




from __future__ import annotations

import bisect




def 					lowerCamelCase__       (						A__       :					list[int]  ,			A__       :					int  ,			A__       :					int = 0  ,			A__       :					int = -1	):





       '''simple docstring'''



       if hi < 0:
              __lowerCamelCase   =						len(A__	)

       while lo < hi:
              __lowerCamelCase   =						lo + (hi - lo) // 2
              if sorted_collection[mid] < item:
                     __lowerCamelCase   =						mid + 1
              else:
                     __lowerCamelCase   =						mid

       return lo




def 					lowerCamelCase__       (						A__       :					list[int]  ,			A__       :					int  ,			A__       :					int = 0  ,			A__       :					int = -1	):





       '''simple docstring'''



       if hi < 0:
              __lowerCamelCase   =						len(A__	)

       while lo < hi:
              __lowerCamelCase   =						lo + (hi - lo) // 2
              if sorted_collection[mid] <= item:
                     __lowerCamelCase   =						mid + 1
              else:
                     __lowerCamelCase   =						mid

       return lo




def 					lowerCamelCase__       (						A__       :					list[int]  ,			A__       :					int  ,			A__       :					int = 0  ,			A__       :					int = -1	):





       '''simple docstring'''



       sorted_collection.insert(bisect_left(A__  ,			A__  ,			A__  ,			A__	)  ,			A__	)




def 					lowerCamelCase__       (						A__       :					list[int]  ,			A__       :					int  ,			A__       :					int = 0  ,			A__       :					int = -1	):





       '''simple docstring'''



       sorted_collection.insert(bisect_right(A__  ,			A__  ,			A__  ,			A__	)  ,			A__	)




def 					lowerCamelCase__       (						A__       :					list[int]  ,			A__       :					int	):





       '''simple docstring'''



       __lowerCamelCase   =						0
       __lowerCamelCase   =						len(A__	) - 1

       while left <= right:
              __lowerCamelCase   =						left + (right - left) // 2
              __lowerCamelCase   =						sorted_collection[midpoint]
              if current_item == item:
                     return midpoint
              elif item < current_item:
                     __lowerCamelCase   =						midpoint - 1
              else:
                     __lowerCamelCase   =						midpoint + 1
       return None




def 					lowerCamelCase__       (						A__       :					list[int]  ,			A__       :					int	):





       '''simple docstring'''



       __lowerCamelCase   =						bisect.bisect_left(A__  ,			A__	)
       if index != len(A__	) and sorted_collection[index] == item:
              return index
       return None




def 					lowerCamelCase__       (						A__       :					list[int]  ,			A__       :					int  ,			A__       :					int  ,			A__       :					int	):





       '''simple docstring'''



       if right < left:
              return None

       __lowerCamelCase   =						left + (right - left) // 2

       if sorted_collection[midpoint] == item:
              return midpoint
       elif sorted_collection[midpoint] > item:
              return binary_search_by_recursion(A__  ,			A__  ,			A__  ,			midpoint - 1	)
       else:
              return binary_search_by_recursion(A__  ,			A__  ,			midpoint + 1  ,			A__	)


if __name__ == "__main__":
       UpperCAmelCase_									=	input('Enter numbers separated by comma:\n').strip()
       UpperCAmelCase_									=	sorted(int(item) for item in user_input.split(','))
       UpperCAmelCase_									=	int(input('Enter a single number to be found in the list:\n'))
       UpperCAmelCase_									=	binary_search(collection, target)
       if result is None:
              print(f"""{target} was not found in {collection}.""")
       else:
              print(f"""{target} was found at position {result} in {collection}.""")







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     lowerCamelCase__(					unittest.TestCase):
      def 			lowerCAmelCase__						(				self: List[str]   ):
             __lowerCamelCase   =						0
      def 			lowerCAmelCase__						(				self: List[str]   ):
             __lowerCamelCase   =						AutoFeatureExtractor.from_pretrained("""facebook/wav2vec2-base-960h"""   )
             self.assertIsInstance(UpperCamelCase_    ,       UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: Union[str, Any]   ):
             __lowerCamelCase   =						AutoFeatureExtractor.from_pretrained(UpperCamelCase_   )
             self.assertIsInstance(UpperCamelCase_    ,       UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: int   ):
             with tempfile.TemporaryDirectory() as tmpdirname:
                    __lowerCamelCase   =						WavaVecaConfig()

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

                    config_dict.pop("""feature_extractor_type"""   )
                    __lowerCamelCase   =						WavaVecaFeatureExtractor(**UpperCamelCase_   )

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

                    __lowerCamelCase   =						AutoFeatureExtractor.from_pretrained(UpperCamelCase_   )

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

             self.assertIsInstance(UpperCamelCase_    ,       UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: Tuple   ):
             __lowerCamelCase   =						AutoFeatureExtractor.from_pretrained(UpperCamelCase_   )
             self.assertIsInstance(UpperCamelCase_    ,       UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: int   ):
             with self.assertRaisesRegex(
                 UpperCamelCase_    ,       """bert-base is not a local folder and is not a valid model identifier"""   ):
                    __lowerCamelCase   =						AutoFeatureExtractor.from_pretrained("""bert-base"""   )
      def 			lowerCAmelCase__						(				self: Tuple   ):
             with self.assertRaisesRegex(
                 UpperCamelCase_    ,       r"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""   ):
                    __lowerCamelCase   =						AutoFeatureExtractor.from_pretrained(UpperCamelCase_    ,       revision="""aaaaaa"""   )
      def 			lowerCAmelCase__						(				self: Optional[Any]   ):
             with self.assertRaisesRegex(
                 UpperCamelCase_    ,       """hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json."""    ,       ):
                    __lowerCamelCase   =						AutoFeatureExtractor.from_pretrained("""hf-internal-testing/config-no-model"""   )
      def 			lowerCAmelCase__						(				self: Tuple   ):
             # If remote code is not set, we will time out when asking whether to load the model.
             with self.assertRaises(UpperCamelCase_   ):
                    __lowerCamelCase   =						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_   ):
                    __lowerCamelCase   =						AutoFeatureExtractor.from_pretrained(
                        """hf-internal-testing/test_dynamic_feature_extractor"""    ,       trust_remote_code=UpperCamelCase_   )

             __lowerCamelCase   =						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_   )
                    __lowerCamelCase   =						AutoFeatureExtractor.from_pretrained(UpperCamelCase_    ,       trust_remote_code=UpperCamelCase_   )
             self.assertEqual(reloaded_feature_extractor.__class__.__name__    ,       """NewFeatureExtractor"""   )
      def 			lowerCAmelCase__						(				self: Any   ):
             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
                    __lowerCamelCase   =						CustomFeatureExtractor.from_pretrained(UpperCamelCase_   )
                    with tempfile.TemporaryDirectory() as tmp_dir:
                           feature_extractor.save_pretrained(UpperCamelCase_   )
                           __lowerCamelCase   =						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 			lowerCAmelCase__						(				self: Dict   ):





             class     lowerCamelCase__(					__lowerCamelCase):
                   UpperCAmelCase__      :	str    		=   True

             try:
                    AutoConfig.register("""custom"""    ,       UpperCamelCase_   )
                    AutoFeatureExtractor.register(UpperCamelCase_    ,       UpperCamelCase_   )
                    # If remote code is not set, the default is to use local
                    __lowerCamelCase   =						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.
                    __lowerCamelCase   =						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
                    __lowerCamelCase   =						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]

