tf.linalg.expm

Computes the inverse of one or more square invertible matrices or their adjoints (conjugate transposes).

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Compat aliases for migration

tf.compat.v1.linalg.inv, tf.compat.v1.matrix_inverse

tf.linalg.inv(
    input, adjoint=False, name=None
)

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 inverse for all input submatrices [..., :, :].

The op uses LU decomposition with partial pivoting to compute the inverses.

If a matrix is not invertible there is no guarantee what the op does. It may detect the condition and raise an exception or it may simply return a garbage result.

Args
`input`	A `Tensor`. Must be one of the following types: `float64`, `float32`, `half`, `complex64`, `complex128`. Shape is `[..., M, M]`.
`adjoint`	An optional `bool`. Defaults to `False`.
`name`	A name for the operation (optional).

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

TensorFlow

tf.linalg / expm

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TensorFlow

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tf.linalg / expm

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