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Fix AutoBatch when working with RT-DETR models (#18912)

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Laughing 2025-01-27 18:04:03 +08:00 • committed by GitHub
parent 305a298ae2
commit 30a2de164b
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2 changed files with 2 additions and 2 deletions
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2
ultralytics/models/utils/ops.py
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@ -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)

2
ultralytics/utils/torch_utils.py
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@ -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