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

1 files changed, 2 insertions, 2 deletions

diff --git a/modules/sd_samplers_cfg_denoiser.py b/modules/sd_samplers_cfg_denoiser.py
index bc9b97e4..b8101d38 100644
--- a/modules/sd_samplers_cfg_denoiser.py
+++ b/modules/sd_samplers_cfg_denoiser.py
@@ -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])