diff --git a/utils/torch_utils.py b/utils/torch_utils.py
index 40eed4ae..03337985 100644
--- a/utils/torch_utils.py
+++ b/utils/torch_utils.py
@@ -1,4 +1,5 @@
 import torch
+import torch.nn as nn
 
 
 def init_seeds(seed=0):
@@ -58,3 +59,26 @@ def fuse_conv_and_bn(conv, bn):
         fusedconv.bias.copy_(b_conv + b_bn)
 
         return fusedconv
+
+
+class FocalLoss(nn.Module):
+    # Wraps focal loss around existing loss_fcn() https://arxiv.org/pdf/1708.02002.pdf
+    # i.e. criteria = FocalLoss(nn.BCEWithLogitsLoss(), gamma=2.5)
+    def __init__(self, loss_fcn, alpha=1, gamma=2, reduction='mean'):
+        super(FocalLoss, self).__init__()
+        self.loss_fcn = loss_fcn
+        self.alpha = alpha
+        self.gamma = gamma
+        self.reduction = reduction
+
+    def forward(self, input, target):
+        loss = self.loss_fcn(input, target, reduction='none')
+        pt = torch.exp(-loss)
+        loss *= self.alpha * (1 - pt) ** self.gamma
+
+        if self.reduction == 'mean':
+            return loss.mean()
+        elif self.reduction == 'sum':
+            return loss.sum()
+        else:  # 'none'
+            return loss