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torch.float_power#

torch.float_power(input,exponent,*,out=None)→Tensor#

Raisesinput to the power ofexponent, elementwise, in double precision.If neither input is complex returns atorch.float64 tensor,and if one or more inputs is complex returns atorch.complex128 tensor.

Note

This function always computes in double precision, unliketorch.pow(),which implements more typicaltype promotion.This is useful when the computation needs to be performed in a wider or more precise dtype,or the results of the computation may contain fractional values not representable in the input dtypes,like when an integer base is raised to a negative integer exponent.

Parameters

  • input (Tensor orNumber) – the base value(s)

  • exponent (Tensor orNumber) – the exponent value(s)

Keyword Arguments

out (Tensor,optional) – the output tensor.

Example:

>>>a=torch.randint(10,(4,))>>>atensor([6, 4, 7, 1])>>>torch.float_power(a,2)tensor([36., 16., 49.,  1.], dtype=torch.float64)>>>a=torch.arange(1,5)>>>atensor([ 1,  2,  3,  4])>>>exp=torch.tensor([2,-3,4,-5])>>>exptensor([ 2, -3,  4, -5])>>>torch.float_power(a,exp)tensor([1.0000e+00, 1.2500e-01, 8.1000e+01, 9.7656e-04], dtype=torch.float64)