PyTorchDiscriminator.train

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

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

Paramètres:

• data (Iterable) – Data batch.

• weights (Iterable) – Data sample weights.

• penalty (bool) – Indicate whether or not penalty function is applied to the loss function. Ignored if no penalty function defined.

• quantum_instance (QuantumInstance) – used to run Quantum network. Ignored for a classical network.

• shots (int | None) – Number of shots for hardware or qasm execution. Ignored for classical network

Renvoie:

with discriminator loss and updated parameters.data, weights, penalty=True,

quantum_instance=None, shots=None) -> Dict[str, Any]:

Type renvoyé:

dict