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op {
graph_op_name: "MatrixExponential"
in_arg {
name: "input"
description: <<END
Shape is `[..., M, M]`.
END
}
out_arg {
name: "output"
description: <<END
Shape is `[..., M, M]`.
@compatibility(scipy)
Equivalent to scipy.linalg.expm
@end_compatibility
END
}
summary: "Computes the matrix exponential of one or more square matrices:"
description: <<END
\\(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 founds 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 `[..., :, :]`.
END
}
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