From 9093301a49a90b654a7f37f6f621784b78579e2d Mon Sep 17 00:00:00 2001
From: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Date: Fri, 27 Jun 2025 11:14:56 -0700
Subject: [PATCH] Don't add tiny bit of random noise when VAE encoding. (#8705)

Shouldn't change outputs but might make things a tiny bit more
deterministic.
---
 comfy/ldm/models/autoencoder.py | 8 ++------
 1 file changed, 2 insertions(+), 6 deletions(-)

diff --git a/comfy/ldm/models/autoencoder.py b/comfy/ldm/models/autoencoder.py
index e6493155e..13bd6e16b 100644
--- a/comfy/ldm/models/autoencoder.py
+++ b/comfy/ldm/models/autoencoder.py
@@ -11,7 +11,7 @@ from comfy.ldm.modules.ema import LitEma
 import comfy.ops
 
 class DiagonalGaussianRegularizer(torch.nn.Module):
-    def __init__(self, sample: bool = True):
+    def __init__(self, sample: bool = False):
         super().__init__()
         self.sample = sample
 
@@ -19,16 +19,12 @@ class DiagonalGaussianRegularizer(torch.nn.Module):
         yield from ()
 
     def forward(self, z: torch.Tensor) -> Tuple[torch.Tensor, dict]:
-        log = dict()
         posterior = DiagonalGaussianDistribution(z)
         if self.sample:
             z = posterior.sample()
         else:
             z = posterior.mode()
-        kl_loss = posterior.kl()
-        kl_loss = torch.sum(kl_loss) / kl_loss.shape[0]
-        log["kl_loss"] = kl_loss
-        return z, log
+        return z, None
 
 
 class AbstractAutoencoder(torch.nn.Module):