# Theano expressions¶

blocks.theano_expressions.hessian_times_vector(gradient, parameter, vector, r_op=False)[source]

Return an expression for the Hessian times a vector.

Parameters: gradient (TensorVariable) – The gradient of a cost with respect to parameter parameter (TensorVariable) – The parameter with respect to which to take the gradient vector (TensorVariable) – The vector with which to multiply the Hessian r_op (bool, optional) – Whether to use Rop() or not. Defaults to False. Which solution is fastest normally needs to be determined by profiling.
blocks.theano_expressions.l2_norm(tensors, squared=False)[source]

Computes the total L2 norm of a set of tensors.

Converts all operands to TensorVariable (see as_tensor_variable()).

Parameters: tensors (iterable of TensorVariable (or compatible)) – The tensors. squared (bool, optional) – If True, return the squared L2 norm. Default: False.