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Add progress to vae decode tiled

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pythongosssss 2023-04-24 11:55:44 +01:00
parent 737c158763
commit c8c9926eeb
2 changed files with 12 additions and 4 deletions
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12
comfy/sd.py
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@ -1,6 +1,7 @@
import torch
import contextlib
import copy
from tqdm.auto import tqdm
import sd1_clip
import sd2_clip
@ -437,11 +438,16 @@ class VAE:
self.device = device
def decode_tiled_(self, samples, tile_x=64, tile_y=64, overlap = 16):
it_1 = -(samples.shape[2] // -(tile_y * 2 - overlap)) * -(samples.shape[3] // -(tile_x // 2 - overlap))
it_2 = -(samples.shape[2] // -(tile_y // 2 - overlap)) * -(samples.shape[3] // -(tile_x * 2 - overlap))
it_3 = -(samples.shape[2] // -(tile_y - overlap)) * -(samples.shape[3] // -(tile_x - overlap))
pbar = tqdm(total=samples.shape[0] * (it_1 + it_2 + it_3))
decode_fn = lambda a: (self.first_stage_model.decode(1. / self.scale_factor * a.to(self.device)) + 1.0)
output = torch.clamp((
(utils.tiled_scale(samples, decode_fn, tile_x // 2, tile_y * 2, overlap, upscale_amount = 8) +
utils.tiled_scale(samples, decode_fn, tile_x * 2, tile_y // 2, overlap, upscale_amount = 8) +
utils.tiled_scale(samples, decode_fn, tile_x, tile_y, overlap, upscale_amount = 8))
(utils.tiled_scale(samples, decode_fn, tile_x // 2, tile_y * 2, overlap, upscale_amount = 8, pbar = pbar) +
utils.tiled_scale(samples, decode_fn, tile_x * 2, tile_y // 2, overlap, upscale_amount = 8, pbar = pbar) +
utils.tiled_scale(samples, decode_fn, tile_x, tile_y, overlap, upscale_amount = 8, pbar = pbar))
/ 3.0) / 2.0, min=0.0, max=1.0)
return output

4
comfy/utils.py
View File

@ -63,7 +63,7 @@ def common_upscale(samples, width, height, upscale_method, crop):
return torch.nn.functional.interpolate(s, size=(height, width), mode=upscale_method)
@torch.inference_mode()
def tiled_scale(samples, function, tile_x=64, tile_y=64, overlap = 8, upscale_amount = 4, out_channels = 3):
def tiled_scale(samples, function, tile_x=64, tile_y=64, overlap = 8, upscale_amount = 4, out_channels = 3, pbar = None):
output = torch.empty((samples.shape[0], out_channels, round(samples.shape[2] * upscale_amount), round(samples.shape[3] * upscale_amount)), device="cpu")
for b in range(samples.shape[0]):
s = samples[b:b+1]
@ -83,6 +83,8 @@ def tiled_scale(samples, function, tile_x=64, tile_y=64, overlap = 8, upscale_am
mask[:,:,:,mask.shape[3]- 1 - t: mask.shape[3]- t] *= ((1.0/feather) * (t + 1))
out[:,:,round(y*upscale_amount):round((y+tile_y)*upscale_amount),round(x*upscale_amount):round((x+tile_x)*upscale_amount)] += ps * mask
out_div[:,:,round(y*upscale_amount):round((y+tile_y)*upscale_amount),round(x*upscale_amount):round((x+tile_x)*upscale_amount)] += mask
if pbar is not None:
pbar.update(1)
output[b:b+1] = out/out_div
return output