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Computes the matrix exponential of one or more square matrices.

tf.linalg.expm( input, name=None )

exp(A) = \sum_{n=0}^\infty A^n/n!

The exponential is computed using a combination of the scaling and squaring method and the Pade approximation. Details can be found in: Nicholas J. Higham, "The scaling and squaring method for the matrix exponential revisited," SIAM J. Matrix Anal. Applic., 26:1179-1193, 2005.

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 | |
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`input` | A `Tensor` . Must be `float16` , `float32` , `float64` , `complex64` , or `complex128` with shape `[..., M, M]` . |

`name` | A name to give this `Op` (optional). |

Returns | |
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the matrix exponential of the input. |

Raises | |
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`ValueError` | An unsupported type is provided as input. |

Equivalent to scipy.linalg.expm

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Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/linalg/expm