Merge branch 'master' into dev/deepdanbooru

1 files changed, 15 insertions, 10 deletions

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 9c079e57..d9cca485 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -5,6 +5,8 @@ from torch import einsum
 from ldm.util import default

 from einops import rearrange

 

+from modules import shared

+

 

 # see https://github.com/basujindal/stable-diffusion/pull/117 for discussion

 def split_cross_attention_forward_v1(self, x, context=None, mask=None):

@@ -42,8 +44,19 @@ def split_cross_attention_forward(self, x, context=None, mask=None):
 

     q_in = self.to_q(x)

     context = default(context, x)

-    k_in = self.to_k(context) * self.scale

-    v_in = self.to_v(context)

+

+    hypernetwork = shared.selected_hypernetwork()

+    hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context.shape[2], None)

+

+    if hypernetwork_layers is not None:

+        k_in = self.to_k(hypernetwork_layers[0](context))

+        v_in = self.to_v(hypernetwork_layers[1](context))

+    else:

+        k_in = self.to_k(context)

+        v_in = self.to_v(context)

+

+    k_in *= self.scale

+

     del context, x

 

     q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in))

@@ -92,14 +105,6 @@ 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_)