YouTipPytorch Torch Linalg Matrix_Rank
# PyTorch torch.linalg.matrix_rank Function
* * *
[
**Parameters**:
* `A` (Tensor): Input matrix.
* `tol` (float, optional): Singular value threshold.
* `hermitian` (bool, optional): If True, the matrix is assumed to be Hermitian (symmetric). Default is False.
* `out` (Tensor, optional): Output tensor.
**Returns**:
* `torch.Tensor`: Returns the rank of the matrix.
* * *
## Usage Examples
## Example
import torch
# Create full-rank matrix
A = torch.tensor([[1.0,2.0,3.0],
[4.0,5.0,6.0],
[7.0,8.0,9.0]])
# Compute matrix rank
rank = torch.linalg.matrix_rank(A)
print("Matrix A:")
print(A)
print("Matrix rank:", rank)
Output:
Matrix A: tensor([[1., 2., 3.], [4., 5., 6.], [7., 8., 9.]])Matrix rank: tensor(2)
## Example - Full-Rank Matrix
import torch
# Create full-rank matrix
B = torch.tensor([[1.0,2.0],
[3.0,4.0]])
rank_B = torch.linalg.matrix_rank(B)
print("Matrix B:")
print(B)
print("Matrix rank:", rank_B)
* * *
[![Image 4: Pytorch torch Reference Manual]( Pytorch torch Reference Manual](