Move silu to sd_hijack

modules/sd_hijack.py

@@ -12,6 +12,7 @@ from ldm.util import default
 from einops import rearrange
 import ldm.modules.attention
 import ldm.modules.diffusionmodules.model
+from torch.nn.functional import silu
 
 
 # see https://github.com/basujindal/stable-diffusion/pull/117 for discussion
@@ -100,14 +101,6 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
 
     return self.to_out(r2)
 
-def nonlinearity_hijack(x):
-    # swish
-    t = torch.sigmoid(x)
-    x *= t
-    del t
-
-    return x
-
 def cross_attention_attnblock_forward(self, x):
         h_ = x
         h_ = self.norm(h_)
@@ -245,11 +238,12 @@ class StableDiffusionModelHijack:
         m.cond_stage_model = FrozenCLIPEmbedderWithCustomWords(m.cond_stage_model, self)
         self.clip = m.cond_stage_model
 
+        ldm.modules.diffusionmodules.model.nonlinearity = silu
+
         if cmd_opts.opt_split_attention_v1:
             ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward_v1
         elif not cmd_opts.disable_opt_split_attention and (cmd_opts.opt_split_attention or torch.cuda.is_available()):
             ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward
-            ldm.modules.diffusionmodules.model.nonlinearity = nonlinearity_hijack
             ldm.modules.diffusionmodules.model.AttnBlock.forward = cross_attention_attnblock_forward
 
         def flatten(el):

webui.py

@@ -22,10 +22,7 @@ import modules.txt2img
 import modules.img2img
 import modules.swinir as swinir
 import modules.sd_models
-from torch.nn.functional import silu
-import ldm
 
-ldm.modules.diffusionmodules.model.nonlinearity = silu
 
 modules.codeformer_model.setup_codeformer()
 modules.gfpgan_model.setup_gfpgan()