Fix bug in CVAE example

The bug is caused by input validation (only accept value between 0 or 1 otherwise raise error) of F.binary_cross_entropy_loss after Pytorch 2.1 update. The fix is to manually mask the input of the loss function to avoid invalid value rather than removing the loss of invalid input from the final loss result.
Please refer to:#3273 for the initial report of the bug

examples/cvae/baseline.py

@@ -34,8 +34,12 @@ def __init__(self, masked_with=-1):
 
     def forward(self, input, target):
         target = target.view(input.shape)
-        loss = F.binary_cross_entropy(input, target, reduction="none")
-        loss[target == self.masked_with] = 0
+        # only calculate loss on target pixels (value = -1)
+        loss = F.binary_cross_entropy(
+            input[target != self.masked_with],
+            target[target != self.masked_with],
+            reduction="none",
+        )
         return loss.sum()
 
 

tests/test_examples.py

@@ -123,10 +123,7 @@
     "vae/ss_vae_M2.py --num-epochs=1 --enum-discrete=sequential",
     "vae/vae.py --num-epochs=1",
     "vae/vae_comparison.py --num-epochs=1",
-    pytest.param(
-        "cvae/main.py --num-quadrant-inputs=1 --num-epochs=1",
-        marks=pytest.mark.skip(reason="https://github.com/pyro-ppl/pyro/issues/3273"),
-    ),
+    "cvae/main.py --num-quadrant-inputs=1 --num-epochs=1",
     "contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=0 ",
     "contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=1 ",
     "contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=2 ",