diff --git a/dumas_h3_latent_upscale.py b/dumas_h3_latent_upscale.py index dae4ecc..4e4df37 100644 --- a/dumas_h3_latent_upscale.py +++ b/dumas_h3_latent_upscale.py @@ -42,6 +42,24 @@ LATENTS_STD = [ _LATENT_UPSCALE_FOLDER = "latent_upscale_models" MP_UNIT = 1024 * 1024 RES_MULTIPLE = 32 +CUDA_MODEL_CHUNK_LENGTH = 17 + + +def _uses_cuda_model_upscale(param): + mode = str(param.get("mode") or "") + model_name = str(param.get("model_name") or "") + device = str(param.get("device", "cuda") or "cuda") + has_model_name = bool(model_name and model_name != "none" and not model_name.startswith("(no upscale models")) + return device == "cuda" and (mode == "model" or has_model_name) + + +def _effective_temporal_params(param): + chunk_length = int(param.get("chunk_length", 0) or 0) + temporal_overlap = int(param.get("temporal_overlap", 0) or 0) + if _uses_cuda_model_upscale(param): + chunk_length = CUDA_MODEL_CHUNK_LENGTH if chunk_length <= 0 else min(chunk_length, CUDA_MODEL_CHUNK_LENGTH) + temporal_overlap = min(max(0, temporal_overlap), max(0, chunk_length - 17)) + return chunk_length, temporal_overlap def _models_dir(): @@ -735,17 +753,19 @@ def upscale_video_interp(video, param): def _upscale_video_temporal_chunks(video, param, upscaler): if video.device.type != "cpu": video = video.to(device="cpu", copy=True) - chunk_length = int(param.get("chunk_length", 0) or 0) - temporal_overlap = int(param.get("temporal_overlap", 0) or 0) + chunk_length, temporal_overlap = _effective_temporal_params(param) + chunk_param = dict(param) + chunk_param["chunk_length"] = chunk_length + chunk_param["temporal_overlap"] = temporal_overlap anchor_strength = float(param.get("anchor_strength", 0.999) or 0.999) t = int(video.shape[2]) frame_count = _frames_for_tokens(t) if chunk_length <= 0 or frame_count <= chunk_length: - return upscaler(video, param) + return upscaler(video, chunk_param) bounds = _temporal_segments(t, chunk_length, temporal_overlap) if len(bounds) <= 1: - return upscaler(video, param) + return upscaler(video, chunk_param) orig_dtype = video.dtype out = None @@ -753,11 +773,11 @@ def _upscale_video_temporal_chunks(video, param, upscaler): for i, (k0, f0, k1, f1) in enumerate(bounds): chunk = video[:, :, k0:k1].contiguous() try: - chunk_out, chunk_h, chunk_w = upscaler(chunk, param) + chunk_out, chunk_h, chunk_w = upscaler(chunk, chunk_param) except RuntimeError as exc: if "out of memory" not in str(exc).lower(): raise - smaller = _shrink_temporal_param(param) + smaller = _shrink_temporal_param(chunk_param) if smaller is None: raise try: @@ -872,10 +892,10 @@ class H3LatentUpscaleParams: "tooltip": "Temporal fade schedule over each tile's sampling. Off keeps the fade fixed; narrowing shrinks it over steps; widening grows it over steps."}), "dynamic_fade_min": ("INT", {"default": 32, "min": 0, "max": 4096, "step": 32, "tooltip": "Minimum fade width used by dynamic_fade when it is enabled."}), - "chunk_length": ("INT", {"default": 85, "min": 17, "max": 100000, "step": 17, - "tooltip": "Temporal chunk length for the latent upscale stage. 85 matches the practical upstream example and helps lower peak VRAM."}), - "temporal_overlap": ("INT", {"default": 17, "min": 0, "max": 100000, "step": 17, - "tooltip": "Temporal overlap between latent chunks. 17 matches the upstream split example and reduces seam risk."}), + "chunk_length": ("INT", {"default": 17, "min": 17, "max": 100000, "step": 17, + "tooltip": "Temporal chunk length for latent upscale. CUDA model upscale is capped to 17 internally so short long-video shots do not bypass splitting and OOM."}), + "temporal_overlap": ("INT", {"default": 0, "min": 0, "max": 100000, "step": 17, + "tooltip": "Temporal overlap between latent chunks. CUDA model upscale uses 0 when capped to one H3 block to minimize peak VRAM."}), "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, @@ -936,9 +956,9 @@ class H3LatentUpscaleParams: "anchor_strength": anchor_strength, },) if chunk_length % 17 != 0: - raise ValueError("chunk_length must be a multiple of 17 pixels") + raise ValueError("chunk_length must be a multiple of 17 frames") if temporal_overlap % 17 != 0: - raise ValueError("temporal_overlap must be a multiple of 17 pixels") + raise ValueError("temporal_overlap must be a multiple of 17 frames") if temporal_overlap >= chunk_length: raise ValueError("temporal_overlap must be smaller than chunk_length") if width > 0: diff --git a/tests/test_dumas_h3_longvideos.py b/tests/test_dumas_h3_longvideos.py index 55249a1..92fddb0 100644 --- a/tests/test_dumas_h3_longvideos.py +++ b/tests/test_dumas_h3_longvideos.py @@ -1165,8 +1165,8 @@ 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"], 85) - self.assertEqual(required["temporal_overlap"][1]["default"], 17) + self.assertEqual(required["chunk_length"][1]["default"], 17) + self.assertEqual(required["temporal_overlap"][1]["default"], 0) self.assertFalse(required["resize_conditioning"][1]["default"]) self.assertEqual(required["anchor_strength"][1]["default"], 0.999) @@ -1256,6 +1256,28 @@ 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): + 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, + }) + self.assertEqual(chunk_length, 17) + self.assertEqual(temporal_overlap, 0) + + def test_interp_temporal_params_preserve_upstream_defaults(self): + latent = importlib.import_module("dumas_h3_latent_upscale") + chunk_length, temporal_overlap = latent._effective_temporal_params({ + "mode": "interp", + "device": "cuda", + "chunk_length": 85, + "temporal_overlap": 17, + }) + self.assertEqual(chunk_length, 85) + self.assertEqual(temporal_overlap, 17) + def test_upscale_video_model_raises_when_gpu_cannot_shrink(self): latent = importlib.import_module("dumas_h3_latent_upscale")