- NumPyDiscriminator.train(data, weights, penalty=False, quantum_instance=None, shots=None)¶
Perform one training step w.r.t to the discriminator’s 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.
with Discriminator loss and updated parameters.
- 반환 형식