Renorm

torch_renorm(self, p, dim, maxnorm)

Arguments

self

(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

Note

If the norm of a row is lower than maxnorm, the row is unchanged

renorm(input, p, dim, maxnorm, out=NULL) -> Tensor

Returns a tensor where each sub-tensor of input along dimension dim is normalized such that the p-norm of the sub-tensor is lower than the value maxnorm

Examples

if (torch_is_installed()) { x = torch_ones(c(3, 3)) x[2,]$fill_(2) x[3,]$fill_(3) x torch_renorm(x, 1, 1, 5) }
#> torch_tensor #> 1.0000 1.0000 1.0000 #> 1.6667 1.6667 1.6667 #> 1.6667 1.6667 1.6667 #> [ CPUFloatType{3,3} ]