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ditch --always-batch-cond-uncond in favor of an UI setting

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AUTOMATIC1111
2023-08-21 15:07:10 +03:00
parent d02c4da483
commit dfd6ea3fca
4 changed files with 6 additions and 5 deletions
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4
modules/sd_samplers_cfg_denoiser.py
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@@ -165,7 +165,7 @@ class CFGDenoiser(torch.nn.Module):
else:
cond_in = catenate_conds([tensor, uncond])
if shared.batch_cond_uncond:
if shared.opts.batch_cond_uncond:
x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict(cond_in, image_cond_in))
else:
x_out = torch.zeros_like(x_in)
@@ -175,7 +175,7 @@ class CFGDenoiser(torch.nn.Module):
x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(subscript_cond(cond_in, a, b), image_cond_in[a:b]))
else:
x_out = torch.zeros_like(x_in)
batch_size = batch_size*2 if shared.batch_cond_uncond else batch_size
batch_size = batch_size*2 if shared.opts.batch_cond_uncond else batch_size
for batch_offset in range(0, tensor.shape[0], batch_size):
a = batch_offset
b = min(a + batch_size, tensor.shape[0])