PyTorchDiscriminator.train¶
- PyTorchDiscriminator.train(data, weights, penalty=False, quantum_instance=None, shots=None)[sorgente]¶
Perform one training step w.r.t to the discriminator’s parameters
- Parametri:
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 (
Optional[int]) – Number of shots for hardware or qasm execution. Ignored for classical network
- Ritorna:
- with discriminator loss and updated parameters.data, weights, penalty=True,
quantum_instance=None, shots=None) -> Dict[str, Any]:
- Tipo di ritorno: