tf.raw_ops.CholeskyGrad
Computes the reverse mode backpropagated gradient of the Cholesky algorithm.
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. |
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Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.9/api_docs/python/tf/raw_ops/CholeskyGrad