Add remaining spatial split settings

H3_LONG_VIDEOS_GUIDE.md

@@ -1165,6 +1165,7 @@ What this really means:
 - the node then runs a short refinement pass over the upscaled latent with the sampler, scheduler, step count, denoise, and megapixel target you picked on the latent-upscale params node
 - if the target is larger than the spatial tile size, that refinement pass is processed in spatial batches using the same tile defaults as the upstream latent-split node
 - the spatial stitch mode follows the upstream overlap controls, including `linear`, `smoothstep`, `overwrite`, and `midpoint`
+- the node also carries the upstream split compatibility knobs (`chunk_length`, `resize_conditioning`, and `anchor_strength`) so the control surface stays in one place
 
 Good starting point:
 
@@ -1174,6 +1175,7 @@ Good starting point:
 - leave width and height at `0` unless you want an exact override; otherwise `megapixels` drives the target size
 - leave the spatial tile inputs at their defaults first: `512x512` tiles, `64` overlap, `0` fade width, `earlier` overlap mode
 - keep `linear` blend first unless you want to reproduce a specific upstream stitch style
+- leave the split compatibility knobs alone unless you specifically need to mirror the upstream node behavior
 
 The important part is that this stage is still a latent pass, not a pixel-space resize:
 

README.md

@@ -47,9 +47,9 @@
   - Per-shot directives now support `continuity:`, `ref_mode:`, `ref_noise_aug:`, `anchor_add:`, `soundscape:`, and `music:` in addition to the existing timing and wardrobe directives.
 
 - `Dumas H3 Latent Upscale Params`
-  - Inputs: `mode`, `model_name`, `method`, `width`, `height`, `device`, `precision`, `sampler_name`, `scheduler`, `steps`, `denoise`, `megapixels`, `tile_width`, `tile_height`, `overlap`, `fade_width`, `overlap_mode`, `overlap_blend`
+  - Inputs: `mode`, `model_name`, `method`, `width`, `height`, `device`, `precision`, `sampler_name`, `scheduler`, `steps`, `denoise`, `megapixels`, `tile_width`, `tile_height`, `overlap`, `fade_width`, `overlap_mode`, `overlap_blend`, `chunk_length`, `resize_conditioning`, `anchor_strength`
   - Output: `latent_upscale_param`
-  - Bundles the optional latent-space upscaler settings used by `Dumas H3 Long Videos` before decode, so the main node can rebuild conditioning at the target size and run a short refinement pass with your chosen sampler, scheduler, step count, denoise, and optional spatial batching.
+  - Bundles the optional latent-space upscaler settings used by `Dumas H3 Long Videos` before decode, so the main node can rebuild conditioning at the target size and run a short refinement pass with your chosen sampler, scheduler, step count, denoise, optional spatial batching, and the upstream split compatibility settings.
 
 - `Dumas H3 Beat Prompt`
   - Inputs: authored through the custom front-end beat editor

dumas_h3_latent_upscale.py

@@ -475,10 +475,16 @@ class H3LatentUpscaleParams:
                     "tooltip": "Which tile wins the overlap band when stitching the spatial batches back together."}),
                 "overlap_blend": (["linear", "smoothstep", "overwrite", "midpoint"], {"default": "linear",
                     "tooltip": "How overlap bands are blended when the spatial batches are stitched back together."}),
+                "chunk_length": ("INT", {"default": 136, "min": 17, "max": 100000, "step": 17,
+                    "tooltip": "Reserved for upstream split compatibility. 136 matches the original chunk-length default."}),
+                "resize_conditioning": ("BOOLEAN", {"default": False,
+                    "tooltip": "Reserved for upstream split compatibility. Leave OFF unless you need the original fallback behavior."}),
+                "anchor_strength": ("FLOAT", {"default": 0.999, "min": 0.0, "max": 1.0, "step": 0.01,
+                    "tooltip": "Reserved for upstream split compatibility. 0.999 matches the original anchor default."}),
             }
         }
 
-    def build(self, mode, model_name, method, width, height, device, precision, sampler_name, scheduler, steps, denoise, megapixels, tile_width, tile_height, overlap, fade_width, overlap_mode, overlap_blend):
+    def build(self, mode, model_name, method, width, height, device, precision, sampler_name, scheduler, steps, denoise, megapixels, tile_width, tile_height, overlap, fade_width, overlap_mode, overlap_blend, chunk_length, resize_conditioning, anchor_strength):
         width = int(width)
         height = int(height)
         steps = int(steps)
@@ -486,6 +492,8 @@ class H3LatentUpscaleParams:
         tile_height = int(tile_height)
         overlap = int(overlap)
         fade_width = int(fade_width)
+        chunk_length = int(chunk_length)
+        anchor_strength = float(anchor_strength)
         if mode == "off":
             return ({
                 "mode": "off",
@@ -503,6 +511,9 @@ class H3LatentUpscaleParams:
                 "fade_width": fade_width,
                 "overlap_mode": overlap_mode,
                 "overlap_blend": overlap_blend,
+                "chunk_length": chunk_length,
+                "resize_conditioning": bool(resize_conditioning),
+                "anchor_strength": anchor_strength,
             },)
         if width > 0:
             width = int(round(width / 32.0)) * 32
@@ -528,6 +539,9 @@ class H3LatentUpscaleParams:
             "fade_width": fade_width,
             "overlap_mode": overlap_mode,
             "overlap_blend": overlap_blend,
+            "chunk_length": chunk_length,
+            "resize_conditioning": bool(resize_conditioning),
+            "anchor_strength": anchor_strength,
         },)
 
 

tests/test_dumas_h3_longvideos.py

@@ -1133,6 +1133,9 @@ class DumasH3LongVideosHelperTests(unittest.TestCase):
         self.assertEqual(required["fade_width"][1]["default"], 0)
         self.assertEqual(required["overlap_mode"][1]["default"], "earlier")
         self.assertEqual(required["overlap_blend"][1]["default"], "linear")
+        self.assertEqual(required["chunk_length"][1]["default"], 136)
+        self.assertFalse(required["resize_conditioning"][1]["default"])
+        self.assertEqual(required["anchor_strength"][1]["default"], 0.999)
 
     def test_compose_persistent_does_not_expand_ambiguous_plural_to_full_cast(self):
         active = self.module.parse_wardrobe(