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