Fail loud on Trellis invalid batch metadata

comfy/sample.py

@@ -14,6 +14,10 @@ def prepare_noise_inner(latent_image, generator, noise_inds=None):
             noise_inds = np.arange(latent_image.size(0), dtype=np.int64)
         else:
             noise_inds = np.asarray(noise_inds, dtype=np.int64)
+            if noise_inds.shape[0] != latent_image.size(0):
+                raise ValueError(
+                    f"Trellis2 noise_inds length {noise_inds.shape[0]} does not match latent batch {latent_image.size(0)}"
+                )
 
         base_seed = int(generator.initial_seed())
         unique_inds = np.unique(noise_inds)

comfy_extras/nodes_trellis2.py

@@ -800,6 +800,11 @@ class EmptyTextureLatentTrellis2(IO.ComfyNode):
 
         elif isinstance(structure_or_coords, torch.Tensor) and structure_or_coords.ndim == 2:
             coords = structure_or_coords.int()
+        else:
+            raise ValueError(
+                "structure_or_coords must be a voxel input with data.ndim == 4, "
+                f'a dict containing "coords", or a 2D torch.Tensor; got {type(structure_or_coords).__name__}'
+            )
 
         shape_batch_index = normalize_batch_index(shape_latent.get("batch_index"))
         shape_latent = shape_latent["samples"]

tests-unit/comfy_extras_test/nodes_trellis2_test.py

@@ -224,6 +224,15 @@ class TestTrellisBatchSemantics(unittest.TestCase):
                 13,
             )
 
+    def test_empty_texture_latent_rejects_invalid_structure_input(self):
+        with self.assertRaises(ValueError):
+            nodes_trellis2.EmptyTextureLatentTrellis2.execute(
+                "bad-input",
+                {"samples": torch.zeros(1, 32, 2, 1)},
+                DummyCloneModel(),
+                13,
+            )
+
     def test_flatten_batched_sparse_latent_validates_coord_counts(self):
         samples = torch.zeros(2, 32, 3, 1)
         coords = torch.tensor(

tests-unit/comfy_test/sample_test.py

@@ -42,6 +42,16 @@ class TestPrepareNoiseInnerTrellis(unittest.TestCase):
         self.assertTrue(torch.equal(noise[1:2, :, :5, :], expected1))
         self.assertTrue(torch.equal(noise[0, :, 3:, :], torch.zeros_like(noise[0, :, 3:, :])))
 
+    def test_coord_counts_noise_inds_length_must_match_batch(self):
+        latent = torch.zeros(2, 4, 5, 1)
+        latent.trellis_coord_counts = torch.tensor([3, 5], dtype=torch.int64)
+
+        generator = torch.Generator(device="cpu")
+        generator.manual_seed(456)
+
+        with self.assertRaises(ValueError):
+            comfy.sample.prepare_noise_inner(latent, generator, noise_inds=[7])
+
 
 if __name__ == "__main__":
     unittest.main()