credit.losses.msle
==================

.. py:module:: credit.losses.msle


Classes
-------

.. autoapisummary::

   credit.losses.msle.MSLELoss


Module Contents
---------------

.. py:class:: MSLELoss(reduction='mean')

   Bases: :py:obj:`torch.nn.Module`


   Mean Squared Logarithmic Error (MSLE) Loss Function.

   This loss function computes the mean squared logarithmic error between the
   predicted and target values. It is useful for handling targets that span
   several orders of magnitude.

   :param reduction: Specifies the reduction to apply to the output.
                     'mean' | 'none'. 'mean': the output is averaged; 'none': no reduction is applied.
   :type reduction: str


   .. py:attribute:: reduction
      :value: 'mean'



   .. py:method:: forward(prediction, target)

      Forward pass for MSLE loss.

      :param prediction: Predicted tensor.
      :type prediction: torch.Tensor
      :param target: Target tensor.
      :type target: torch.Tensor

      :returns: MSLE loss value.
      :rtype: torch.Tensor