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

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Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/CholeskyGrad