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Constructs the Hessian of sum of `ys`

with respect to `x`

in `xs`

.

tf.hessians( ys, xs, gate_gradients=False, aggregation_method=None, name='hessians' )

`hessians()`

adds ops to the graph to output the Hessian matrix of `ys`

with respect to `xs`

. It returns a list of `Tensor`

of length `len(xs)`

where each tensor is the Hessian of `sum(ys)`

.

The Hessian is a matrix of second-order partial derivatives of a scalar tensor (see https://en.wikipedia.org/wiki/Hessian_matrix for more details).

Args | |
---|---|

`ys` | A `Tensor` or list of tensors to be differentiated. |

`xs` | A `Tensor` or list of tensors to be used for differentiation. |

`gate_gradients` | See `gradients()` documentation for details. |

`aggregation_method` | See `gradients()` documentation for details. |

`name` | Optional name to use for grouping all the gradient ops together. defaults to 'hessians'. |

Returns | |
---|---|

A list of Hessian matrices of `sum(ys)` for each `x` in `xs` . |

Raises | |
---|---|

`LookupError` | if one of the operations between `xs` and `ys` does not have a registered gradient function. |

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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/hessians