What's wrong with this? Do I need to do anything else? It will affect my result?

[lixiangMindSpore]

Describe the bug A clear and concise description of what the bug is.

Environment

• Your operating system and version: Ubuntu18.04
• Your python version:3.8.12
• Your PyTorch version:11.1
• How did you install python (e.g. apt or pyenv)? Did you use a virtualenv?:conda create -n torch python=3.8
• Have you tried using latest bagua master (python3 -m pip install --pre bagua)?:0.8.1.post1

Reproducing

Please provide a minimal working example. This means the runnable code.

Please also write what exact commands are required to reproduce your results.

Additional context Add any other context about the problem here.

[NOBLES5E]

The message means the memory layout of your PyTorch tensor is inconsistent with latest PyTorch, so Bagua will fallback to a less efficient way to get a tensor's memory address. It will not affect your result. You can safely ignore it if your training runs fine.

[lixiangMindSpore]

The message means the memory layout of your PyTorch tensor is inconsistent with latest PyTorch, so Bagua will fallback to a less efficient way to get a tensor's memory address. It will not affect your result. You can safely ignore it if your training runs fine.

It will affect my velocity?

[NOBLES5E]

Only about 0.5%-2% difference in training speed in our tests. We actually plan to remove this warning in next release.

[lixiangMindSpore]

Only about 0.5%-2% difference in training speed in our tests. We actually plan to remove this warning in next release.

Now I intend to remove this warning. How can I do?

[NOBLES5E]

Try to launch your program with environment variable LOG_LEVEL=error

Like this

export LOG_LEVEL=error
python -m bagua.distributed.launch ....