Offload H3 before latent upscale

tests/test_dumas_h3_longvideos.py

@@ -373,6 +373,7 @@ class DumasH3LongVideosHelperTests(unittest.TestCase):
         original_cleanup = self.module._deep_cleanup
         original_upscale = self.module._upscale_latent_video
         original_copy_sample = self.module._copy_sample_latent
+        original_unload = getattr(self.module.mm, "unload_model_and_clones", None)
         original_nested = getattr(self.module.comfy.nested_tensor, "NestedTensor", None)
         try:
             self.module.comfy.nested_tensor.NestedTensor = FakeNestedTensor
@@ -395,20 +396,28 @@ class DumasH3LongVideosHelperTests(unittest.TestCase):
             def cleanup():
                 order.append("cleanup")
 
+            def unload_model_and_clones(*_args, **_kwargs):
+                order.append("unload_h3")
+
+            def upscale_latent_video(video, param):
+                order.append("upscale")
+                return FakeTensor("upv"), 8, 16
+
             self.module.nodes.common_ksampler = common_ksampler
             self.module._build_shot_conditioning = lambda *_args, **_kwargs: (
                 "cond",
                 {"samples": FakeNestedTensor((FakeTensor("basev"), FakeTensor("basea")))},
             )
             self.module._evict_all_but = lambda *_args, **_kwargs: None
-            self.module._upscale_latent_video = lambda video, param: (FakeTensor("upv"), 8, 16)
+            self.module.mm.unload_model_and_clones = unload_model_and_clones
+            self.module._upscale_latent_video = upscale_latent_video
             self.module._copy_sample_latent = lambda sampled: sampled["samples"].unbind()
             self.module._decode_video = decode_video
             self.module._decode_audio = decode_audio
             self.module._deep_cleanup = cleanup
 
             self.module.H3LongVideos()._render(
-                model=object(),
+                model=types.SimpleNamespace(clone_base_uuid="h3"),
                 clip=types.SimpleNamespace(
                     tokenize=lambda text, **kwargs: text,
                     encode_from_tokens_scheduled=lambda tokens: tokens,
@@ -427,7 +436,7 @@ class DumasH3LongVideosHelperTests(unittest.TestCase):
                 latent_upscale_param={
                     "mode": "model",
                     "model_name": "upscale.safetensors",
-                    "device": "cpu",
+                    "device": "cuda",
                     "precision": "fp16",
                     "sampler_name": "euler_ancestral",
                     "scheduler": "simple",
@@ -438,7 +447,8 @@ class DumasH3LongVideosHelperTests(unittest.TestCase):
             )
 
             self.assertEqual(order[0], "sample")
-            self.assertEqual(order[1], "latent_upscale_sample")
+            self.assertLess(order.index("unload_h3"), order.index("upscale"))
+            self.assertLess(order.index("upscale"), order.index("latent_upscale_sample"))
             self.assertLess(order.index("audio"), order.index("video"))
             self.assertEqual(order[-1], "cleanup")
         finally:
@@ -450,6 +460,10 @@ class DumasH3LongVideosHelperTests(unittest.TestCase):
             self.module._deep_cleanup = original_cleanup
             self.module._upscale_latent_video = original_upscale
             self.module._copy_sample_latent = original_copy_sample
+            if original_unload is None:
+                delattr(self.module.mm, "unload_model_and_clones")
+            else:
+                self.module.mm.unload_model_and_clones = original_unload
             if original_nested is None:
                 delattr(self.module.comfy.nested_tensor, "NestedTensor")
             else: