





from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE   						=		{
    """configuration_xlm_prophetnet""": ["""XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMProphetNetConfig"""],
}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_SCREAMING_SNAKE_CASE   						=		["""XLMProphetNetTokenizer"""]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_SCREAMING_SNAKE_CASE   						=		[
						    """XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """XLMProphetNetDecoder""",
						    """XLMProphetNetEncoder""",
						    """XLMProphetNetForCausalLM""",
						    """XLMProphetNetForConditionalGeneration""",
						    """XLMProphetNetModel""",
						    """XLMProphetNetPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_xlm_prophetnet import (
												    XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    XLMProphetNetDecoder,
												    XLMProphetNetEncoder,
												    XLMProphetNetForCausalLM,
												    XLMProphetNetForConditionalGeneration,
												    XLMProphetNetModel,
												    XLMProphetNetPreTrainedModel,
												)

else:
						import sys

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








def        __SCREAMING_SNAKE_CASE	(				__lowercase:		int = 10_00):



  '''simple docstring'''






  __lowerCAmelCase								=					0
  for i in range(__lowercase):
    if i % 3 == 0 or i % 5 == 0:
      result += i
  return result


if __name__ == "__main__":
      print(f"""{solution() = }""")
