From 5381405eaa1e809e5cfb97522bd4c19d3c946079 Mon Sep 17 00:00:00 2001
From: drhead <1313496+drhead@users.noreply.github.com>
Date: Sat, 9 Dec 2023 14:09:28 -0500
Subject: 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.
---
 modules/sd_samplers_timesteps.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'modules/sd_samplers_timesteps.py')

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)
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