ddgrcf / yolov5_learning

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𝑯𝒊, 𝑰'𝒎 ✨ 𝑫𝑫𝑮𝑹𝑪𝑭 ✨, 𝒂 𝒑𝒂𝒔𝒔𝒊𝒐𝒏𝒂𝒕𝒆 𝒄𝒐𝒎𝒑𝒖𝒕𝒆𝒓 𝒗𝒊𝒔𝒊𝒐𝒏 𝒅𝒆𝒗𝒆𝒍𝒐𝒑𝒆𝒓 𝒇𝒓𝒐𝒎 𝑪𝒉𝒊𝒏𝒂. 𝑪𝒖𝒓𝒓𝒆𝒏𝒕𝒍𝒚 𝒔𝒕𝒖𝒅𝒚𝒊𝒏𝒈 𝒇𝒐𝒓 𝒂 𝒈𝒓𝒂𝒅𝒖𝒂𝒕𝒆 𝒔𝒕𝒖𝒅𝒆𝒏𝒕 𝒊𝒏 𝑵𝒐𝒓𝒕𝒉𝒘𝒆𝒔𝒕𝒆𝒓𝒏 𝑷𝒐𝒍𝒚𝒕𝒆𝒄𝒉𝒏𝒊𝒄𝒂𝒍 𝑼𝒏𝒊𝒗𝒆𝒓𝒔𝒊𝒕𝒚 🏫, 𝒕𝒉𝒆 𝒎𝒂𝒊𝒏 𝒓𝒆𝒔𝒆𝒂𝒓𝒄𝒉 𝒅𝒊𝒓𝒆𝒄𝒕𝒊𝒐𝒏𝒔 𝒂𝒓𝒆 𝒐𝒃𝒋𝒆𝒄𝒕 𝒅𝒆𝒕𝒆𝒄𝒕𝒊𝒐𝒏 (𝒓𝒆𝒎𝒐𝒕𝒆 𝒔𝒆𝒏𝒔𝒊𝒏𝒈), 𝒊𝒏𝒔𝒕𝒂𝒏𝒄𝒆 𝒔𝒆𝒈𝒎𝒆𝒏𝒕𝒂𝒕𝒊𝒐𝒏, 𝒂𝒏𝒅 𝒐𝒃𝒋𝒆𝒄𝒕 𝒕𝒓𝒂𝒄𝒌𝒊𝒏𝒈. 𝑰 𝒘𝒊𝒍𝒍 𝒔𝒕𝒖𝒅𝒚 𝒔𝒐𝒎𝒆 𝒔𝒐𝒇𝒕𝒘𝒂𝒓𝒆 𝒅𝒆𝒗𝒆𝒍𝒐𝒑𝒎𝒆𝒏𝒕 𝒂𝒏𝒅 𝒘𝒆𝒃 𝒅𝒆𝒗𝒆𝒍𝒐𝒑𝒎𝒆𝒏𝒕 𝒓𝒆𝒍𝒂𝒕𝒆𝒅 𝒌𝒏𝒐𝒘𝒍𝒆𝒅𝒈𝒆 𝒊𝒏 𝒎𝒚 𝒔𝒑𝒂𝒓𝒆 𝒕𝒊𝒎𝒆. 𝑹𝒆𝒈𝒂𝒓𝒅𝒊𝒏𝒈 𝒕𝒉𝒆 𝒓𝒆𝒍𝒂𝒕𝒆𝒅 𝒊𝒔𝒔𝒖𝒆𝒔 𝒊𝒏 𝒕𝒉𝒆 𝒇𝒊𝒆𝒍𝒅 𝒐𝒇 𝒅𝒆𝒗𝒆𝒍𝒐𝒑𝒎𝒆𝒏𝒕 𝒂𝒏𝒅 𝒓𝒆𝒔𝒆𝒂𝒓𝒄𝒉, 𝒘𝒆𝒍𝒄𝒐𝒎𝒆 𝒕𝒐 𝒅𝒊𝒔𝒄𝒖𝒔𝒔 𝒘𝒊𝒕𝒉 𝒎𝒆 😊🫶❤️

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yolov5_learning's Issues

剪枝前后速度问题

❔Question

大佬你好，我发现剪枝前后速度竟然没有一边变化，同一张图片剪枝前后速度竟然都是20ms，而且我加载了之前直接用yolov5训练的模型发现只要10ms，大佬你之前测试速度是咋样的呢？

Additional context

由于我对于short_cut采取了并行操作，剪枝完速度可能不会有提升。而这个项目比较杂，我又重新开了一个项目yolov5_pruning，其中我跳过了short_cut层，并不采用并行操作

Before submitting a bug report, please be aware that your issue must be reproducible with all of the following, otherwise it is non-actionable, and we can not help you:

• Current repo: run git fetch && git status -uno to check and git pull to update repo
• Common dataset: coco.yaml or coco128.yaml
• Common environment: Colab, Google Cloud, or Docker image. See https://github.com/ultralytics/yolov5#environments

If this is a custom dataset/training question you must include your train*.jpg, val*.jpg and results.png figures, or we can not help you. You can generate these with utils.plot_results().

🐛 Bug

A clear and concise description of what the bug is.

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

Add any other context about the problem here.