






'''simple docstring'''






def      UpperCAmelCase      (		lowerCamelCase_  :str				,      lowerCamelCase_  :int				,      lowerCamelCase_  :Optional[Any] ):







		'''simple docstring'''
		if n == 0:
				return 1

		elif n % 2 == 1:
				return (binary_exponentiation(lowerCamelCase_				,      n - 1				,      lowerCamelCase_ ) * a) % mod

		else:
				snake_case_		:							Dict			       =						binary_exponentiation(lowerCamelCase_				,      n / 2				,      lowerCamelCase_ )
				return (b * b) % mod


# a prime number
__A	:	Tuple     =     701

__A	:	Any     =     1_000_000_000
__A	:	str     =     10

# using binary exponentiation function, O(log(p)):
print((a / b) % p == (a * binary_exponentiation(b, p - 2, p)) % p)






print((a / b) % p == (a * b ** (p - 2)) % p)



'''simple docstring'''






from typing import TYPE_CHECKING

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


__A	:	Tuple     =     {
    '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	:	Tuple     =     [
							    'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'ASTForAudioClassification',
							    'ASTModel',
							    'ASTPreTrainedModel',
							]

try:
							if not is_speech_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__A	:	int     =     ['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	:	Union[str, Any]     =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)