- PyTorchDiscriminator.train(data, weights, penalty=False, quantum_instance=None, shots=None)¶
Perform one training step w.r.t to the discriminator’s parameters
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
- with discriminator loss and updated parameters.data, weights, penalty=True,
quantum_instance=None, shots=None) -> Dict[str, Any]:
- Type renvoyé: