torch.renorm#

torch.renorm(input,p,dim,maxnorm,*,out=None)→Tensor#

Returns a tensor where each sub-tensor ofinput along dimensiondim is normalized such that thep-norm of the sub-tensor is lowerthan the valuemaxnorm

Note

If the norm of a row is lower thanmaxnorm, the row is unchanged

Parameters:

• input (Tensor) – the input tensor.

• p (float) – the power for the norm computation

• dim (int) – the dimension to slice over to get the sub-tensors

• maxnorm (float) – the maximum norm to keep each sub-tensor under

Keyword Arguments:

out (Tensor,optional) – the output tensor.

Example:

>>>x=torch.ones(3,3)>>>x[1].fill_(2)tensor([ 2.,  2.,  2.])>>>x[2].fill_(3)tensor([ 3.,  3.,  3.])>>>xtensor([[ 1.,  1.,  1.],        [ 2.,  2.,  2.],        [ 3.,  3.,  3.]])>>>torch.renorm(x,1,0,5)tensor([[ 1.0000,  1.0000,  1.0000],        [ 1.6667,  1.6667,  1.6667],        [ 1.6667,  1.6667,  1.6667]])