# tensorplay.linalg.matrix_rank

Source: https://www.tensorplay.cn/docs/generated/tensorplay.linalg.matrix_rank.html

```python
tensorplay.linalg.matrix_rank(A, *, atol=None, rtol=None, hermitian=False)
```

Computes the numerical rank of each matrix in A.

A singular value counts towards the rank when it exceeds the sum of an
absolute tolerance and a relative tolerance scaled by the largest
singular value of its matrix.

Parameters:

- A ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)) – tensor of shape (..., m, n) holding the matrices.

- atol ([float](https://docs.python.org/3/builtins/functions.html#float), [Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor), optional) – absolute threshold applied to the singular values. Defaults to 0.

- rtol ([float](https://docs.python.org/3/builtins/functions.html#float), [Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor), optional) – relative threshold applied to the largest singular value. Defaults to max(m, n) times the machine epsilon of A’s dtype.

- hermitian ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – when True, A is treated as Hermitian and its rank is derived from eigenvalues instead of singular values.

Returns:

integer tensor with the rank of each matrix, with the batch
dimensions of A.

Return type:

[Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)