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torch.fmin#

torch.fmin(input,other,*,out=None)→Tensor#

Computes the element-wise minimum ofinput andother.

This is liketorch.minimum() except it handles NaNs differently:if exactly one of the two elements being compared is a NaN then the non-NaN element is taken as the minimum.Only if both elements are NaN is NaN propagated.

This function is a wrapper around C++’sstd::fmin and is similar to NumPy’sfmin function.

Supportsbroadcasting to a common shape,type promotion, and integer and floating-point inputs.

Parameters:

  • input (Tensor) – the input tensor.

  • other (Tensor) – the second input tensor

Keyword Arguments:

out (Tensor,optional) – the output tensor.

Example:

>>>a=torch.tensor([2.2,float('nan'),2.1,float('nan')])>>>b=torch.tensor([-9.3,0.1,float('nan'),float('nan')])>>>torch.fmin(a,b)tensor([-9.3000, 0.1000, 2.1000,    nan])