):
     with tempfile.TemporaryDirectory() as tmpdirname:
         snake_case_				:  List[Any]       =			WavaVecaConfig()

         # remove feature_extractor_type to make sure config.json alone is enough to load feature processor locally
         snake_case_				:  Optional[Any]       =			AutoFeatureExtractor.from_pretrained(lowercase_       ).to_dict()

         config_dict.pop('''feature_extractor_type'''       )
         snake_case_				:  Optional[Any]       =			WavaVecaFeatureExtractor(**lowercase_       )

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

         snake_case_				:  List[Any]       =			AutoFeatureExtractor.from_pretrained(lowercase_       )

         # make sure private variable is not incorrectly saved
         snake_case_				:  Dict       =			json.loads(config.to_json_string()       )
         self.assertTrue('''_processor_class''' not in dict_as_saved       )

     self.assertIsInstance(lowercase_						,  lowercase_       )

 def 		_snake_case      (  self	: Optional[Any]       ):
     snake_case_				:  str       =			AutoFeatureExtractor.from_pretrained(lowercase_       )
     self.assertIsInstance(lowercase_						,  lowercase_       )

 def 		_snake_case      (  self	: List[Any]       ):
     with self.assertRaisesRegex(
         lowercase_						,  '''bert-base is not a local folder and is not a valid model identifier'''       ):
         snake_case_				:  List[str]       =			AutoFeatureExtractor.from_pretrained('''bert-base'''       )

 def 		_snake_case      (  self	: Any       ):
     with self.assertRaisesRegex(
         lowercase_						,  r'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''       ):
         snake_case_				:  Dict       =			AutoFeatureExtractor.from_pretrained(lowercase_						,  revision='''aaaaaa'''       )

 def 		_snake_case      (  self	: Optional[Any]       ):
     with self.assertRaisesRegex(
         lowercase_						,  '''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'''						,  ):
         snake_case_				:  Dict       =			AutoFeatureExtractor.from_pretrained('''hf-internal-testing/config-no-model'''       )

 def 		_snake_case      (  self	: Optional[int]       ):
     # If remote code is not set, we will time out when asking whether to load the model.
     with self.assertRaises(lowercase_       ):
         snake_case_				:  str       =			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_       ):
         snake_case_				:  str       =			AutoFeatureExtractor.from_pretrained(
             '''hf-internal-testing/test_dynamic_feature_extractor'''						,  trust_remote_code=lowercase_       )

     snake_case_				:  List[str]       =			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_       )
         snake_case_				:  Optional[int]       =			AutoFeatureExtractor.from_pretrained(lowercase_						,  trust_remote_code=lowercase_       )
     self.assertEqual(reloaded_feature_extractor.__class__.__name__						,  '''NewFeatureExtractor'''       )

 def 		_snake_case      (  self	: Optional[Any]       ):
     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
         snake_case_				:  List[Any]       =			CustomFeatureExtractor.from_pretrained(lowercase_       )
         with tempfile.TemporaryDirectory() as tmp_dir:
             feature_extractor.save_pretrained(lowercase_       )
             snake_case_				:  Any       =			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 		_snake_case      (  self	: Union[str, Any]       ):




     class  _UpperCAmelCase (    lowerCAmelCase__):
      _lowerCAmelCase     :    str	      =	True

     try:
         AutoConfig.register('''custom'''						,  lowercase_       )
         AutoFeatureExtractor.register(lowercase_						,  lowercase_       )
         # If remote code is not set, the default is to use local
         snake_case_				:  List[Any]       =			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.
         snake_case_				:  Union[str, Any]       =			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
         snake_case_				:  Tuple       =			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]





