


"""simple docstring"""


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     :   List[Any]			    =			get_tests_dir("fixtures")
A     :   int			    =			get_tests_dir("fixtures/dummy_feature_extractor_config.json")
A     :   str			    =			get_tests_dir("fixtures/dummy-config.json")
class   _UpperCamelCase  (   unittest.TestCase		):
							'''simple docstring'''







							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			0

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			AutoFeatureExtractor.from_pretrained("facebook/wav2vec2-base-960h"	)
										self.assertIsInstance(__a    ,   __a	)

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			AutoFeatureExtractor.from_pretrained(__a	)
										self.assertIsInstance(__a    ,   __a	)

							def 			snake_case				(     self	):
										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(__a	).to_dict()

													config_dict.pop("feature_extractor_type"	)
													__lowerCAmelCase				    =			WavaVecaFeatureExtractor(**__a	)

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

													__lowerCAmelCase				    =			AutoFeatureExtractor.from_pretrained(__a	)

													# 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(__a    ,   __a	)

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			AutoFeatureExtractor.from_pretrained(__a	)
										self.assertIsInstance(__a    ,   __a	)

							def 			snake_case				(     self	):
										with self.assertRaisesRegex(
										    __a    ,   "bert-base is not a local folder and is not a valid model identifier"	):
													__lowerCAmelCase				    =			AutoFeatureExtractor.from_pretrained("bert-base"	)

							def 			snake_case				(     self	):
										with self.assertRaisesRegex(
										    __a    ,   R"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"	):
													__lowerCAmelCase				    =			AutoFeatureExtractor.from_pretrained(__a    ,   revision="aaaaaa"	)

							def 			snake_case				(     self	):
										with self.assertRaisesRegex(
										    __a    ,   "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 			snake_case				(     self	):
										# If remote code is not set, we will time out when asking whether to load the model.
										with self.assertRaises(__a	):
													__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(__a	):
													__lowerCAmelCase				    =			AutoFeatureExtractor.from_pretrained(
													    "hf-internal-testing/test_dynamic_feature_extractor"    ,   trust_remote_code=__a	)

										__lowerCAmelCase				    =			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	)
													__lowerCAmelCase				    =			AutoFeatureExtractor.from_pretrained(__a    ,   trust_remote_code=__a	)
										self.assertEqual(reloaded_feature_extractor.__class__.__name__    ,   "NewFeatureExtractor"	)

							def 			snake_case				(     self	):
										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
													__lowerCAmelCase				    =			CustomFeatureExtractor.from_pretrained(__a	)
													with tempfile.TemporaryDirectory() as tmp_dir:
																feature_extractor.save_pretrained(__a	)
																__lowerCAmelCase				    =			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 			snake_case				(     self	):
										class   _UpperCamelCase  (   lowerCAmelCase__		):
																	'''simple docstring'''







																	__UpperCAmelCase						:    Optional[int]				      =True

										try:
													AutoConfig.register("custom"    ,   __a	)
													AutoFeatureExtractor.register(__a    ,   __a	)
													# 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=__a	)
													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=__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"""


def _lowerCamelCase	(		_UpperCamelCase    , _UpperCamelCase      ):

			'''simple docstring'''




			if not isinstance(_UpperCamelCase    , _UpperCamelCase      ):
						raise ValueError("iterations must be defined as integers"      )
			if not isinstance(_UpperCamelCase    , _UpperCamelCase      ) or not number >= 1:
						raise ValueError(
						    "starting number must be\n                         and integer and be more than 0"      )
			if not iterations >= 1:
						raise ValueError("Iterations must be done more than 0 times to play FizzBuzz"      )

			__lowerCAmelCase				    =			""
			while number <= iterations:
						if number % 3 == 0:
									out += "Fizz"
						if number % 5 == 0:
									out += "Buzz"
						if 0 not in (number % 3, number % 5):
									out += str(_UpperCamelCase      )

						# print(out)
						number += 1
						out += " "
			return out


if __name__ == "__main__":
	import doctest

	doctest.testmod()




