
"""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


lowerCamelCase__ :       str						     =			get_tests_dir("fixtures")
lowerCamelCase__ :       Optional[Any]						     =			get_tests_dir("fixtures/dummy_feature_extractor_config.json")
lowerCamelCase__ :       Optional[Any]						     =			get_tests_dir("fixtures/dummy-config.json")




class 				lowercase__(				unittest.TestCase   ):
	'''simple docstring'''

	def   __lowerCAmelCase (						self    :str					)							->			Tuple:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     Union[str, Any]				= 0





	def   __lowerCAmelCase (						self    :Union[str, Any]					)							->			Tuple:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     List[str]				= AutoFeatureExtractor.from_pretrained('''facebook/wav2vec2-base-960h'''					)
			self.assertIsInstance(lowerCamelCase_		, lowerCamelCase_					)





	def   __lowerCAmelCase (						self    :str					)							->			Union[str, Any]:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     Dict				= AutoFeatureExtractor.from_pretrained(lowerCamelCase_					)
			self.assertIsInstance(lowerCamelCase_		, lowerCamelCase_					)





	def   __lowerCAmelCase (						self    :Optional[Any]					)							->			Optional[int]:







			'''simple docstring'''




			with tempfile.TemporaryDirectory() as tmpdirname:
					SCREAMING_SNAKE_CASE       :     int				= WavaVecaConfig()

					# remove feature_extractor_type to make sure config.json alone is enough to load feature processor locally
					SCREAMING_SNAKE_CASE       :     int				= AutoFeatureExtractor.from_pretrained(lowerCamelCase_					).to_dict()

					config_dict.pop('''feature_extractor_type'''					)
					SCREAMING_SNAKE_CASE       :     str				= WavaVecaFeatureExtractor(**lowerCamelCase_					)

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

					SCREAMING_SNAKE_CASE       :     Tuple				= AutoFeatureExtractor.from_pretrained(lowerCamelCase_					)

					# make sure private variable is not incorrectly saved
					SCREAMING_SNAKE_CASE       :     Optional[int]				= json.loads(config.to_json_string()					)
					self.assertTrue('''_processor_class''' not in dict_as_saved					)

			self.assertIsInstance(lowerCamelCase_		, lowerCamelCase_					)





	def   __lowerCAmelCase (						self    :Dict					)							->			List[str]:







			'''simple docstring'''




			SCREAMING_SNAKE_CASE       :     Tuple				= AutoFeatureExtractor.from_pretrained(lowerCamelCase_					)
			self.assertIsInstance(lowerCamelCase_		, lowerCamelCase_					)





	def   __lowerCAmelCase (						self    :Tuple					)							->			Optional[Any]:







			'''simple docstring'''




			with self.assertRaisesRegex(
			    lowerCamelCase_		, '''bert-base is not a local folder and is not a valid model identifier'''					):
					SCREAMING_SNAKE_CASE       :     Optional[int]				= AutoFeatureExtractor.from_pretrained('''bert-base'''					)





	def   __lowerCAmelCase (						self    :Any					)							->			Any:







			'''simple docstring'''




			with self.assertRaisesRegex(
			    lowerCamelCase_		, R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''					):
					SCREAMING_SNAKE_CASE       :     List[str]				= AutoFeatureExtractor.from_pretrained(lowerCamelCase_		, revision='''aaaaaa'''					)





	def   __lowerCAmelCase (						self    :Any					)							->			Dict:







			'''simple docstring'''




			with self.assertRaisesRegex(
			    lowerCamelCase_		, '''hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json.'''		, ):
					SCREAMING_SNAKE_CASE       :     Any				= AutoFeatureExtractor.from_pretrained('''hf-internal-testing/config-no-model'''					)





	def   __lowerCAmelCase (						self    :List[str]					)							->			List[str]:







			'''simple docstring'''




			with self.assertRaises(lowerCamelCase_					):
					SCREAMING_SNAKE_CASE       :     List[Any]				= AutoFeatureExtractor.from_pretrained(
					    '''hf-internal-testing/test_dynamic_feature_extractor'''					)
			# If remote code is disabled, we can't load this config.
			with self.assertRaises(lowerCamelCase_					):
					SCREAMING_SNAKE_CASE       :     List[str]				= AutoFeatureExtractor.from_pretrained(
					    '''hf-internal-testing/test_dynamic_feature_extractor'''		, trust_remote_code=lowerCamelCase_					)

			SCREAMING_SNAKE_CASE       :     List[str]				= AutoFeatureExtractor.from_pretrained(
			    '''hf-internal-testing/test_dynamic_feature_extractor'''		, trust_remote_code=lowerCamelCase_					)
			self.assertEqual(feature_extractor.__class__.__name__		, '''NewFeatureExtractor'''					)

			# Test feature extractor can be reloaded.
			with tempfile.TemporaryDirectory() as tmp_dir:
					feature_extractor.save_pretrained(lowerCamelCase_					)
					SCREAMING_SNAKE_CASE       :     Tuple				= AutoFeatureExtractor.from_pretrained(lowerCamelCase_		, trust_remote_code=lowerCamelCase_					)
			self.assertEqual(reloaded_feature_extractor.__class__.__name__		, '''NewFeatureExtractor'''					)





	def   __lowerCAmelCase (						self    :Union[str, Any]					)							->			str:







			'''simple docstring'''




			try:
					AutoConfig.register('''custom'''		, lowerCamelCase_					)
					AutoFeatureExtractor.register(lowerCamelCase_		, lowerCamelCase_					)
					# Trying to register something existing in the Transformers library will raise an error
					with self.assertRaises(lowerCamelCase_					):
							AutoFeatureExtractor.register(lowerCamelCase_		, lowerCamelCase_					)

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

			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    :Tuple					)							->			Union[str, Any]:







			'''simple docstring'''




			class 				lowercase__(				_UpperCAmelCase   ):
				'''simple docstring'''

				UpperCamelCase				=  True

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

					# If remote is enabled, we load from the Hub
					SCREAMING_SNAKE_CASE       :     Union[str, Any]				= AutoFeatureExtractor.from_pretrained(
					    '''hf-internal-testing/test_dynamic_feature_extractor'''		, trust_remote_code=lowerCamelCase_					)
					self.assertEqual(feature_extractor.__class__.__name__		, '''NewFeatureExtractor'''					)
					self.assertTrue(not hasattr(lowerCamelCase_		, '''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"""






import math





def __A						(   a_ :							list		,		a_ :							int     )->							int:




		'''simple docstring'''






		SCREAMING_SNAKE_CASE       :     Optional[int]				= len(a_     )
		SCREAMING_SNAKE_CASE       :     Optional[Any]				= int(math.floor(math.sqrt(a_     )     )     )
		SCREAMING_SNAKE_CASE       :     List[str]				= 0
		while arr[min(a_		,		a_     ) - 1] < x:
				SCREAMING_SNAKE_CASE       :     Optional[Any]				= step
				step += int(math.floor(math.sqrt(a_     )     )     )
				if prev >= n:
						return -1

		while arr[prev] < x:
				SCREAMING_SNAKE_CASE       :     Any				= prev + 1
				if prev == min(a_		,		a_     ):
						return -1
		if arr[prev] == x:
				return prev
		return -1


if __name__ == "__main__":
					lowerCamelCase__ :       Union[str, Any]						     =			input("Enter numbers separated by a comma:\n").strip()
					lowerCamelCase__ :       List[str]						     =			[int(item) for item in user_input.split(",")]
					lowerCamelCase__ :       Dict						     =			int(input("Enter the number to be searched:\n"))
					lowerCamelCase__ :       Tuple						     =			jump_search(arr, x)
					if res == -1:
										print("Number not found!")
					else:
										print(f'''Number {x} is at index {res}''')





