Add weighted CE proxy and fix loss imports

opengait/modeling/losses/bce.py

@@ -1,14 +1,21 @@
+from __future__ import annotations
+
 import torch
+
+from opengait.evaluation.metric import mean_iou
+from opengait.utils.common import Odict
+
 from .base import BaseLoss
-from evaluation import mean_iou
 
 
 class BinaryCrossEntropyLoss(BaseLoss):
-    def __init__(self, loss_term_weight=1.0, eps=1.0e-9):
+    eps: float
+
+    def __init__(self, loss_term_weight: float = 1.0, eps: float = 1.0e-9) -> None:
         super(BinaryCrossEntropyLoss, self).__init__(loss_term_weight)
         self.eps = eps
 
-    def forward(self, logits, labels):
+    def forward(self, logits: torch.Tensor, labels: torch.Tensor) -> tuple[torch.Tensor, Odict]:
         """
             logits: [n, 1, h, w]
             labels: [n, 1, h, w]