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Update nodes_upscale_model.py

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Fix GPU utilization in upscale model node by keeping tensors on GPU. Added output_device parameter to tiled_scale function to prevent unnecessary CPU transfers, resulting in 2x faster processing. Commented out model CPU offloading to maintain GPU acceleration throughout the pipeline.
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yash-711 2025-03-11 18:16:11 +05:30 committed by GitHub
parent bc219a6487
commit 5cd7530637
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1 changed files with 3 additions and 2 deletions
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comfy_extras/nodes_upscale_model.py
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@ -66,14 +66,15 @@ class ImageUpscaleWithModel:
try:
steps = in_img.shape[0] * comfy.utils.get_tiled_scale_steps(in_img.shape[3], in_img.shape[2], tile_x=tile, tile_y=tile, overlap=overlap)
pbar = comfy.utils.ProgressBar(steps)
s = comfy.utils.tiled_scale(in_img, lambda a: upscale_model(a), tile_x=tile, tile_y=tile, overlap=overlap, upscale_amount=upscale_model.scale, pbar=pbar)
# KEY CHANGE: Pass device as output_device instead of default "cpu"
s = comfy.utils.tiled_scale(in_img, lambda a: upscale_model(a), tile_x=tile, tile_y=tile, overlap=overlap, upscale_amount=upscale_model.scale, output_device=device, pbar=pbar)
oom = False
except model_management.OOM_EXCEPTION as e:
tile //= 2
if tile < 128:
raise e
upscale_model.to("cpu")
# upscale_model.to("cpu") # Commented out to keep model on GPU because when processing batch images then model unnecessarily moves to CPU
s = torch.clamp(s.movedim(-3,-1), min=0, max=1.0)
return (s,)