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NumPyDiscriminator.train

NumPyDiscriminator.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 (tuple(numpy.ndarray, numpy.ndarray)) – real_batch: array, Training data batch. generated_batch: array, Generated data batch.

  • weights (tuple) – real problem, generated problem

  • penalty (bool) – Depreciated for classical networks.

  • quantum_instance (QuantumInstance) – Depreciated for classical networks.

  • shots (int) – Number of shots for hardware or qasm execution. Ignored for classical networks.

Returns

with Discriminator loss and updated parameters.

Return type

dict