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Force temporal chunks for CUDA latent upscale

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chris.dumas
2026-09-04 10:22:41 +00:00
parent 618a48e4d9
commit e8599055a1
2 changed files with 56 additions and 14 deletions
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dumas_h3_latent_upscale.py
+32 -12
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@@ -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: