From cbabcf8208d5b7caf932256bb159578eba546221 Mon Sep 17 00:00:00 2001
From: Chris Dumas <chrisldumas@hotmail.com>
Date: Fri, 4 Sep 2026 09:49:34 +0000
Subject: [PATCH] Offload H3 before latent upscale

---
 dumas_h3_longvideos.py            |  6 +++---
 tests/test_dumas_h3_longvideos.py | 22 ++++++++++++++++++----
 2 files changed, 21 insertions(+), 7 deletions(-)

diff --git a/dumas_h3_longvideos.py b/dumas_h3_longvideos.py
index eb6bfcb..28e88a6 100644
--- a/dumas_h3_longvideos.py
+++ b/dumas_h3_longvideos.py
@@ -6662,6 +6662,9 @@ class H3LongVideos:
                 parts = _nested_tensor_parts(out_samples)
                 if not getattr(out_samples, "is_nested", False) or len(parts) < 2:
                     raise RuntimeError("latent upscale expects a nested AV latent")
+                if latent_upscale_mode == "model" and str(latent_upscale_param.get("device", "cuda")) == "cuda" and hasattr(model, "clone_base_uuid"):
+                    mm.unload_model_and_clones(model, unload_additional_models=False)
+                    mm.soft_empty_cache()
                 upscaled_video, up_h, up_w = _upscale_latent_video(parts[0], latent_upscale_param)
                 full_audio = parts[1]
                 # Drop the first-pass sampling state before we start the refinement
@@ -6674,9 +6677,6 @@ class H3LongVideos:
                 target_h = int(up_h) * 16
                 if target_w <= 0 or target_h <= 0:
                     raise RuntimeError("latent upscale target size must be positive")
-                if latent_upscale_mode == "model" and str(latent_upscale_param.get("device", "cuda")) == "cuda" and hasattr(model, "clone_base_uuid"):
-                    mm.unload_model_and_clones(model, unload_additional_models=False)
-                    mm.soft_empty_cache()
                 upscale_cond, upscale_latent = _build_shot_conditioning(
                     clip, vae, prompt, target_w, target_h, ln, fps, handoff,
                     ref_images=refs, ref_image_size=ref_image_size,
diff --git a/tests/test_dumas_h3_longvideos.py b/tests/test_dumas_h3_longvideos.py
index 165b252..4539299 100644
--- a/tests/test_dumas_h3_longvideos.py
+++ b/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: