| linalg_norm {torch} | R Documentation | 
Computes a vector or matrix norm.
Description
If A is complex valued, it computes the norm of A$abs()
Supports input of float, double, cfloat and cdouble dtypes.
Whether this function computes a vector or matrix norm is determined as follows:
Usage
linalg_norm(A, ord = NULL, dim = NULL, keepdim = FALSE, dtype = NULL)
Arguments
| A | (Tensor): tensor of shape  | 
| ord | (int, float, inf, -inf, 'fro', 'nuc', optional): order of norm. Default:  | 
| dim | (int, Tupleint, optional): dimensions over which to compute
the vector or matrix norm. See above for the behavior when  | 
| keepdim | (bool, optional): If set to  | 
| dtype | dtype ( | 
Details
- If - dimis an int, the vector norm will be computed.
- If - dimis a 2-tuple, the matrix norm will be computed.
- If - dim=NULLand- ord=NULL, A will be flattened to 1D and the 2-norm of the resulting vector will be computed.
- If - dim=NULLand- ord!=NULL, A must be 1D or 2D.
ord defines the norm that is computed. The following norms are
supported:
| ord | norm for matrices | norm for vectors | 
| NULL(default) | Frobenius norm | 2-norm (see below) | 
| "fro" | Frobenius norm | – not supported – | 
| "nuc" | nuclear norm | – not supported – | 
| Inf | max(sum(abs(x), dim=2)) | max(abs(x)) | 
| -Inf | min(sum(abs(x), dim=2)) | min(abs(x)) | 
| 0 | – not supported – | sum(x != 0) | 
| 1 | max(sum(abs(x), dim=1)) | as below | 
| -1 | min(sum(abs(x), dim=1)) | as below | 
| 2 | largest singular value | as below | 
| -2 | smallest singular value | as below | 
| other intorfloat | – not supported – | sum(abs(x)^{ord})^{(1 / ord)} | 
See Also
Other linalg: 
linalg_cholesky_ex(),
linalg_cholesky(),
linalg_det(),
linalg_eigh(),
linalg_eigvalsh(),
linalg_eigvals(),
linalg_eig(),
linalg_householder_product(),
linalg_inv_ex(),
linalg_inv(),
linalg_lstsq(),
linalg_matrix_norm(),
linalg_matrix_power(),
linalg_matrix_rank(),
linalg_multi_dot(),
linalg_pinv(),
linalg_qr(),
linalg_slogdet(),
linalg_solve_triangular(),
linalg_solve(),
linalg_svdvals(),
linalg_svd(),
linalg_tensorinv(),
linalg_tensorsolve(),
linalg_vector_norm()
Examples
if (torch_is_installed()) {
a <- torch_arange(0, 8, dtype = torch_float()) - 4
a
b <- a$reshape(c(3, 3))
b
linalg_norm(a)
linalg_norm(b)
}