loss function like has a bug

[rrjia]

🐛 Bug

A clear and concise description of what the bug is.

utils/loss.py line108

gain[2:6] = torch.tensor(p[i].shape)[[3, 2, 3, 2]]  # xyxy gain

for yolov5s.yaml
if i=1
p[i].shape = 3,80,80,85
gain[2:6] = [85, 80, 85, 80]

gain[2:6] = torch.tensor(p[i].shape)[[2, 1, 2, 1]]  # xyxy gain

it shoud be [80, 80, 80, 80]

[github-actions]

👋 Hello @rrjia, thank you for your interest in 🚀 YOLOv5! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.

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Requirements

Python 3.8 or later with all requirements.txt dependencies installed, including torch>=1.7. To install run:

$ pip install -r requirements.txt

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[rrjia]

[glenn-jocher]

@rrjia hi thanks for the bug report and the screenshot! We have updated the loss function recently, creating a new ComputeLoss() class to replace it. Can you verify that you see the same bug in the most recent code please?

You can update your code with git pull, or alternatively you can git clone https://github.com/ultralytics/yolov5 again.

[glenn-jocher]

@rrjia if I try to reproduce by training with default settings and placing a breakpoint here, everything looks correct:

[rrjia]

sorry it's my fault, the model get A list of length 3, i use y[0] input compute_loss function, thank you.