




from decimal import Decimal, getcontext
from math import ceil, factorial







def SCREAMING_SNAKE_CASE       ( lowercase_		)     -> str:



       """simple docstring"""

       if not isinstance(UpperCAmelCase__				,       UpperCAmelCase__		):
              raise TypeError('''Undefined for non-integers'''		)
       elif precision < 1:
              raise ValueError('''Undefined for non-natural numbers'''		)

       A__   				=					precision
       A__   				=					ceil(precision / 14		)
       A__   				=					426_880 * Decimal(10_005		).sqrt()
       A__   				=					1
       A__   				=					13_591_409
       A__   				=					Decimal(UpperCAmelCase__		)
       for k in range(1				,       UpperCAmelCase__		):
              A__   				=					factorial(6 * k		) // (factorial(3 * k		) * factorial(UpperCAmelCase__		) ** 3)
              linear_term += 545_140_134
              exponential_term *= -262_537_412_640_768_000
              partial_sum += Decimal(multinomial_term * linear_term		) / exponential_term
       return str(constant_term / partial_sum		)[:-1]


if __name__ == "__main__":
  _lowerCamelCase			:	int							 =     50
  print(F'''The first {n} digits of pi is: {pi(n)}''')







from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable


_lowerCamelCase			:	Union[str, Any]							 =     {"""configuration_dpt""": ["""DPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DPTConfig"""]}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase			:	Optional[Any]							 =     ["""DPTFeatureExtractor"""]
  _lowerCamelCase			:	int							 =     ["""DPTImageProcessor"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase			:	Optional[int]							 =     [
      """DPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """DPTForDepthEstimation""",
      """DPTForSemanticSegmentation""",
      """DPTModel""",
      """DPTPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_dpt import DPTFeatureExtractor
    from .image_processing_dpt import DPTImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_dpt import (
        DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
        DPTForDepthEstimation,
        DPTForSemanticSegmentation,
        DPTModel,
        DPTPreTrainedModel,
    )


else:
  import sys

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


