self.balance = {3: [4.0, 1.0, 0.4], 4: [4.0, 1.0, 0.25, 0.06], 5: [4.0, 1.0, 0.25, 0.06, .02]}[det.nl]

[Radleye]

🐛 Bug

I train yolov5s.yaml with voc2007andvoc2012dataset is ok, but when i edit the yolov5s.yaml,and train, the erro was occured.
I changed yolov5s.yaml same as he does.#1237 (comment)


the erro is :
Traceback (most recent call last):
File "train.py", line 526, in
train(hyp, opt, device, tb_writer, wandb)
File "train.py", line 233, in train
compute_loss = ComputeLoss(model) # init loss class
File "/yolov5/utils/loss.py", line 108, in init
self.balance = {3: [4.0, 1.0, 0.4], 4: [4.0, 1.0, 0.25, 0.06], 5: [4.0, 1.0, 0.25, 0.06, .02]}[det.nl]
KeyError: 2

To Reproduce (REQUIRED)

Input:

import torch

a = torch.tensor([5])
c = a / 0

Output:

Traceback (most recent call last):
  File "/Users/glennjocher/opt/anaconda3/envs/env1/lib/python3.7/site-packages/IPython/core/interactiveshell.py", line 3331, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-5-be04c762b799>", line 5, in <module>
    c = a / 0
RuntimeError: ZeroDivisionError

Expected behavior

A clear and concise description of what you expected to happen.

Environment

If applicable, add screenshots to help explain your problem.

• OS: [e.g. Ubuntu]
• GPU [e.g. 2080 Ti]

Additional context

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[github-actions]

👋 Hello @xiaowo1996, 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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[glenn-jocher]

@xiaowo1996 thanks for the bug report! Yes your modifications are correct. It seems the balancing code we have in loss.py is not robust to 2 layer outputs. I will submit a PR with a fix.

[glenn-jocher]

@xiaowo1996 this problem should be resolved now in PR #2256. Please git pull to receive this update and try again!

[Radleye]

@glenn-jocher thank you sir , when i git pull updata the project,this erro was disappear.but the new issue was appeared during the trainning time.the new issue is:
RuntimeError: Sizes of tensors must match except in dimension 3. Got 41 and 42 (The offending index is 0)

my enviromet is dokcerimages you offer,and i train orgin yolov5s.yaml successful,the train data is voc2012,but edited yam file didn't work

[Radleye]

@glenn-jocher I try again in the googlecolab,and the dataset is you provided from the command bash data/scripts/get_voc.sh you provided, my train command is :
python train.py --data data/voc.yaml --cfg models/yolov5s.yaml --weights weights/yolov5s.pt --batch-size 16 --epochs 500.
the yolov5s.yaml i have been edited same as above,but the same issue was appear

[glenn-jocher]

@xiaowo1996 you don't need to download VOC manually, it will download automatically on first use. I will try with a P3-P4 model.

[glenn-jocher]

@xiaowo1996 you can use the colab notebook to get started easily. You 1) run the setup cell, and then 2) run the VOC training cell (in the Appendix). The VOC training cell contents are:

# VOC
for b, m in zip([64, 48, 32, 16], ['yolov5s', 'yolov5m', 'yolov5l', 'yolov5x']):  # zip(batch_size, model)
  !python train.py --batch {b} --weights {m}.pt --data voc.yaml --epochs 50 --cache --img 512 --nosave --hyp hyp.finetune.yaml --project VOC --name {m}

[glenn-jocher]

@xiaowo1996 everything works perfectly well training a P3-P4 model on VOC, I encountered no problems:

[Radleye]

@glenn-jocher Thankyou, sir. In fact,This error occurred during the test time clearly，can you wait a time and see what happen?I try again same as you do.and same issue appeared:

[glenn-jocher]

Ah, test time. Yes I will try that, hold on.

[glenn-jocher]

@xiaowo1996 yes, I get the same result as you now!
RuntimeError: Sizes of tensors must match except in dimension 3. Got 33 and 34 (The offending index is 0)

I think this is caused by a too small stride to support the feature map size reduction the models need. 32 may be the minimum image stride supported.