tf.linalg.cholesky | TensorFlow v2.16.1 (original) (raw)
Computes the Cholesky decomposition of one or more square matrices.
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Compat aliases for migration
SeeMigration guide for more details.
tf.compat.v1.cholesky, tf.compat.v1.linalg.cholesky
tf.linalg.cholesky(
input: Annotated[Any, TV_Cholesky_T], name=None
) -> Annotated[Any, TV_Cholesky_T]
Used in the notebooks
The input is a tensor of shape [..., M, M]
whose inner-most 2 dimensions form square matrices.
The input has to be symmetric and positive definite. Only the lower-triangular part of the input will be used for this operation. The upper-triangular part will not be read.
The output is a tensor of the same shape as the input containing the Cholesky decompositions for all input submatrices [..., :, :]
.
Args | |
---|---|
input | A Tensor. Must be one of the following types: float64, float32, half, complex64, complex128. Shape is [..., M, M]. |
name | A name for the operation (optional). |
Returns |
---|
A Tensor. Has the same type as input. |