
"""simple docstring"""






from decimal import Decimal, getcontext
from math import ceil, factorial
def 					UpperCamelCase		( UpperCAmelCase			)		->Dict:

   """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__":
      UpperCamelCase_							=					50
      print(F"""The first {n} digits of pi is: {pi(n)}""")
# Copyright 2022 The HuggingFace Team and The OpenBMB Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__a  :     Any       =  {
    """configuration_cpmant""": ["""CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CpmAntConfig"""],
    """tokenization_cpmant""": ["""CpmAntTokenizer"""],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__a  :     List[Any]       =  [
		    """CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST""",
		    """CpmAntForCausalLM""",
		    """CpmAntModel""",
		    """CpmAntPreTrainedModel""",
		]


if TYPE_CHECKING:
		from .configuration_cpmant import CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP, CpmAntConfig
		from .tokenization_cpmant import CpmAntTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_cpmant import (
				    CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    CpmAntForCausalLM,
				    CpmAntModel,
				    CpmAntPreTrainedModel,
				)


else:
		import sys

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