



'''simple docstring'''




from typing import TYPE_CHECKING

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


UpperCamelCase__       :	Dict    = {
    "configuration_data2vec_audio": ["DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP", "Data2VecAudioConfig"],
    "configuration_data2vec_text": [
        "DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Data2VecTextConfig",
        "Data2VecTextOnnxConfig",
    ],
    "configuration_data2vec_vision": [
        "DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Data2VecVisionConfig",
        "Data2VecVisionOnnxConfig",
    ],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						UpperCamelCase__       :	Optional[int]    = [
						    "DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "Data2VecAudioForAudioFrameClassification",
						    "Data2VecAudioForCTC",
						    "Data2VecAudioForSequenceClassification",
						    "Data2VecAudioForXVector",
						    "Data2VecAudioModel",
						    "Data2VecAudioPreTrainedModel",
						]
						UpperCamelCase__       :	str    = [
						    "DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "Data2VecTextForCausalLM",
						    "Data2VecTextForMaskedLM",
						    "Data2VecTextForMultipleChoice",
						    "Data2VecTextForQuestionAnswering",
						    "Data2VecTextForSequenceClassification",
						    "Data2VecTextForTokenClassification",
						    "Data2VecTextModel",
						    "Data2VecTextPreTrainedModel",
						]
						UpperCamelCase__       :	Optional[int]    = [
						    "DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "Data2VecVisionForImageClassification",
						    "Data2VecVisionForMaskedImageModeling",
						    "Data2VecVisionForSemanticSegmentation",
						    "Data2VecVisionModel",
						    "Data2VecVisionPreTrainedModel",
						]

if is_tf_available():
						UpperCamelCase__       :	List[Any]    = [
						    "TFData2VecVisionForImageClassification",
						    "TFData2VecVisionForSemanticSegmentation",
						    "TFData2VecVisionModel",
						    "TFData2VecVisionPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_dataavec_audio import DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP, DataaVecAudioConfig
						from .configuration_dataavec_text import (
						    DATA2VEC_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    DataaVecTextConfig,
						    DataaVecTextOnnxConfig,
						)
						from .configuration_dataavec_vision import (
						    DATA2VEC_VISION_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    DataaVecVisionConfig,
						    DataaVecVisionOnnxConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_dataavec_audio import (
												    DATA2VEC_AUDIO_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DataaVecAudioForAudioFrameClassification,
												    DataaVecAudioForCTC,
												    DataaVecAudioForSequenceClassification,
												    DataaVecAudioForXVector,
												    DataaVecAudioModel,
												    DataaVecAudioPreTrainedModel,
												)
												from .modeling_dataavec_text import (
												    DATA2VEC_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DataaVecTextForCausalLM,
												    DataaVecTextForMaskedLM,
												    DataaVecTextForMultipleChoice,
												    DataaVecTextForQuestionAnswering,
												    DataaVecTextForSequenceClassification,
												    DataaVecTextForTokenClassification,
												    DataaVecTextModel,
												    DataaVecTextPreTrainedModel,
												)
												from .modeling_dataavec_vision import (
												    DATA2VEC_VISION_PRETRAINED_MODEL_ARCHIVE_LIST,
												    DataaVecVisionForImageClassification,
												    DataaVecVisionForMaskedImageModeling,
												    DataaVecVisionForSemanticSegmentation,
												    DataaVecVisionModel,
												    DataaVecVisionPreTrainedModel,
												)
						if is_tf_available():
												from .modeling_tf_dataavec_vision import (
												    TFDataaVecVisionForImageClassification,
												    TFDataaVecVisionForSemanticSegmentation,
												    TFDataaVecVisionModel,
												    TFDataaVecVisionPreTrainedModel,
												)

else:
						import sys

						UpperCamelCase__       :	str    = _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



'''simple docstring'''






from math import ceil







def 				UpperCamelCase_			(    A__					:   int = 10_01					):
  '''simple docstring'''





  lowerCAmelCase_			:      List[Any]			=   1

  for i in range(1							,    int(ceil(n / 2.0					)					)					):
    lowerCAmelCase_			:      int			=   2 * i + 1
    lowerCAmelCase_			:      Tuple			=   2 * i
    lowerCAmelCase_			:      Tuple			=   total + 4 * odd**2 - 6 * even

  return total


if __name__ == "__main__":
  import sys

  if len(sys.argv) == 1:
    print(solution())
  else:
    try:
      __A					:  str											=      int(sys.argv[1])
      print(solution(n))
    except ValueError:
      print("Invalid entry - please enter a number")



