rsquare loss is added

catalyst/contrib/nn/criterion/__init__.py

@@ -39,6 +39,7 @@
     HuberLossV0,
     CategoricalRegressionLoss,
     QuantileRegressionLoss,
+    RSquareLoss,
 )
 from catalyst.contrib.nn.criterion.supervised_contrastive import SupervisedContrastiveLoss
 from catalyst.contrib.nn.criterion.trevsky import FocalTrevskyLoss, TrevskyLoss

catalyst/contrib/nn/criterion/regression.py

@@ -1,5 +1,6 @@
 import torch
 from torch import nn
+from torch.nn import functional as F
 
 
 def _ce_with_logits(logits, target):
@@ -99,4 +100,21 @@ def forward(self, outputs: torch.Tensor, targets: torch.Tensor) -> torch.Tensor:
         return loss
 
 
-__all__ = ["HuberLossV0", "CategoricalRegressionLoss", "QuantileRegressionLoss"]
+class RSquareLoss(nn.Module):
+    """RSquareLoss"""
+
+    def forward(self, outputs: torch.Tensor, targets: torch.Tensor) -> torch.Tensor:
+        """Compute the loss.
+
+        Args:
+            outputs (torch.Tensor): model outputs
+            targets (torch.Tensor): targets
+
+        Returns:
+            torch.Tensor: computed loss
+        """
+        var_y = torch.var(targets, unbiased=False)
+        return 1.0 - F.mse_loss(outputs, targets, reduction="mean") / var_y
+
+
+__all__ = ["HuberLossV0", "CategoricalRegressionLoss", "QuantileRegressionLoss", "RSquareLoss"]

docs/api/contrib.rst

@@ -205,6 +205,13 @@ QuantileRegressionLoss
     :undoc-members:
     :show-inheritance:
 
+RSquareLoss
+*************************
+.. autoclass:: catalyst.contrib.nn.criterion.regression.RSquareLoss
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
 RecSys
 """"""