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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

dict