

from __future__ import annotations

# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
A											=     10





def a(lowercase__			, lowercase__			, lowercase__			, lowercase__	):





	'''simple docstring'''
	for i in range(lowercase__			, lowercase__	):
		if array[i] == target:
			return i
	return -1





def a(lowercase__			, lowercase__	):





	'''simple docstring'''
	snake_case_      		= 0
	snake_case_      		= len(lowercase__	)
	while left <= right:
		if right - left < precision:
			return lin_search(lowercase__			, lowercase__			, lowercase__			, lowercase__	)

		snake_case_      		= (left + right) // 3 + 1
		snake_case_      		= 2 * (left + right) // 3 + 1

		if array[one_third] == target:
			return one_third
		elif array[two_third] == target:
			return two_third

		elif target < array[one_third]:
			snake_case_      		= one_third - 1
		elif array[two_third] < target:
			snake_case_      		= two_third + 1

		else:
			snake_case_      		= one_third + 1
			snake_case_      		= two_third - 1
	else:
		return -1





def a(lowercase__			, lowercase__			, lowercase__			, lowercase__	):





	'''simple docstring'''
	if left < right:
		if right - left < precision:
			return lin_search(lowercase__			, lowercase__			, lowercase__			, lowercase__	)
		snake_case_      		= (left + right) // 3 + 1
		snake_case_      		= 2 * (left + right) // 3 + 1

		if array[one_third] == target:
			return one_third
		elif array[two_third] == target:
			return two_third

		elif target < array[one_third]:
			return rec_ternary_search(lowercase__			, one_third - 1			, lowercase__			, lowercase__	)
		elif array[two_third] < target:
			return rec_ternary_search(two_third + 1			, lowercase__			, lowercase__			, lowercase__	)
		else:
			return rec_ternary_search(one_third + 1			, two_third - 1			, lowercase__			, lowercase__	)
	else:
		return -1


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		A											=     input('Enter numbers separated by comma:\n').strip()
		A											=     [int(item.strip()) for item in user_input.split(',')]
		assert collection == sorted(collection), f"List must be ordered.\n{collection}."
		A											=     int(input('Enter the number to be found in the list:\n').strip())
		A											=     ite_ternary_search(collection, target)
		A											=     rec_ternary_search(0, len(collection) - 1, collection, target)
		if resulta != -1:
				print(f"""Iterative search: {target} found at positions: {resulta}""")
				print(f"""Recursive search: {target} found at positions: {resulta}""")
		else:
				print('Not found')



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available


A											=     {
    'configuration_audio_spectrogram_transformer': [
        'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'ASTConfig',
    ]
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A											=     [
		    'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'ASTForAudioClassification',
		    'ASTModel',
		    'ASTPreTrainedModel',
		]

try:
		if not is_speech_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		A											=     ['ASTFeatureExtractor']

if TYPE_CHECKING:
		from .configuration_audio_spectrogram_transformer import (
		    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    ASTConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_audio_spectrogram_transformer import (
				    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ASTForAudioClassification,
				    ASTModel,
				    ASTPreTrainedModel,
				)

		try:
				if not is_speech_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
		import sys

		A											=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
