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Add hypernetwork support to split cross attention v1

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* Add hypernetwork support to split_cross_attention_forward_v1
* Fix device check in esrgan_model.py to use devices.device_esrgan instead of shared.device
This commit is contained in:
brkirch
2022-10-08 01:47:02 -04:00
committed by AUTOMATIC1111
parent a958f9b3fd
commit f2055cb1d4
2 changed files with 15 additions and 5 deletions
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18
modules/sd_hijack_optimizations.py
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@@ -12,13 +12,22 @@ from modules import shared
def split_cross_attention_forward_v1(self, x, context=None, mask=None):
h = self.heads
q = self.to_q(x)
q_in = self.to_q(x)
context = default(context, x)
k = self.to_k(context)
v = 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)
del context, x
q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q, k, v))
q, k, v = map(lambda t: rearrange(t, 'b n (h d) -> (b h) n d', h=h), (q_in, k_in, v_in))
del q_in, k_in, v_in
r1 = torch.zeros(q.shape[0], q.shape[1], v.shape[2], device=q.device)
for i in range(0, q.shape[0], 2):
@@ -31,6 +40,7 @@ def split_cross_attention_forward_v1(self, x, context=None, mask=None):
r1[i:end] = einsum('b i j, b j d -> b i d', s2, v[i:end])
del s2
del q, k, v
r2 = rearrange(r1, '(b h) n d -> b n (h d)', h=h)
del r1