Loss Functions

class stride.optimisation.loss.l2_distance.L2DistanceLoss(**kwargs)

Bases: stride.core.Operator

L2-Norm of the difference between observed and modelled data:

f = 1/2 ||modelled - observed||^2

async adjoint(d_fun, modelled, observed, **kwargs)

Method defining the adjoint behaviour of the operator. This method needs to be defined by classes inheriting from the operator.

The method will be called with positional arguments comprised of: the gradients of every output of the forward operation, followed by the arguments originally given when calling the forward method.

The adjoint method needs to return a gradient for each of its Variable inputs (or None if the variable does not needs_grad).

This method should not be called directly from user code.

Parameters

• args –

• kwargs –

property comms

async forward(modelled, observed, **kwargs)

Method defining the forward behaviour of the operator. This method needs to be defined by classes inheriting from the operator.

The method can take multiple inputs and produce multiple outputs. Outputs of this method should be of type Variable.

Positional and keyword arguments to forward are processed so that present variables are tracked.

This method should not be called directly from user code.

Parameters

• args –

• kwargs –

property head

classmethod local(*args, uid=None, **kwargs)

classmethod local_parameter(*args, uid=None, **kwargs)

property logger

property loop

property monitor

property node

classmethod parameter(*args, uid=None, **kwargs)

classmethod remote(*args, **kwargs)

property runtime

async classmethod select_worker(runtime=None)

Select an available worker.

Parameters

runtime (str or Runtime, optional) – If a valid runtime is given, this will be selected as the target worker.

Returns

UID of the target worker.

Return type

str

property worker

property zmq_context

class stride.optimisation.loss.functional.FunctionalValue(fun_value, shot_id, residuals=None, **kwargs)

Bases: stride.problem.data.Scalar

Container class for the calculated functional value and the residuals.

Parameters

• fun_value (float) – Scalar value of the functional.

• shot_id (int) – ID of the shot for which the value has been calculated.

• residuals (Data) – Calculated residuals.