
def 			_SCREAMING_SNAKE_CASE      (	_lowerCamelCase				:    int		,						_lowerCamelCase				:    int)      ->					str:






							'''simple docstring'''





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

							__UpperCamelCase			:     Optional[int]         =      ""
							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(_lowerCamelCase)

														# 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_torch_available


lowercase						:      Optional[Any]									= {
    'configuration_blip_2': [
        'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Blip2Config',
        'Blip2QFormerConfig',
        'Blip2VisionConfig',
    ],
    'processing_blip_2': ['Blip2Processor'],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase						:      Tuple									= [
		    'BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'Blip2Model',
		    'Blip2QFormerModel',
		    'Blip2PreTrainedModel',
		    'Blip2ForConditionalGeneration',
		    'Blip2VisionModel',
		]

if TYPE_CHECKING:
		from .configuration_blip_a import (
		    BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    BlipaConfig,
		    BlipaQFormerConfig,
		    BlipaVisionConfig,
		)
		from .processing_blip_a import BlipaProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_blip_a import (
				    BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BlipaForConditionalGeneration,
				    BlipaModel,
				    BlipaPreTrainedModel,
				    BlipaQFormerModel,
				    BlipaVisionModel,
				)

else:
		import sys

		lowercase						:      Dict									= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)