# tf.hessians

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


See the guide: Training > Gradient Computation

Constructs the Hessian of sum of ys with respect to x in xs.

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.
• name: Optional name to use for grouping all the gradient ops together. defaults to 'hessians'.
• colocate_gradients_with_ops: See gradients() documentation for details.
• gate_gradients: See gradients() documentation for details.
• aggregation_method: See gradients() documentation for details.

#### 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.