dicee.models.sampled_loss
=========================

.. py:module:: dicee.models.sampled_loss

.. autoapi-nested-parse::

   Reusable loss for positive-first groups of negative samples.



Functions
---------

.. autoapisummary::

   dicee.models.sampled_loss.grouped_adversarial_bce


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

.. py:function:: grouped_adversarial_bce(logits: torch.Tensor, targets: torch.Tensor, temperature: float) -> torch.Tensor

   Balance the positive against a weighted negative group (ULTRA convention).

   Positive temperature uses detached softmax(logits / temperature); zero uses
   uniform negative weights. This intentionally differs from ordinary mean BCE.