NeuralNetwork

class NeuralNetwork(num_inputs, num_weights, sparse, output_shape, input_gradients=False)

기반 클래스: ABC

Abstract Neural Network class providing forward and backward pass and handling batched inputs. This is to be implemented by other (quantum) neural networks.

매개변수:

• num_inputs (int) – The number of input features.

• num_weights (int) – The number of trainable weights.

• sparse (bool) – Determines whether the output is a sparse array or not.

• output_shape (int | tuple[int, ...]) – The shape of the output.

• input_gradients (bool) – Determines whether to compute gradients with respect to input data.

예외 발생:

QiskitMachineLearningError – Invalid parameter values.

Attributes

input_gradients	Returns whether gradients with respect to input data are computed by this neural network in the backward method or not.
num_inputs	Returns the number of input features.
num_weights	Returns the number of trainable weights.
output_shape	Returns the output shape.
sparse	Returns whether the output is sparse or not.

Methods

backward(input_data, weights)	Backward pass of the network.
forward(input_data, weights)	Forward pass of the network.