tf.linalg.eigh

TensorFlow 1 version

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Computes the matrix exponential of one or more square matrices.

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Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.linalg.expm

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
`input`	A `Tensor`. Must be `float16`, `float32`, `float64`, `complex64`, or `complex128` with shape `[..., M, M]`.
`name`	A name to give this `Op` (optional).

Returns
the matrix exponential of the input.

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

Scipy Compatibility

Equivalent to scipy.linalg.expm

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tf.linalg / eigh

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Args

Returns

Raises

Scipy Compatibility