GPU environmental issues.

After using the new version, after CUDA10.0 and CUDA10.1 are installed at the same time, now, suddenly CUDA10.0 can't be used, no, it should be said that its corresponding tf-GPU can't be used. …

System: win10
tf version: 2.0.0

tf.config.experimental.list_physical_devices('GPU') returns as follows:
[Why is there only one graphics card??? My computer has a discrete graphics card, and the environment is all set up,...]

[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]

This tf version supports GPU:

print(tf.__version__)
print(tf.test.is_gpu_available())
print(tf.test.is_built_with_cuda())#是否支持NVIdia GPU

But it returns as follows:

2.0.0
True
True

tf.test.is_gpu_available() shows True but tf.config.experimental.list_physical_devices('GPU') does not have NVIDIA graphics card. . .

And the nvidia-smi command line is displayed as follows:

please comment from someone who comes over, thank you God.

[Already resolved]