



'''simple docstring'''







from typing import TYPE_CHECKING

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


_UpperCamelCase  						=			{
    """configuration_camembert""": ["""CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CamembertConfig""", """CamembertOnnxConfig"""],
}

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

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_UpperCamelCase  						=			["""CamembertTokenizerFast"""]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_UpperCamelCase  						=			[
		    """CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """CamembertForCausalLM""",
		    """CamembertForMaskedLM""",
		    """CamembertForMultipleChoice""",
		    """CamembertForQuestionAnswering""",
		    """CamembertForSequenceClassification""",
		    """CamembertForTokenClassification""",
		    """CamembertModel""",
		    """CamembertPreTrainedModel""",
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_UpperCamelCase  						=			[
		    """TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """TFCamembertForCausalLM""",
		    """TFCamembertForMaskedLM""",
		    """TFCamembertForMultipleChoice""",
		    """TFCamembertForQuestionAnswering""",
		    """TFCamembertForSequenceClassification""",
		    """TFCamembertForTokenClassification""",
		    """TFCamembertModel""",
		    """TFCamembertPreTrainedModel""",
		]


if TYPE_CHECKING:
		from .configuration_camembert import CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, CamembertConfig, CamembertOnnxConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_camembert import CamembertTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_camembert_fast import CamembertTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_camembert import (
				    CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    CamembertForCausalLM,
				    CamembertForMaskedLM,
				    CamembertForMultipleChoice,
				    CamembertForQuestionAnswering,
				    CamembertForSequenceClassification,
				    CamembertForTokenClassification,
				    CamembertModel,
				    CamembertPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_camembert import (
				    TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFCamembertForCausalLM,
				    TFCamembertForMaskedLM,
				    TFCamembertForMultipleChoice,
				    TFCamembertForQuestionAnswering,
				    TFCamembertForSequenceClassification,
				    TFCamembertForTokenClassification,
				    TFCamembertModel,
				    TFCamembertPreTrainedModel,
				)

else:
		import sys

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






'''simple docstring'''

def        UpperCAmelCase__   (				_lowerCAmelCase    :			int = 400_0000)    ->		int:



						"""simple docstring"""

						snake_case :       List[Any]				=    1
						snake_case :       int				=    2
						snake_case :       List[str]				=    0
						while j <= n:
												if j % 2 == 0:
																		total += j
												snake_case				,					snake_case :       Any				=    j, i + j

						return total


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





