hyper-param change

configs/trainers/DZGCoOp/vit_b16_c2_ep20_batch4_4+4ctx.yaml

@@ -38,7 +38,7 @@ TRAINER:
     PROMPT_DEPTH_VISION: 9
     PROMPT_DEPTH_TEXT: 9
     IMAGE_LOSS_WEIGHT: 8
-    TEXT_LOSS_WEIGHT_STRONG: 8
-    TEXT_LOSS_WEIGHT_WEAK: 24
+    TEXT_LOSS_WEIGHT_STRONG: 24
+    TEXT_LOSS_WEIGHT_WEAK: 8
     EWA_MEAN: 15
     EWA_STD: 1

trainers/dzgcoop.py

@@ -354,14 +354,14 @@ class DZGCoOp(TrainerX):
             L_sg_strong = F.l1_loss(text_features_strong, semantic_embeddings.cuda(), reduction='mean') * lambda2
             L_sg_weak = F.l1_loss(text_features_weak, semantic_embeddings.cuda(), reduction='mean') * lambda3
 
-            L_zlg = F.kl_div(
+            L_zpg = F.kl_div(
                 F.log_softmax(logits_final / 1, dim=1),
                 F.log_softmax(zero_shot_logits / 1, dim=1),
                 reduction='sum',
                 log_target=True
             ) * (1 * 1) / logits_final.numel()
 
-            L_zg = (L_zlg + L_sg_strong + L_sg_weak + L_zvg)
+            L_zg = (L_zpg + L_sg_strong + L_sg_weak + L_zvg)
             loss = (loss_ce + L_zg)
             optim.zero_grad()
             loss.backward()