Non-OK-status: status: Internal: initialization error - tensorflow

Question

environment：tensorflow 2.3.0 Anaconda with CUDA Toolkit 10.1 CUDNN 7.6.0 (Windows 10)
I run my code with multiprocessing it return a issue
Non-OK-status: GpuLaunchKernel(FillPhiloxRandomKernelLaunch<Distribution>, num_blocks, block_size, 0, d.stream(), gen, data, size, dist) status: Internal: initialization error
but the problem goes away when I run the code using "else" methods:
This is the related code：
if runInProcess:
p = multiprocessing.Process(target=Train, args=(yml, train_subs, loadData, channDic, eventTypeDic, getData, folderIndex, modelPath))
p.start()
p.join()
else:
Train(yml, train_subs, loadData, channDic, eventTypeDic, getData, folderIndex, modelPath)
My GPU : RTX2080Ti 12G
I already run the nvcc -V and it returns :
meya#admin:~$ nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Fri_Feb__8_19:08:17_PST_2019
Cuda compilation tools, release 10.1, V10.1.105
This is the full result :
coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s
2022-05-30 09:54:42.815682: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
2022-05-30 09:54:42.815732: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcublas.so.10
2022-05-30 09:54:42.815769: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcufft.so.10
2022-05-30 09:54:42.815804: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcurand.so.10
2022-05-30 09:54:42.815838: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusolver.so.10
2022-05-30 09:54:42.815872: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusparse.so.10
2022-05-30 09:54:42.815907: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudnn.so.7
2022-05-30 09:54:42.818666: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1858] Adding visible gpu devices: 0
2022-05-30 09:54:42.818744: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
2022-05-30 09:54:43.491362: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1257] Device interconnect StreamExecutor with strength 1 edge matrix:
2022-05-30 09:54:43.491412: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1263] 0
2022-05-30 09:54:43.491419: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1276] 0: N
2022-05-30 09:54:43.492693: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1402] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9374 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:af:00.0, compute capability: 7.5)
../model/1S_FB1-100_S100_chanSeq.yml
Will Return
folder Index: 1
--------------------- Fetching 1/1 Data from suject 1 ---------------------
Extracting EDF parameters from
/data0/meya/MI/RaiseLower/Action/session_miltiprocess/s01/evt.bdf...
BDF file detected
Setting channel info structure...
Creating raw.info structure...
/data0/meya/code/code_test/MI/interSub/../../MI/loadData.py:204: RuntimeWarning: Omitted
136 annotation(s) that were outside data range.
annotationData = mne.io.read_raw_bdf(eventFile)
mne version > 0.20
Filtering raw data in 1 contiguous segment
Setting up band-pass filter from 4 - 1e+02 Hz
FIR filter parameters
---------------------
Designing a one-pass, zero-phase, non-causal bandpass filter:
- Windowed time-domain design (firwin) method
- Hamming window with 0.0194 passband ripple and 53 dB stopband attenuation
- Lower passband edge: 4.00
- Lower transition bandwidth: 2.00 Hz (-6 dB cutoff frequency: 3.00 Hz)
- Upper passband edge: 100.00 Hz
- Upper transition bandwidth: 25.00 Hz (-6 dB cutoff frequency: 112.50 Hz)
- Filter length: 1651 samples (1.651 sec)
----------------------Build Model----------------------
Model Type: EEGNet
2022-05-30 09:55:53.385452: F ./tensorflow/core/kernels/random_op_gpu.h:232] Non-OK-status: GpuLaunchKernel(FillPhiloxRandomKernelLaunch<Distribution>, num_blocks, block_size, 0, d.stream(), gen, data, size, dist) status: Internal: initialization error
What are the issues and how to fix it?