jinx/ComfyUI
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Make VAE Encode tiled node work with video VAE.

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comfyanonymous
2024-12-19 05:31:39 -05:00
parent 9f4b181ab3
commit c441048a4f
3 changed files with 70 additions and 17 deletions
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22
comfy/utils.py
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@@ -751,7 +751,7 @@ def get_tiled_scale_steps(width, height, tile_x, tile_y, overlap):
return rows * cols
@torch.inference_mode()
def tiled_scale_multidim(samples, function, tile=(64, 64), overlap = 8, upscale_amount = 4, out_channels = 3, output_device="cpu", pbar = None):
def tiled_scale_multidim(samples, function, tile=(64, 64), overlap=8, upscale_amount=4, out_channels=3, output_device="cpu", downscale=False, pbar=None):
dims = len(tile)
if not (isinstance(upscale_amount, (tuple, list))):
@@ -767,10 +767,22 @@ def tiled_scale_multidim(samples, function, tile=(64, 64), overlap = 8, upscale_
else:
return up * val
def get_downscale(dim, val):
up = upscale_amount[dim]
if callable(up):
return up(val)
else:
return val / up
if downscale:
get_scale = get_downscale
else:
get_scale = get_upscale
def mult_list_upscale(a):
out = []
for i in range(len(a)):
out.append(round(get_upscale(i, a[i])))
out.append(round(get_scale(i, a[i])))
return out
output = torch.empty([samples.shape[0], out_channels] + mult_list_upscale(samples.shape[2:]), device=output_device)
@@ -798,13 +810,13 @@ def tiled_scale_multidim(samples, function, tile=(64, 64), overlap = 8, upscale_
pos = max(0, min(s.shape[d + 2] - (overlap[d] + 1), it[d]))
l = min(tile[d], s.shape[d + 2] - pos)
s_in = s_in.narrow(d + 2, pos, l)
upscaled.append(round(get_upscale(d, pos)))
upscaled.append(round(get_scale(d, pos)))
ps = function(s_in).to(output_device)
mask = torch.ones_like(ps)
for d in range(2, dims + 2):
feather = round(get_upscale(d - 2, overlap[d - 2]))
feather = round(get_scale(d - 2, overlap[d - 2]))
if feather >= mask.shape[d]:
continue
for t in range(feather):
@@ -828,7 +840,7 @@ def tiled_scale_multidim(samples, function, tile=(64, 64), overlap = 8, upscale_
return output
def tiled_scale(samples, function, tile_x=64, tile_y=64, overlap = 8, upscale_amount = 4, out_channels = 3, output_device="cpu", pbar = None):
return tiled_scale_multidim(samples, function, (tile_y, tile_x), overlap, upscale_amount, out_channels, output_device, pbar)
return tiled_scale_multidim(samples, function, (tile_y, tile_x), overlap=overlap, upscale_amount=upscale_amount, out_channels=out_channels, output_device=output_device, pbar=pbar)
PROGRESS_BAR_ENABLED = True
def set_progress_bar_enabled(enabled):