tf.hessians

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'
)

Used in the notebooks

Used in the tutorials

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).

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'.

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

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