tensornn.loss.Poisson

class tensornn.loss.Poisson

Bases: Loss

Poisson loss is calculated with this formula: average of (pred-desired*logₑ(pred))

Methods

calculate	The loss function is used to calculate how off the predictions of the network are.
derivative	Used in backpropagation which helps calculates how much each neuron impacts the loss.
source

__repr__()

Return repr(self).

calculate(pred: Tensor, desired: Tensor) → Tensor

The loss function is used to calculate how off the predictions of the network are.

Parameters:

• pred – the prediction of the network

• desired – the desired values which the network should have gotten close to

Returns:

the average of calculated loss for one whole pass of the network

abstractmethod derivative(pred: Tensor, desired: Tensor) → Tensor

Used in backpropagation which helps calculates how much each neuron impacts the loss.

Parameters:

• pred – the prediction of the network

• desired – the desired values which the network should have gotten close to

Returns:

the derivative of the loss function wrt the last layer of the network