NeuralNetwork.backward

NeuralNetwork.backward(input_data, weights)[source]

Backward pass of the network.

Parameters:
  • input_data (float | list[float] | np.ndarray | None) -- input data of the shape (num_inputs). In case of a single scalar input it is directly cast to and interpreted like a one-element array.

  • weights (float | list[float] | np.ndarray | None) -- trainable weights of the shape (num_weights). In case of a single scalar weight

  • array. (it is directly cast to and interpreted like a one-element) --

Returns:

The result of the neural network of the backward pass, i.e., a tuple with the gradients for input and weights of shape (output_shape, num_input) and (output_shape, num_weights), respectively.

Return type:

tuple[np.ndarray | SparseArray | None, np.ndarray | SparseArray | None]