




def    A						(__A   :    Dict   ,				__A   :    int       )   ->      Optional[int]:







     """simple docstring"""


     if not isinstance(__A   ,				__A       ):
          raise ValueError('''iterations must be defined as integers'''       )
     if not isinstance(__A   ,				__A       ) or not number >= 1:
          raise ValueError(
              '''starting number must be
                         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_          =							''''''
     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(__A       )

          # 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_tf_available, is_torch_available


lowerCAmelCase       =							{
    'configuration_tapas': ['TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TapasConfig'],
    'tokenization_tapas': ['TapasTokenizer'],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase       =							[
			    'TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'TapasForMaskedLM',
			    'TapasForQuestionAnswering',
			    'TapasForSequenceClassification',
			    'TapasModel',
			    'TapasPreTrainedModel',
			    'load_tf_weights_in_tapas',
			]
try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase       =							[
			    'TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'TFTapasForMaskedLM',
			    'TFTapasForQuestionAnswering',
			    'TFTapasForSequenceClassification',
			    'TFTapasModel',
			    'TFTapasPreTrainedModel',
			]


if TYPE_CHECKING:
			from .configuration_tapas import TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP, TapasConfig
			from .tokenization_tapas import TapasTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tapas import (
						    TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TapasForMaskedLM,
						    TapasForQuestionAnswering,
						    TapasForSequenceClassification,
						    TapasModel,
						    TapasPreTrainedModel,
						    load_tf_weights_in_tapas,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_tapas import (
						    TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFTapasForMaskedLM,
						    TFTapasForQuestionAnswering,
						    TFTapasForSequenceClassification,
						    TFTapasModel,
						    TFTapasPreTrainedModel,
						)


else:
			import sys

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


