ramjet.losses

Code for custom losses for the ramjet package.

Module Contents

Classes

PerTimeStepBinaryCrossEntropy(positive_weight: float = 1, *args, **kwargs) Computes the cross-entropy loss between true labels and predicted labels for a time series which each time step has
class PerTimeStepBinaryCrossEntropy(positive_weight: float = 1, *args, **kwargs)[source]

Bases: tensorflow.python.keras.losses.LossFunctionWrapper

Computes the cross-entropy loss between true labels and predicted labels for a time series which each time step has a binary label.

__init__(self, positive_weight: float = 1, *args, **kwargs)[source]
Parameters:positive_weight – The weight to give to positive labels in calculating the loss (relative to negative).
static per_time_step_binary_cross_entropy(y_true: tf.Tensor, y_pred: tf.Tensor, positive_weight: float = 1)[source]

Calculates the cross-entropy loss between true labels and predicted labels for a time series which each time step has a binary label.

Parameters:
  • y_true – The true label.
  • y_pred – The predicted label.
  • positive_weight – The weight to give to positive labels in calculating the loss (relative to negative).
Returns:

The resulting cross entropy loss.