From 30a2de164bcb991057b212b47846ea3c13715ee5 Mon Sep 17 00:00:00 2001
From: Laughing <61612323+Laughing-q@users.noreply.github.com>
Date: Mon, 27 Jan 2025 18:04:03 +0800
Subject: [PATCH] Fix `AutoBatch` when working with RT-DETR models (#18912)

---
 ultralytics/models/utils/ops.py  | 2 +-
 ultralytics/utils/torch_utils.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/ultralytics/models/utils/ops.py b/ultralytics/models/utils/ops.py
index eafc7440..7133072e 100644
--- a/ultralytics/models/utils/ops.py
+++ b/ultralytics/models/utils/ops.py
@@ -172,7 +172,7 @@ def get_cdn_group(
             bounding boxes, attention mask and meta information for denoising. If not in training mode or 'num_dn'
             is less than or equal to 0, the function returns None for all elements in the tuple.
     """
-    if (not training) or num_dn <= 0:
+    if (not training) or num_dn <= 0 or batch is None:
         return None, None, None, None
     gt_groups = batch["gt_groups"]
     total_num = sum(gt_groups)
diff --git a/ultralytics/utils/torch_utils.py b/ultralytics/utils/torch_utils.py
index e1cd9de8..1f87ec79 100644
--- a/ultralytics/utils/torch_utils.py
+++ b/ultralytics/utils/torch_utils.py
@@ -667,7 +667,7 @@ def profile(input, ops, n=10, device=None, max_num_obj=0):
             m = m.half() if hasattr(m, "half") and isinstance(x, torch.Tensor) and x.dtype is torch.float16 else m
             tf, tb, t = 0, 0, [0, 0, 0]  # dt forward, backward
             try:
-                flops = thop.profile(m, inputs=[x], verbose=False)[0] / 1e9 * 2  # GFLOPs
+                flops = thop.profile(deepcopy(m), inputs=[x], verbose=False)[0] / 1e9 * 2  # GFLOPs
             except Exception:
                 flops = 0