


import math

A			:						List[Any]        =  1_0
A			:						Union[str, Any]        =  7
A			:						List[str]        =  BALLS_PER_COLOUR * NUM_COLOURS






def 					UpperCamelCase   (      __magic_name__	:				int = 20	)  ->    str:
		"""simple docstring"""




		lowercase__	     =						math.comb(__magic_name__       ,       __magic_name__	)
		lowercase__	     =						math.comb(NUM_BALLS - BALLS_PER_COLOUR       ,       __magic_name__	)

		lowercase__	     =						NUM_COLOURS * (1 - missing_colour / total)

		return f'''{result:.9f}'''


if __name__ == "__main__":
	print(solution(2_0))





import os
import sys

A			:						Tuple        =  os.path.join(os.path.dirname(__file__), 'src')
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


A			:						Dict        =  [
    'torch',
    'numpy',
    'tokenizers',
    'filelock',
    'requests',
    'tqdm',
    'regex',
    'sentencepiece',
    'sacremoses',
    'importlib_metadata',
    'huggingface_hub',
]






@add_start_docstrings(AutoConfig.__doc__	)
def 					UpperCamelCase   (      *__magic_name__	:				str       ,       **__magic_name__	:				List[Any]	)  ->    str:
		"""simple docstring"""




		return AutoConfig.from_pretrained(*__magic_name__       ,       **__magic_name__	)






@add_start_docstrings(AutoTokenizer.__doc__	)
def 					UpperCamelCase   (      *__magic_name__	:				Any       ,       **__magic_name__	:				Optional[Any]	)  ->    Optional[Any]:
		"""simple docstring"""




		return AutoTokenizer.from_pretrained(*__magic_name__       ,       **__magic_name__	)






@add_start_docstrings(AutoModel.__doc__	)
def 					UpperCamelCase   (      *__magic_name__	:				str       ,       **__magic_name__	:				Optional[Any]	)  ->    Tuple:
		"""simple docstring"""




		return AutoModel.from_pretrained(*__magic_name__       ,       **__magic_name__	)






@add_start_docstrings(AutoModelForCausalLM.__doc__	)
def 					UpperCamelCase   (      *__magic_name__	:				str       ,       **__magic_name__	:				Tuple	)  ->    List[str]:
		"""simple docstring"""




		return AutoModelForCausalLM.from_pretrained(*__magic_name__       ,       **__magic_name__	)






@add_start_docstrings(AutoModelForMaskedLM.__doc__	)
def 					UpperCamelCase   (      *__magic_name__	:				Optional[Any]       ,       **__magic_name__	:				Any	)  ->    Optional[int]:
		"""simple docstring"""




		return AutoModelForMaskedLM.from_pretrained(*__magic_name__       ,       **__magic_name__	)






@add_start_docstrings(AutoModelForSequenceClassification.__doc__	)
def 					UpperCamelCase   (      *__magic_name__	:				Any       ,       **__magic_name__	:				List[str]	)  ->    Union[str, Any]:
		"""simple docstring"""




		return AutoModelForSequenceClassification.from_pretrained(*__magic_name__       ,       **__magic_name__	)







@add_start_docstrings(AutoModelForQuestionAnswering.__doc__	)
def 					UpperCamelCase   (      *__magic_name__	:				Dict       ,       **__magic_name__	:				List[Any]	)  ->    int:
		"""simple docstring"""




		return AutoModelForQuestionAnswering.from_pretrained(*__magic_name__       ,       **__magic_name__	)

