
'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_lowercase				:						List[Any]												= {
    "configuration_bart": ["BART_PRETRAINED_CONFIG_ARCHIVE_MAP", "BartConfig", "BartOnnxConfig"],
    "tokenization_bart": ["BartTokenizer"],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowercase				:						List[Any]												= ["BartTokenizerFast"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowercase				:						Any												= [
							    "BART_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "BartForCausalLM",
							    "BartForConditionalGeneration",
							    "BartForQuestionAnswering",
							    "BartForSequenceClassification",
							    "BartModel",
							    "BartPretrainedModel",
							    "PretrainedBartModel",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowercase				:						List[Any]												= [
							    "TFBartForConditionalGeneration",
							    "TFBartForSequenceClassification",
							    "TFBartModel",
							    "TFBartPretrainedModel",
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowercase				:						int												= [
							    "FlaxBartDecoderPreTrainedModel",
							    "FlaxBartForCausalLM",
							    "FlaxBartForConditionalGeneration",
							    "FlaxBartForQuestionAnswering",
							    "FlaxBartForSequenceClassification",
							    "FlaxBartModel",
							    "FlaxBartPreTrainedModel",
							]

if TYPE_CHECKING:
							from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
							from .tokenization_bart import BartTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_bart_fast import BartTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_bart import (
														    BART_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BartForCausalLM,
														    BartForConditionalGeneration,
														    BartForQuestionAnswering,
														    BartForSequenceClassification,
														    BartModel,
														    BartPretrainedModel,
														    PretrainedBartModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_bart import (
														    TFBartForConditionalGeneration,
														    TFBartForSequenceClassification,
														    TFBartModel,
														    TFBartPretrainedModel,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_bart import (
														    FlaxBartDecoderPreTrainedModel,
														    FlaxBartForCausalLM,
														    FlaxBartForConditionalGeneration,
														    FlaxBartForQuestionAnswering,
														    FlaxBartForSequenceClassification,
														    FlaxBartModel,
														    FlaxBartPreTrainedModel,
														)

else:
							import sys

							_lowercase				:						Optional[Any]												= _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)








'''simple docstring'''







def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				int = 1000							):



						"""simple docstring"""





						lowercase_			:  List[Any]									= 0
						for i in range(__SCREAMING_SNAKE_CASE							):
												if i % 3 == 0 or i % 5 == 0:
																		result += i
						return result


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



