






"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


A__					: Union[str, Any]=	{
    """configuration_convnext""": ["""CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ConvNextConfig""", """ConvNextOnnxConfig"""]
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  A__					: Optional[int]=	["""ConvNextFeatureExtractor"""]
  A__					: Optional[int]=	["""ConvNextImageProcessor"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  A__					: Tuple=	[
      """CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """ConvNextForImageClassification""",
      """ConvNextModel""",
      """ConvNextPreTrainedModel""",
      """ConvNextBackbone""",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  A__					: Optional[Any]=	[
      """TFConvNextForImageClassification""",
      """TFConvNextModel""",
      """TFConvNextPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_convnext import ConvNextFeatureExtractor
    from .image_processing_convnext import ConvNextImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_convnext import (
        CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
        ConvNextBackbone,
        ConvNextForImageClassification,
        ConvNextModel,
        ConvNextPreTrainedModel,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
  import sys

  A__					: List[Any]=	_LazyModule(__name__, globals()["""__file__"""], _import_structure)












"""simple docstring"""





def   lowerCAmelCase_( SCREAMING_SNAKE_CASE					)					->	bool:
    """simple docstring"""

    UpperCamelCase__         =    (1 + 24 * n) ** 0.5
    return ((1 + root) / 6) % 1 == 0







def   lowerCAmelCase_( SCREAMING_SNAKE_CASE = 50_00					)					->	int:
    """simple docstring"""

    UpperCamelCase__         =    [(i * (3 * i - 1)) // 2 for i in range(1 ,	SCREAMING_SNAKE_CASE					)]
    for i, pentagonal_i in enumerate(SCREAMING_SNAKE_CASE					):
        for j in range(SCREAMING_SNAKE_CASE ,	len(SCREAMING_SNAKE_CASE					)					):
            UpperCamelCase__         =    pentagonal_nums[j]
            UpperCamelCase__         =    pentagonal_i + pentagonal_j
            UpperCamelCase__         =    pentagonal_j - pentagonal_i
            if is_pentagonal(SCREAMING_SNAKE_CASE					) and is_pentagonal(SCREAMING_SNAKE_CASE					):
                return b

    return -1


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




