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optimized attention #177

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optimized attention #177

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5eef2ec
optimized attention
neonsecret Sep 4, 2022
7e85436
rolled back the cosmetic stuff
neonsecret Sep 5, 2022
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20 changes: 12 additions & 8 deletions ldm/modules/attention.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,7 +89,7 @@ def forward(self, x):
b, c, h, w = x.shape
qkv = self.to_qkv(x)
q, k, v = rearrange(qkv, 'b (qkv heads c) h w -> qkv b heads c (h w)', heads = self.heads, qkv=3)
k = k.softmax(dim=-1)
k = k.softmax(dim=-1)
context = torch.einsum('bhdn,bhen->bhde', k, v)
out = torch.einsum('bhde,bhdn->bhen', context, q)
out = rearrange(out, 'b heads c (h w) -> b (heads c) h w', heads=self.heads, h=h, w=w)
Expand Down Expand Up @@ -174,23 +174,27 @@ def forward(self, x, context=None, mask=None):
context = default(context, x)
k = self.to_k(context)
v = 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))

sim = einsum('b i d, b j d -> b i j', q, k) * self.scale
sim = einsum('b i d, b j d -> b i j', q, k) * self.scale # (8, 4096, 40)
del q, k

if exists(mask):
mask = rearrange(mask, 'b ... -> b (...)')
max_neg_value = -torch.finfo(sim.dtype).max
mask = repeat(mask, 'b j -> (b h) () j', h=h)
sim.masked_fill_(~mask, max_neg_value)
del mask

# attention, what we cannot get enough of
attn = sim.softmax(dim=-1)
# attention, what we cannot get enough of, by halves
sim[4:] = sim[4:].softmax(dim=-1)
sim[:4] = sim[:4].softmax(dim=-1)

out = einsum('b i j, b j d -> b i d', attn, v)
out = rearrange(out, '(b h) n d -> b n (h d)', h=h)
return self.to_out(out)
sim = einsum('b i j, b j d -> b i d', sim, v)
sim = rearrange(sim, '(b h) n d -> b n (h d)', h=h)
return self.to_out(sim)


class BasicTransformerBlock(nn.Module):
Expand Down Expand Up @@ -258,4 +262,4 @@ def forward(self, x, context=None):
x = block(x, context=context)
x = rearrange(x, 'b (h w) c -> b c h w', h=h, w=w)
x = self.proj_out(x)
return x + x_in
return x + x_in