(test) test ResNet backbone

configs/default.yaml

@@ -32,7 +32,7 @@ eval:
   fine_batch: 16
 
 optim:
-  iters: 10000
+  iters: 5000
   batch_size: 4
   lr: 6e-5
   weight_decay: 0.01
@@ -45,7 +45,7 @@ seed: 42
 out_dir: runs/wireseghr
 eval_interval: 200
 ckpt_interval: 400
-resume: runs/wireseghr/ckpt_1800.pt  # optional
+resume: runs/wireseghr/ckpt_4800.pt  # optional
 
 # dataset paths (placeholders)
 data:

tests/test_model_forward.py

@@ -17,3 +17,19 @@ def test_wireseghr_forward_shapes():
 
     logits_fine = model.forward_fine(x)
     assert logits_fine.shape == logits_coarse.shape
+
+
+def test_wireseghr_forward_shapes_resnet50():
+    # Ensure ResNet-50 alt backbone works and keeps 1/4 stage0 resolution
+    model = WireSegHR(backbone="resnet50", in_channels=3, pretrained=False)
+
+    x = torch.randn(1, 3, 64, 64)
+    logits_coarse, cond = model.forward_coarse(x)
+    assert logits_coarse.shape[0] == 1 and logits_coarse.shape[1] == 2
+    assert cond.shape[0] == 1 and cond.shape[1] == 1
+    # ResNet stage0 is also 1/4 of input
+    assert logits_coarse.shape[2] == 16 and logits_coarse.shape[3] == 16
+    assert cond.shape[2] == 16 and cond.shape[3] == 16
+
+    logits_fine = model.forward_fine(x)
+    assert logits_fine.shape == logits_coarse.shape