





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


UpperCAmelCase_           =	get_tests_dir("fixtures")
UpperCAmelCase_           =	get_tests_dir("fixtures/dummy_feature_extractor_config.json")
UpperCAmelCase_           =	get_tests_dir("fixtures/dummy-config.json")




class 			__UpperCamelCase    (							unittest.TestCase    ):





     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   0





     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   AutoFeatureExtractor.from_pretrained('''facebook/wav2vec2-base-960h'''					)
        self.assertIsInstance(_UpperCamelCase				,							_UpperCamelCase					)





     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   AutoFeatureExtractor.from_pretrained(_UpperCamelCase					)
        self.assertIsInstance(_UpperCamelCase				,							_UpperCamelCase					)





     def 		UpperCamelCase(     self					):
        with tempfile.TemporaryDirectory() as tmpdirname:
           _UpperCAmelCase           =   WavaVecaConfig()

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

           config_dict.pop('''feature_extractor_type'''					)
           _UpperCAmelCase           =   WavaVecaFeatureExtractor(**_UpperCamelCase					)

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

           _UpperCAmelCase           =   AutoFeatureExtractor.from_pretrained(_UpperCamelCase					)

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

        self.assertIsInstance(_UpperCamelCase				,							_UpperCamelCase					)





     def 		UpperCamelCase(     self					):
        _UpperCAmelCase           =   AutoFeatureExtractor.from_pretrained(_UpperCamelCase					)
        self.assertIsInstance(_UpperCamelCase				,							_UpperCamelCase					)





     def 		UpperCamelCase(     self					):
        with self.assertRaisesRegex(
            _UpperCamelCase				,							'''bert-base is not a local folder and is not a valid model identifier'''					):
           _UpperCAmelCase           =   AutoFeatureExtractor.from_pretrained('''bert-base'''					)





     def 		UpperCamelCase(     self					):
        with self.assertRaisesRegex(
            _UpperCamelCase				,							R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''					):
           _UpperCAmelCase           =   AutoFeatureExtractor.from_pretrained(_UpperCamelCase				,							revision='''aaaaaa'''					)





     def 		UpperCamelCase(     self					):
        with self.assertRaisesRegex(
            _UpperCamelCase				,							'''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'''				,							):
           _UpperCAmelCase           =   AutoFeatureExtractor.from_pretrained('''hf-internal-testing/config-no-model'''					)





     def 		UpperCamelCase(     self					):
        # If remote code is not set, we will time out when asking whether to load the model.
        with self.assertRaises(_UpperCamelCase					):
           _UpperCAmelCase           =   AutoFeatureExtractor.from_pretrained(
               '''hf-internal-testing/test_dynamic_feature_extractor'''					)
        # If remote code is disabled, we can't load this config.
        with self.assertRaises(_UpperCamelCase					):
           _UpperCAmelCase           =   AutoFeatureExtractor.from_pretrained(
               '''hf-internal-testing/test_dynamic_feature_extractor'''				,							trust_remote_code=_UpperCamelCase					)

        _UpperCAmelCase           =   AutoFeatureExtractor.from_pretrained(
            '''hf-internal-testing/test_dynamic_feature_extractor'''				,							trust_remote_code=_UpperCamelCase					)
        self.assertEqual(feature_extractor.__class__.__name__				,							'''NewFeatureExtractor'''					)

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





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

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

        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 		UpperCamelCase(     self					):




        class 			__UpperCamelCase    (							A__    ):
             __A	:  Dict							  =   True

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

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






def      A__       (    SCREAMING_SNAKE_CASE_   :      int = 2_00_00_00						)  ->  int:






   """simple docstring"""







   _UpperCAmelCase           =   [0 for i in range(n + 1						)]
   _UpperCAmelCase           =   1
   _UpperCAmelCase           =   1

   for i in range(2				,	int(n**0.5						) + 1						):
      if primality_list[i] == 0:
         for j in range(i * i				,	n + 1				,	SCREAMING_SNAKE_CASE_						):
            _UpperCAmelCase           =   1
   _UpperCAmelCase           =   0
   for i in range(SCREAMING_SNAKE_CASE_						):
      if primality_list[i] == 0:
         sum_of_primes += i
   return sum_of_primes


if __name__ == "__main__":
   print(f'''{solution() = }''')