average loss

enhancer/utils/loss.py

@@ -1,3 +1,4 @@
+from turtle import forward
 import torch
 import torch.nn as nn
 
@@ -23,6 +24,32 @@ class mean_absolute_error(nn.Module):
 
         return self.loss_fun(prediction, target)
 
+class Avergeloss(nn.Module):
+
+    def __init__(self,losses):
+
+        self.valid_losses = nn.ModuleList()
+        for loss in losses:
+            loss = self.validate_loss(loss)
+            self.valid_losses.append(loss())
+
+
+    def validate_loss(self,loss:str):
+        if loss not in LOSS_MAP.keys():
+            raise ValueError()
+        else:
+            return LOSS_MAP[loss]
+
+    def forward(self,prediction:torch.Tensor, target:torch.Tensor):
+        loss = 0.0
+        for loss_fun in self.valid_losses:
+            loss += loss_fun(prediction, target)
+        
+        return loss
+
+            
+
+
 LOSS_MAP = {"mea":mean_absolute_error, "mse": mean_squared_error}