From 7250d013dfac0269b16d30a31b77242a4b7b3672 Mon Sep 17 00:00:00 2001
From: kijai <40791699+kijai@users.noreply.github.com>
Date: Thu, 5 Mar 2026 15:20:42 +0200
Subject: [PATCH] Not necessary for this model anymore

---
 comfy/ldm/rt_detr/rtdetr_v4.py |  2 +-
 comfy/ops.py                   | 31 -------------------------------
 2 files changed, 1 insertion(+), 32 deletions(-)

diff --git a/comfy/ldm/rt_detr/rtdetr_v4.py b/comfy/ldm/rt_detr/rtdetr_v4.py
index 3233dbdf6..426d3e6c3 100644
--- a/comfy/ldm/rt_detr/rtdetr_v4.py
+++ b/comfy/ldm/rt_detr/rtdetr_v4.py
@@ -31,7 +31,7 @@ class ConvBNAct(nn.Module):
         super().__init__()
 
         self.conv = operations.Conv2d(ic, oc, k, s, (k - 1) // 2, groups=groups, bias=False, device=device, dtype=dtype)
-        self.bn   = operations.BatchNorm2d(oc, device=device, dtype=dtype)
+        self.bn   = nn.BatchNorm2d(oc, device=device, dtype=dtype)
         self.act  = nn.ReLU() if use_act else nn.Identity()
 
     def forward(self, x):
diff --git a/comfy/ops.py b/comfy/ops.py
index 130dad74e..3752ed395 100644
--- a/comfy/ops.py
+++ b/comfy/ops.py
@@ -483,34 +483,6 @@ class disable_weight_init:
             else:
                 return super().forward(*args, **kwargs)
 
-    class BatchNorm2d(torch.nn.BatchNorm2d, CastWeightBiasOp):
-        def reset_parameters(self):
-            return None
-
-        def forward_comfy_cast_weights(self, input):
-            if self.weight is not None:
-                weight, bias, offload_stream = cast_bias_weight(self, input, offloadable=True)
-            else:
-                weight = None
-                bias = None
-                offload_stream = None
-
-            x = torch.nn.functional.batch_norm(
-                input,
-                comfy.model_management.cast_to(self.running_mean, dtype=input.dtype, device=input.device),
-                comfy.model_management.cast_to(self.running_var, dtype=input.dtype, device=input.device),
-                weight, bias, self.training or not self.track_running_stats,
-                self.momentum, self.eps
-            )
-            uncast_bias_weight(self, weight, bias, offload_stream)
-            return x
-
-        def forward(self, *args, **kwargs):
-            run_every_op()
-            if self.comfy_cast_weights or len(self.weight_function) > 0 or len(self.bias_function) > 0:
-                return self.forward_comfy_cast_weights(*args, **kwargs)
-            else:
-                return super().forward(*args, **kwargs)
 
     class ConvTranspose2d(torch.nn.ConvTranspose2d, CastWeightBiasOp):
         def reset_parameters(self):
@@ -625,9 +597,6 @@ class manual_cast(disable_weight_init):
     class Embedding(disable_weight_init.Embedding):
         comfy_cast_weights = True
 
-    class BatchNorm2d(disable_weight_init.BatchNorm2d):
-        comfy_cast_weights = True
-
 
 def fp8_linear(self, input):
     """