





"""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


lowerCAmelCase__     			=			get_tests_dir('''fixtures''')





class        _lowerCamelCase      (       unittest.TestCase ):


						def     snake_case_   (self		) ->   int:
								# A mock response for an HTTP head request to emulate server down
								UpperCamelCase   =	mock.Mock()
								UpperCamelCase   =	5_00
								UpperCamelCase   =	{}
								UpperCamelCase   =	HTTPError
								UpperCamelCase   =	{}

								# Download this model to make sure it's in the cache.
								UpperCamelCase   =	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=__a		) as mock_head:
										UpperCamelCase   =	WavaVecaFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-wav2vec2"		)
										# This check we did call the fake head request
										mock_head.assert_called()




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





@is_staging_test
class        _lowerCamelCase      (       unittest.TestCase ):


						@classmethod
						def     snake_case_   (cls		) ->   Union[str, Any]:
								UpperCamelCase   =	TOKEN
								HfFolder.save_token(__a		)


						@classmethod
						def     snake_case_   (cls		) ->   Optional[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     snake_case_   (self		) ->   Union[str, Any]:
								UpperCamelCase   =	WavaVecaFeatureExtractor.from_pretrained(__a		)
								feature_extractor.push_to_hub("test-feature-extractor"   ,							use_auth_token=self._token		)

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

								# 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(
										    __a   ,							repo_id="test-feature-extractor"   ,							push_to_hub=__a   ,							use_auth_token=self._token		)

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


						def     snake_case_   (self		) ->   Dict:
								UpperCamelCase   =	WavaVecaFeatureExtractor.from_pretrained(__a		)
								feature_extractor.push_to_hub("valid_org/test-feature-extractor"   ,							use_auth_token=self._token		)

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

								# 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(
										    __a   ,							repo_id="valid_org/test-feature-extractor-org"   ,							push_to_hub=__a   ,							use_auth_token=self._token		)

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




						def     snake_case_   (self		) ->   Optional[Any]:
								CustomFeatureExtractor.register_for_auto_class()
								UpperCamelCase   =	CustomFeatureExtractor.from_pretrained(__a		)

								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"}   ,							)

								UpperCamelCase   =	AutoFeatureExtractor.from_pretrained(
								    F"{USER}/test-dynamic-feature-extractor"   ,							trust_remote_code=__a		)
								# 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"""





import argparse
from collections import defaultdict


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	F"{file}_{class_name}_{test_name}"
		done_test[_id] += 1

		with open(_SCREAMING_SNAKE_CASE  ,	"r"    ) as f:
				UpperCamelCase   =	f.readlines()

		UpperCamelCase   =	F"class {class_name}("
		UpperCamelCase   =	F"{4 * ' '}def {test_name}("
		UpperCamelCase   =	F"{8 * ' '}{correct_line.split()[0]}"
		UpperCamelCase   =	F"{16 * ' '}{correct_line.split()[0]}"
		UpperCamelCase   =	False
		UpperCamelCase   =	False
		UpperCamelCase   =	False
		UpperCamelCase   =	False
		UpperCamelCase   =	0
		UpperCamelCase   =	0

		UpperCamelCase   =	[]
		for line in lines:
				if line.startswith(_SCREAMING_SNAKE_CASE    ):
						UpperCamelCase   =	True
				elif in_class and line.startswith(_SCREAMING_SNAKE_CASE    ):
						UpperCamelCase   =	True
				elif in_class and in_func and (line.startswith(_SCREAMING_SNAKE_CASE    ) or line.startswith(_SCREAMING_SNAKE_CASE    )):
						UpperCamelCase   =	len(line.split(correct_line.split()[0]    )[0]    )
						count += 1

						if count == done_test[_id]:
								UpperCamelCase   =	True

				if in_class and in_func and in_line:
						if ")" not in line:
								continue
						else:
								UpperCamelCase   =	True

				if in_class and in_func and in_line and insert_line:
						new_lines.append(F"{spaces * ' '}{correct_line}"    )
						UpperCamelCase   =	UpperCamelCase   =	UpperCamelCase   =	UpperCamelCase   =	False
				else:
						new_lines.append(_SCREAMING_SNAKE_CASE    )

		with open(_SCREAMING_SNAKE_CASE  ,	"w"    ) as f:
				for line in new_lines:
						f.write(_SCREAMING_SNAKE_CASE    )


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE=None    ):




		"""simple docstring"""


		if fail is not None:
				with open(_SCREAMING_SNAKE_CASE  ,	"r"    ) as f:
						UpperCamelCase   =	{l.strip() for l in f.readlines()}
		else:
				UpperCamelCase   =	None

		with open(_SCREAMING_SNAKE_CASE  ,	"r"    ) as f:
				UpperCamelCase   =	f.readlines()

		UpperCamelCase   =	defaultdict(_SCREAMING_SNAKE_CASE    )
		for line in correct_lines:
				UpperCamelCase   ,				UpperCamelCase   ,				UpperCamelCase   ,				UpperCamelCase   =	line.split(";"    )
				if test_failures is None or "::".join([file, class_name, test_name]    ) in test_failures:
						overwrite_file(_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    )


if __name__ == "__main__":
						lowerCAmelCase__     			=			argparse.ArgumentParser()
						parser.add_argument('''--correct_filename''', help='''filename of tests with expected result''')
						parser.add_argument('''--fail_filename''', help='''filename of test failures''', type=str, default=None)
						lowerCAmelCase__     			=			parser.parse_args()

						main(args.correct_filename, args.fail_filename)






