






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


a		:       Optional[int]			     = get_tests_dir("fixtures")
a		:       Any			     = get_tests_dir("fixtures/dummy_feature_extractor_config.json")
a		:       List[Any]			     = get_tests_dir("fixtures/dummy-config.json")
class     a    ( unittest.TestCase   ):



      """simple docstring"""


      def 	UpperCAmelCase      (      self					:			str					)							->      Union[str, Any]:
        __UpperCAmelCase							:	Union[str, Any]           =  0
      def 	UpperCAmelCase      (      self					:			Dict					)							->      Dict:
        __UpperCAmelCase							:	Union[str, Any]           =  AutoFeatureExtractor.from_pretrained("""facebook/wav2vec2-base-960h"""					)
        self.assertIsInstance(__a		,      __a					)
      def 	UpperCAmelCase      (      self					:			Optional[Any]					)							->      Optional[Any]:
        __UpperCAmelCase							:	List[Any]           =  AutoFeatureExtractor.from_pretrained(__a					)
        self.assertIsInstance(__a		,      __a					)
      def 	UpperCAmelCase      (      self					:			Any					)							->      Tuple:
        with tempfile.TemporaryDirectory() as tmpdirname:
          __UpperCAmelCase							:	Optional[Any]           =  WavaVecaConfig()

          # remove feature_extractor_type to make sure config.json alone is enough to load feature processor locally
          __UpperCAmelCase							:	List[str]           =  AutoFeatureExtractor.from_pretrained(__a					).to_dict()

          config_dict.pop("""feature_extractor_type"""					)
          __UpperCAmelCase							:	Dict           =  WavaVecaFeatureExtractor(**__a					)

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

          __UpperCAmelCase							:	int           =  AutoFeatureExtractor.from_pretrained(__a					)

          # make sure private variable is not incorrectly saved
          __UpperCAmelCase							:	List[str]           =  json.loads(config.to_json_string()					)
          self.assertTrue("""_processor_class""" not in dict_as_saved					)

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

        __UpperCAmelCase							:	Optional[int]           =  AutoFeatureExtractor.from_pretrained(
            """hf-internal-testing/test_dynamic_feature_extractor"""		,      trust_remote_code=__a					)
        self.assertEqual(feature_extractor.__class__.__name__		,      """NewFeatureExtractor"""					)

        # Test feature extractor can be reloaded.
        with tempfile.TemporaryDirectory() as tmp_dir:
          feature_extractor.save_pretrained(__a					)
          __UpperCAmelCase							:	Union[str, Any]           =  AutoFeatureExtractor.from_pretrained(__a		,      trust_remote_code=__a					)
        self.assertEqual(reloaded_feature_extractor.__class__.__name__		,      """NewFeatureExtractor"""					)
      def 	UpperCAmelCase      (      self					:			List[str]					)							->      List[str]:
        try:
          AutoConfig.register("""custom"""		,      __a					)
          AutoFeatureExtractor.register(__a		,      __a					)
          # Trying to register something existing in the Transformers library will raise an error
          with self.assertRaises(__a					):
            AutoFeatureExtractor.register(__a		,      __a					)

          # Now that the config is registered, it can be used as any other config with the auto-API
          __UpperCAmelCase							:	Optional[int]           =  CustomFeatureExtractor.from_pretrained(__a					)
          with tempfile.TemporaryDirectory() as tmp_dir:
            feature_extractor.save_pretrained(__a					)
            __UpperCAmelCase							:	Optional[Any]           =  AutoFeatureExtractor.from_pretrained(__a					)
            self.assertIsInstance(__a		,      __a					)

        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					:			List[Any]					)							->      Union[str, Any]:
        class     a    ( lowercase__   ):



              """simple docstring"""


              a  : List[Any]							       =	True

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

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




"""simple docstring"""





from __future__ import annotations



def       lowerCamelCase__		(			__snake_case,     __snake_case	)							->		float:


					"""simple docstring"""





					_UpperCamelCase							 =  sorted(numsa + numsa	)
					_UpperCamelCase ,  _UpperCamelCase							 =  divmod(len(__snake_case	),     2	)
					if mod == 1:
										return all_numbers[div]
					else:
										return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				_a														=		[float(x) for x in input("""Enter the elements of first array: """).split()]
				_a														=		[float(x) for x in input("""Enter the elements of second array: """).split()]
				print(F"""The median of two arrays is: {median_of_two_arrays(array_a, array_a)}""")






