



import math

import tensorflow as tf
from packaging import version

def    lowerCamelCase_(lowerCamelCase_    ) ->       List[Any]:
						UpperCAmelCase         =     tf.convert_to_tensor(lowerCamelCase_    )
						UpperCAmelCase         =     0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0    )    ,   x.dtype    )    ))

						return x * cdf

def    lowerCamelCase_(lowerCamelCase_    ) ->       Tuple:
						UpperCAmelCase         =     tf.convert_to_tensor(lowerCamelCase_    )
						UpperCAmelCase         =     tf.cast(math.pi    ,   x.dtype    )
						UpperCAmelCase         =     tf.cast(0.04_4715    ,   x.dtype    )
						UpperCAmelCase         =     0.5 * (1.0 + tf.tanh(tf.sqrt(2.0 / pi    ) * (x + coeff * tf.pow(lowerCamelCase_    ,   3    ))    ))

						return x * cdf

def    lowerCamelCase_(lowerCamelCase_    ) ->       Optional[int]:
						UpperCAmelCase         =     tf.convert_to_tensor(lowerCamelCase_    )

						return x * tf.tanh(tf.math.softplus(lowerCamelCase_    )    )

def    lowerCamelCase_(lowerCamelCase_    ) ->       Dict:
						UpperCAmelCase         =     tf.convert_to_tensor(lowerCamelCase_    )
						UpperCAmelCase         =     tf.cast(0.04_4715    ,   x.dtype    )
						UpperCAmelCase         =     tf.cast(0.79_7884_5608    ,   x.dtype    )

						return 0.5 * x * (1.0 + tf.tanh(x * coeffa * (1.0 + coeffa * x * x)    ))

def    lowerCamelCase_(lowerCamelCase_    ) ->       List[str]:
						UpperCAmelCase         =     tf.convert_to_tensor(lowerCamelCase_    )
						UpperCAmelCase         =     tf.cast(1.702    ,   x.dtype    )
						return x * tf.math.sigmoid(coeff * x    )

def    lowerCamelCase_(lowerCamelCase_    ) ->       Any:
						return tf.clip_by_value(_gelu(lowerCamelCase_    )    ,   -10    ,   10    )

def    lowerCamelCase_(lowerCamelCase_    ,   lowerCamelCase_=-1    ) ->       Optional[int]:
						UpperCAmelCase       ,		UpperCAmelCase         =     tf.split(lowerCamelCase_    ,   2    ,   axis=lowerCamelCase_    )
						return a * tf.math.sigmoid(lowerCamelCase_    )


if version.parse(tf.version.VERSION) >= version.parse("2.4"):

		def    lowerCamelCase_(lowerCamelCase_    ) ->       Optional[int]:
								return tf.keras.activations.gelu(lowerCamelCase_    ,   approximate=lowerCamelCase_    )

		__lowerCamelCase     :							List[Any]  							=				tf.keras.activations.gelu





		__lowerCamelCase     :							Any  							=				approximate_gelu_wrap
else:
		__lowerCamelCase     :							Any  							=				_gelu
		__lowerCamelCase     :							Union[str, Any]  							=				_gelu_new


__lowerCamelCase     :							Any  							=				{
    "gelu": gelu,
    "gelu_10": gelu_aa,
    "gelu_fast": gelu_fast,
    "gelu_new": gelu_new,
    "glu": glu,
    "mish": mish,
    "quick_gelu": quick_gelu,
    "relu": tf.keras.activations.relu,
    "sigmoid": tf.keras.activations.sigmoid,
    "silu": tf.keras.activations.swish,
    "swish": tf.keras.activations.swish,
    "tanh": tf.keras.activations.tanh,
}





def    lowerCamelCase_(lowerCamelCase_    ) ->       Any:
						if activation_string in ACTaFN:
												return ACTaFN[activation_string]
						else:
												raise KeyError(F'function {activation_string} not found in ACT2FN mapping {list(ACTaFN.keys()    )}'    )








def    lowerCamelCase_(lowerCamelCase_    ) ->       list[int]:
						UpperCAmelCase         =     len(lowerCamelCase_    )
						for i in range(lowerCamelCase_    ):
												for j in range(i + 1    ,   lowerCamelCase_    ):
																		if numbers[j] < numbers[i]:
																								UpperCAmelCase       ,		UpperCAmelCase         =     numbers[j], numbers[i]
						return numbers


if __name__ == "__main__":
		__lowerCamelCase     :							int  							=				input("Enter numbers separated by a comma:\n").strip()
		__lowerCamelCase     :							Dict  							=				[int(item) for item in user_input.split(",")]
		print(exchange_sort(unsorted))



