# tf.raw_ops.CholeskyGrad

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Computes the reverse mode backpropagated gradient of the Cholesky algorithm.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.raw_ops.CholeskyGrad`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/CholeskyGrad)

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    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>

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| ## 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). |

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| ## Returns ||
|---|---|
| A `Tensor`. Has the same type as `l`. ||

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