

def     lowerCAmelCase__							(		SCREAMING_SNAKE_CASE_:							int		,				SCREAMING_SNAKE_CASE_:							int					)	->					str:




				'''simple docstring'''





				if not isinstance(SCREAMING_SNAKE_CASE_		,				SCREAMING_SNAKE_CASE_					):
								raise ValueError("iterations must be defined as integers"					)
				if not isinstance(SCREAMING_SNAKE_CASE_		,				SCREAMING_SNAKE_CASE_					) 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"					)

				A__						=	""
				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(SCREAMING_SNAKE_CASE_					)

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


if __name__ == "__main__":
	import doctest

	doctest.testmod()







from typing import TYPE_CHECKING

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


UpperCamelCase__    			=			{
    """configuration_audio_spectrogram_transformer""": [
        """AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """ASTConfig""",
    ]
}

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

try:
					if not is_speech_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__    			=			["""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

					UpperCamelCase__    			=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




