NumPyDiscriminator.train

NumPyDiscriminator.train(data, weights, penalty=False, quantum_instance=None, shots=None)

Perform one training step w.r.t to the discriminator’s parameters

Parameters

• data (tuple(numpy.ndarray, numpy.ndarray)) – real_batch: array, Training data batch. generated_batch: array, Generated data batch.

• weights (tuple) – real problem, generated problem

• penalty (bool) – Depreciated for classical networks.

• quantum_instance (QuantumInstance) – Depreciated for classical networks.

• shots (int) – Number of shots for hardware or qasm execution. Ignored for classical networks.

Returns

with Discriminator loss and updated parameters.

Return type

dict