Sped up sampling 20x

src/losses/crps_metric.py

@@ -15,7 +15,7 @@ class CRPSLoss(nn.Module):
         # preds shape: [batch_size, num_quantiles]
 
         # unsqueeze target
-        target = target.unsqueeze(-1)
+        # target = target.unsqueeze(-1)
 
         mask = (preds > target).float()
         test = self.quantiles_tensor - mask

src/losses/pinball_loss.py

@@ -1,24 +1,27 @@
 import torch
 from torch import nn
 
+
 class PinballLoss(nn.Module):
     def __init__(self, quantiles):
         super(PinballLoss, self).__init__()
         self.quantiles_tensor = torch.tensor(quantiles, dtype=torch.float32)
-        
+        self.quantiles = self.quantiles_tensor.tolist()
+
     def forward(self, pred, target):
         error = target - pred
         upper = self.quantiles_tensor * error
-        lower = (self.quantiles_tensor - 1) * error 
+        lower = (self.quantiles_tensor - 1) * error
         losses = torch.max(lower, upper)
         loss = torch.mean(torch.mean(losses, dim=0))
         return loss
-    
+
 
 class NonAutoRegressivePinballLoss(nn.Module):
     def __init__(self, quantiles):
         super(NonAutoRegressivePinballLoss, self).__init__()
         self.quantiles_tensor = torch.tensor(quantiles, dtype=torch.float32)
+        self.quantiles = self.quantiles_tensor.tolist()
 
     def forward(self, pred, target):
         pred = pred.reshape(-1, 96, len(self.quantiles_tensor))