tf.raw_ops.CholeskyGrad

Computes the reverse mode backpropagated gradient of the Cholesky algorithm.

Compat aliases for migration

tf.compat.v1.raw_ops.CholeskyGrad

tf.raw_ops.CholeskyGrad(
    l, grad, name=None
)

For an explanation see "Differentiation of the Cholesky algorithm" by Iain Murray http://arxiv.org/abs/1602.07527

Args
`l`	A `Tensor`. Must be one of the following types: `half`, `float32`, `float64`. Output of batch Cholesky algorithm l = cholesky(A). Shape is `[..., M, M]`. Algorithm depends only on lower triangular part of the innermost matrices of this tensor.
`grad`	A `Tensor`. Must have the same type as `l`. df/dl where f is some scalar function. Shape is `[..., M, M]`. Algorithm depends only on lower triangular part of the innermost matrices of this tensor.
`name`	A name for the operation (optional).

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

Args