Losses Documentation

Classes

Loss

The main loss function

• extends: Metric
• Could be use as a decorator of a function

@Loss
def loss_fn(input: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
	...

• Loss tensor is stayed in memory until reset is called
• Constructor:
  • Parameters: - loss_fn: A Callable function that accepts input or y_pred in Any kind and target or y_true in Any kind as inputs and gives a loss in torch.Tensor

CrossEntropy

The cross entropy loss

• extends: Loss

Dice

The dice loss

• extends: Loss

DiceCE

Combined Dice loss and CrossEntropy loss

• extends: CrossEntropy, Dice

FocalCrossEntropy

The focal cross entropy loss

• extends: Loss
• Constructor:
  • Parameters: - alpha: A float of alpha in focal cross entropy - gamma: A float of gamma in focal cross entropy - calculate_average: A bool flag of if calculate average for the focal loss

KLDiv

KL-Div Loss

• extends: Loss

MAE

The MAE loss

• extends _ReductableLoss

MSE

The MSE loss

• extends _ReductableLoss

• Properties: - reduction: A .loss.Reduction of reduction method - replace_nan: A boolean flag of if replacing nan results to zeros

MultiLosses

A loss with multiple losses

• extends: Loss

• Properties:
  • losses: A list of loss metrics in Metric

MultiOutputsLosses

A loss with multiple losses for multiple outputs

• Pending Depreciation Warning: MultiOutputsLosses will be deprecated in v1.1.0, use MultiLosses along with target parameter for each loss instead.
• extends: Loss

• Properties:
  • losses: A dict of loss metrics in Metric

Methods

loss

The loss wrapping function that wrap a function into a loss

• Use as a decorator

@loss
def loss_fn(input: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
	...