New TensorFlow(Compatible for GPU) Not Detecting GPU: CUDA 12.6, cuDNN, and Environment Variables Issues

Accelerated Computing CUDA CUDA Setup and Installation
1

I’m having trouble getting TensorFlow to recognize my GPU. Despite following several guides, TensorFlow still reports no GPUs available. Here are the details of my setup and the issue:

System Information:

Operating System: Windows 11 Home

GPU: NVIDIA GeForce RTX 4070 Laptop GPU

NVIDIA Driver Version: 560.81

CUDA Version: 12.6

cuDNN Version: 9.3.0

 !nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2024 NVIDIA Corporation
Built on Fri_Jun_14_16:44:19_Pacific_Daylight_Time_2024
Cuda compilation tools, release 12.6, V12.6.20
Build cuda_12.6.r12.6/compiler.34431801_0



  !nvidia-smi
Wed Aug 14 09:18:01 2024       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 560.81                 Driver Version: 560.81         CUDA Version: 12.6     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                  Driver-Model | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA GeForce RTX 4070 ...  WDDM  |   00000000:01:00.0 Off |                  N/A |
| N/A   51C    P3             13W /   55W |       0MiB /   8188MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+
                                                                                         
+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+

    import tensorflow as tf

2024-08-14 09:18:06.027008: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-08-14 09:18:06.960623: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.

gpus = tf.config.list_physical_devices('GPU')

print("Available GPUs: ", gpus)
Available GPUs:  []

I looking for a solution since i bought this RTX 4070.Hope someone help me

3 Likes
2

Hello, I am having the same issue with my rtx 3060. Nvidia-smi shows the GPU, however tensorflow did not find it: GPU [ }. Did you solve your prloblem?

3

I have the same problem with a RTX4080 Cuda version 12.6. Any suggestions?

4

the same issue, tensorflow v2.18.0, CUDA v12.6, cuDNN v9.5, GPU RTX 3050 Laptop.
Is it because I didn’t use the gpu version of tensorflow?

5

I have the same issue too! I am using windows 11, python version 3.10, I had tried a lot version of CUDA and the CUDNM it still couldnt able to find the GPU too. Is it possible was due too the windows 11?

6

I’m not sure😂please tell me why when you find out the solution. Thanks!