OpflowQNN

class OpflowQNN(operator, input_params=None, weight_params=None, exp_val=None, gradient=None, quantum_instance=None, input_gradients=False)

Basi: NeuralNetwork

Pending deprecation: Opflow Quantum Neural Network.

Parametri:

• operator (OperatorBase) – The parametrized operator that represents the neural network.

• input_params (Optional[List[Parameter]]) – The operator parameters that correspond to the input of the network.

• weight_params (Optional[List[Parameter]]) – The operator parameters that correspond to the trainable weights.

• exp_val (Optional[ExpectationBase]) – The Expected Value converter to be used for the operator.

• gradient (Optional[Gradient]) – The Gradient converter to be used for the operator’s backward pass.

• quantum_instance (Union[Backend, QuantumInstance, None]) – The quantum instance to evaluate the network.

• input_gradients (bool) – Determines whether to compute gradients with respect to input data. Note that this parameter is False by default, and must be explicitly set to True for a proper gradient computation when using TorchConnector.

Attributes

input_gradients	Returns whether gradients with respect to input data are computed by this neural network in the backward method or not.
operator	Returns the underlying operator of this QNN.
quantum_instance	Returns the quantum instance to evaluate the operator.

Methods