Use adaptive CUDA latent upscale chunking

tests/test_dumas_h3_longvideos.py

@@ -1171,8 +1171,8 @@ class DumasH3LongVideosHelperTests(unittest.TestCase):
         self.assertFalse(required["brightness_match"][1]["default"])
         self.assertEqual(required["dynamic_fade"][1]["default"], "off")
         self.assertEqual(required["dynamic_fade_min"][1]["default"], 32)
-        self.assertEqual(required["chunk_length"][1]["default"], 17)
-        self.assertEqual(required["temporal_overlap"][1]["default"], 0)
+        self.assertEqual(required["chunk_length"][1]["default"], 85)
+        self.assertEqual(required["temporal_overlap"][1]["default"], 17)
         self.assertFalse(required["resize_conditioning"][1]["default"])
         self.assertEqual(required["anchor_strength"][1]["default"], 0.999)
 
@@ -1262,14 +1262,25 @@ class DumasH3LongVideosHelperTests(unittest.TestCase):
         self.assertEqual(smaller["chunk_length"], 17)
         self.assertEqual(smaller["temporal_overlap"], 0)
 
-    def test_cuda_model_temporal_params_cap_saved_workflows(self):
+    def test_cuda_model_temporal_params_keep_splitting_saved_workflows(self):
         latent = importlib.import_module("dumas_h3_latent_upscale")
         chunk_length, temporal_overlap = latent._effective_temporal_params({
             "mode": "model",
             "device": "cuda",
             "chunk_length": 85,
             "temporal_overlap": 17,
-        })
+        }, frame_count=124)
+        self.assertEqual(chunk_length, 85)
+        self.assertEqual(temporal_overlap, 17)
+
+    def test_cuda_model_temporal_params_cap_single_chunk_saved_workflows(self):
+        latent = importlib.import_module("dumas_h3_latent_upscale")
+        chunk_length, temporal_overlap = latent._effective_temporal_params({
+            "mode": "model",
+            "device": "cuda",
+            "chunk_length": 85,
+            "temporal_overlap": 17,
+        }, frame_count=85)
         self.assertEqual(chunk_length, 17)
         self.assertEqual(temporal_overlap, 0)