dacapo.experiments.tasks.losses.mse_loss

Classes

MSELoss

A class used to represent the Mean Square Error Loss function (MSELoss). This class inherits from the Loss class.

Module Contents

class dacapo.experiments.tasks.losses.mse_loss.MSELoss

A class used to represent the Mean Square Error Loss function (MSELoss). This class inherits from the Loss class.

compute(prediction, target, weight) → torch.Tensor: Function to compute the MSELoss for the provided prediction and target, with respect to the weight.

Note

This class is abstract. Subclasses must implement the abstract methods. Once created, the values of its attributes cannot be changed.

compute(prediction, target, weight)

Function to compute the MSELoss for the provided prediction and target, with respect to the weight.

Parameters:

prediction – torch.Tensor The predicted tensor.
target – torch.Tensor The target tensor.
weight – torch.Tensor The weight tensor.

Returns:

torch.Tensor: The computed MSELoss tensor.

Raises:

NotImplementedError – If the method is not implemented in the subclass.

Examples

>>> loss = MSELoss()
>>> prediction = torch.tensor([1.0, 2.0, 3.0])
>>> target = torch.tensor([1.0, 2.0, 3.0])
>>> weight = torch.tensor([1.0, 1.0, 1.0])
>>> loss.compute(prediction, target, weight)
tensor(0.)

Note

This method must be implemented in the subclass. It should return the computed MSELoss tensor.