"""simple docstring"""






import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError

from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER, get_tests_dir, is_staging_test


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

from test_module.custom_feature_extraction import CustomFeatureExtractor  # noqa E402


_A   					=    get_tests_dir('fixtures')

class lowerCamelCase		(unittest.TestCase      ):






					'''simple docstring'''


					def 			lowerCAmelCase_					(						self			:				str		)							->       Optional[int]:
									# A mock response for an HTTP head request to emulate server down
									SCREAMING_SNAKE_CASE__		  =				mock.Mock()
									SCREAMING_SNAKE_CASE__		  =				500
									SCREAMING_SNAKE_CASE__		  =				{}
									SCREAMING_SNAKE_CASE__		  =				HTTPError
									SCREAMING_SNAKE_CASE__		  =				{}

									# Download this model to make sure it's in the cache.
									SCREAMING_SNAKE_CASE__		  =				WavaVecaFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-wav2vec2"		)
									# Under the mock environment we get a 500 error when trying to reach the model.
									with mock.patch("requests.Session.request"   , return_value=_snake_case		) as mock_head:
													SCREAMING_SNAKE_CASE__		  =				WavaVecaFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-wav2vec2"		)
													# This check we did call the fake head request
													mock_head.assert_called()



					def 			lowerCAmelCase_					(						self			:				Union[str, Any]		)							->       int:
									# This test is for deprecated behavior and can be removed in v5
									SCREAMING_SNAKE_CASE__		  =				WavaVecaFeatureExtractor.from_pretrained(
									    "https://huggingface.co/hf-internal-testing/tiny-random-wav2vec2/resolve/main/preprocessor_config.json"		)



@is_staging_test
class lowerCamelCase		(unittest.TestCase      ):






					'''simple docstring'''


					@classmethod
					def 			lowerCAmelCase_					(						cls			:				List[str]		)							->       List[str]:
									SCREAMING_SNAKE_CASE__		  =				TOKEN
									HfFolder.save_token(_snake_case		)



					@classmethod
					def 			lowerCAmelCase_					(						cls			:				List[Any]		)							->       Any:
									try:
													delete_repo(token=cls._token   , repo_id="test-feature-extractor"		)
									except HTTPError:
													pass

									try:
													delete_repo(token=cls._token   , repo_id="valid_org/test-feature-extractor-org"		)
									except HTTPError:
													pass

									try:
													delete_repo(token=cls._token   , repo_id="test-dynamic-feature-extractor"		)
									except HTTPError:
													pass



					def 			lowerCAmelCase_					(						self			:				Any		)							->       Any:
									SCREAMING_SNAKE_CASE__		  =				WavaVecaFeatureExtractor.from_pretrained(_snake_case		)
									feature_extractor.push_to_hub("test-feature-extractor"   , use_auth_token=self._token		)

									SCREAMING_SNAKE_CASE__		  =				WavaVecaFeatureExtractor.from_pretrained(F"""{USER}/test-feature-extractor"""		)
									for k, v in feature_extractor.__dict__.items():
													self.assertEqual(_snake_case   , getattr(_snake_case   , _snake_case		)		)

									# Reset repo
									delete_repo(token=self._token   , repo_id="test-feature-extractor"		)

									# Push to hub via save_pretrained
									with tempfile.TemporaryDirectory() as tmp_dir:
													feature_extractor.save_pretrained(
													    _snake_case   , repo_id="test-feature-extractor"   , push_to_hub=_snake_case   , use_auth_token=self._token		)

									SCREAMING_SNAKE_CASE__		  =				WavaVecaFeatureExtractor.from_pretrained(F"""{USER}/test-feature-extractor"""		)
									for k, v in feature_extractor.__dict__.items():
													self.assertEqual(_snake_case   , getattr(_snake_case   , _snake_case		)		)



					def 			lowerCAmelCase_					(						self			:				Tuple		)							->       Optional[int]:
									SCREAMING_SNAKE_CASE__		  =				WavaVecaFeatureExtractor.from_pretrained(_snake_case		)
									feature_extractor.push_to_hub("valid_org/test-feature-extractor"   , use_auth_token=self._token		)

									SCREAMING_SNAKE_CASE__		  =				WavaVecaFeatureExtractor.from_pretrained("valid_org/test-feature-extractor"		)
									for k, v in feature_extractor.__dict__.items():
													self.assertEqual(_snake_case   , getattr(_snake_case   , _snake_case		)		)

									# Reset repo
									delete_repo(token=self._token   , repo_id="valid_org/test-feature-extractor"		)

									# Push to hub via save_pretrained
									with tempfile.TemporaryDirectory() as tmp_dir:
													feature_extractor.save_pretrained(
													    _snake_case   , repo_id="valid_org/test-feature-extractor-org"   , push_to_hub=_snake_case   , use_auth_token=self._token		)

									SCREAMING_SNAKE_CASE__		  =				WavaVecaFeatureExtractor.from_pretrained("valid_org/test-feature-extractor-org"		)
									for k, v in feature_extractor.__dict__.items():
													self.assertEqual(_snake_case   , getattr(_snake_case   , _snake_case		)		)



					def 			lowerCAmelCase_					(						self			:				Tuple		)							->       Dict:
									CustomFeatureExtractor.register_for_auto_class()
									SCREAMING_SNAKE_CASE__		  =				CustomFeatureExtractor.from_pretrained(_snake_case		)

									feature_extractor.push_to_hub("test-dynamic-feature-extractor"   , use_auth_token=self._token		)

									# This has added the proper auto_map field to the config
									self.assertDictEqual(
									    feature_extractor.auto_map   , {"AutoFeatureExtractor": "custom_feature_extraction.CustomFeatureExtractor"}   , )

									SCREAMING_SNAKE_CASE__		  =				AutoFeatureExtractor.from_pretrained(
									    F"""{USER}/test-dynamic-feature-extractor"""   , trust_remote_code=_snake_case		)
									# Can't make an isinstance check because the new_feature_extractor is from the CustomFeatureExtractor class of a dynamic module
									self.assertEqual(new_feature_extractor.__class__.__name__   , "CustomFeatureExtractor"		)





"""simple docstring"""






from math import pi




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase  ,					__UpperCAmelCase       )							->   float:
				return 2 * pi * radius * (angle / 360)


if __name__ == "__main__":
						print(arc_length(9_0, 1_0))




