A series of warnings often appear while using DeePMD-kit

[JTaozhang]

Summary

it is a question about DeepMD shows some warnings when I use it. The sofware doesn't report any errors. I want to know the reasons, how to solve those warnings and whether we can ignore them.

DeePMD-kit Version

deePMD-kit v2.1.5

TensorFlow Version

tensorflow 2.9.0

Python Version, CUDA Version, GCC Version, LAMMPS Version, etc

I use the python version of deepMD and run it on linux system with multiple calculation nodes.

Details

when I use the deePMD softeware, it always shows some warnings。
warning 1: "WARNING:tensorflow:From /public/home/ZT/.conda/envs/deepmd/lib/python3.10/site-packages/tensorflow/python/compat/v2_compat.py:107: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.
This warning would apppear, although I used the somple command "dp --version", and no matter only CPU version or GPU version.

warning 2:WARNING:root:To get the best performance, it is recommended to adjust the number of threads by setting the environment variables OMP_NUM_THREADS, TF_INTRA_OP_PARALLELISM_THREADS, and TF_INTER_OP_PARALLELISM_THREADS..

warning 3: WARNING:root:Environment variable KMP_BLOCKTIME is empty. Use the default value 0; WARNING:root:Environment variable KMP_AFFINITY is empty. Use the default value granularity=fine,verbose,compact,1,0

warning 4: /public/home/ZT/.conda/envs/deepmd/lib/python3.10/importlib/init.py:169: UserWarning: The NumPy module was reloaded (imported a second time). This can in some cases result in small but subtle issues and is discouraged.

As for the warning 1 and 4, I want to ask the developers the reason why those warning appears, and how to solve them? Those warnings whether have innegligible influence on the calculation accuracy, or we can neglect them?

As for the warning 2 and 3, it seems these paramters use default value and they only have influence on the speed of calculation. How to set them, using export="these parameters"?

[njzjz]

I check all the warnings.

Warning 1 is thrown by TensorFlow. There is nothing we can do.

For warning 2, a link to documentation has been added in #2362.

Warning 3 is straightforward.

Warning 4 is thrown by the Python imp module.

So there is nothing to do with us in this issue.

[njzjz]

Reopen. It seems the TensorFlow warnings can be filtered.