# W3cubDocs

/TensorFlow Python

# tf.linalg.logm

```tf.linalg.logm(
input,
name=None
)
```

Defined in `tensorflow/python/ops/gen_linalg_ops.py`.

Computes the matrix logarithm of one or more square matrices:

log(exp(A)) = A

This op is only defined for complex matrices. If A is positive-definite and real, then casting to a complex matrix, taking the logarithm and casting back to a real matrix will give the correct result.

This function computes the matrix logarithm using the Schur-Parlett algorithm. Details of the algorithm can be found in Section 11.6.2 of: Nicholas J. Higham, Functions of Matrices: Theory and Computation, SIAM 2008. ISBN 978-0-898716-46-7.

The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions form square matrices. The output is a tensor of the same shape as the input containing the exponential for all input submatrices `[..., :, :]`.

#### Args:

• `input`: A `Tensor`. Must be one of the following types: `complex64`, `complex128`. Shape is `[..., M, M]`.
• `name`: A name for the operation (optional).

#### Returns:

A `Tensor`. Has the same type as `input`.