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authordrhead <1313496+drhead@users.noreply.github.com>2023-12-09 19:09:28 +0000
committerGitHub <noreply@github.com>2023-12-09 19:09:28 +0000
commit5381405eaa1e809e5cfb97522bd4c19d3c946079 (patch)
tree2d7630111fcdec4dd0c51f8a2cdfb4a3a4aace94 /modules/sd_samplers_timesteps.py
parent78acdcf677a96894651ff0d7d8287f2a994f3781 (diff)
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re-derive sqrt alpha bar and sqrt one minus alphabar
This is the only place these values are ever referenced outside of training code so this change is very justifiable and more consistent.
Diffstat (limited to 'modules/sd_samplers_timesteps.py')
-rw-r--r--modules/sd_samplers_timesteps.py2
1 files changed, 1 insertions, 1 deletions
diff --git a/modules/sd_samplers_timesteps.py b/modules/sd_samplers_timesteps.py
index b17a8f93..c4bd5c12 100644
--- a/modules/sd_samplers_timesteps.py
+++ b/modules/sd_samplers_timesteps.py
@@ -36,7 +36,7 @@ class CompVisTimestepsVDenoiser(torch.nn.Module):
self.inner_model = model
def predict_eps_from_z_and_v(self, x_t, t, v):
- return self.inner_model.sqrt_alphas_cumprod[t.to(torch.int), None, None, None] * v + self.inner_model.sqrt_one_minus_alphas_cumprod[t.to(torch.int), None, None, None] * x_t
+ return torch.sqrt(self.inner_model.alphas_cumprod)[t.to(torch.int), None, None, None] * v + torch.sqrt(1 - self.inner_model.alphas_cumprod)[t.to(torch.int), None, None, None] * x_t
def forward(self, input, timesteps, **kwargs):
model_output = self.inner_model.apply_model(input, timesteps, **kwargs)