[英]CUDA Tensorflow Version ,nvidia-smi version issue. Failed to get convolution algorithm. This is probably because cuDNN failed to initialize,
Tried, preds = model.predict(k[np.newaxis,...])试过了, preds = model.predict(k[np.newaxis,...])
UnknownError: Failed to get convolution algorithm.
UnknownError:获取卷积算法失败。 This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
这可能是因为 cuDNN 初始化失败,因此请尝试查看上面是否打印了警告日志消息。 [[node model/stem_conv/Conv2D (defined at:3) ]] [Op:__inference_distributed_function_18348]
[[节点模型/stem_conv/Conv2D(定义于:3)]] [Op:__inference_distributed_function_18348]
Hardware: Make: OMEN, OS_ Windows 10, GPU NVIDIA GEFORCE RTX 2060, My System configuration硬件: 制造商: OMEN,OS_ Windows 10,GPU NVIDIA GEFORCE RTX 2060,我的系统配置
!nvcc --version !nvcc --版本
> nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2019 NVIDIA
> Corporation Built on Sun_Jul_28_19:12:52_Pacific_Daylight_Time_2019
> Cuda compilation tools, release 10.1, V10.1.243
!nvidia-smi !nvidia-smi
Mon Jul 20 23:15:20 2020 2020 年 7 月 20 日星期一 23:15:20
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 451.77 Driver Version: 451.77 CUDA Version: 11.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce RTX 2060 WDDM | 00000000:01:00.0 Off | N/A |
| N/A 38C P8 5W / N/A | 5304MiB / 6144MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 18900 C ...nvs\tensorflow\python.exe N/A |
+-----------------------------------------------------------------------------+
Seems like some thing is missing.好像少了点什么。 CUDA version is not in Sync is what I guess.
CUDA 版本不同步是我猜的。 Please correct me.
请纠正我。 If its NVIDIA STUDIO DRIVER not appropriate, Could some one please help me the one appropriate for Tensorflow 2.1.0
如果它的 NVIDIA STUDIO 驱动程序不合适,请有人帮我一个适合 Tensorflow 2.1.0 的驱动程序
Tensor Flow Version: 2.1.0, Keras Version: 2.2.4-tf, Python 3.7.7 (default, May 6 2020, 11:45:54) [MSC v.1916 64 bit (AMD64)],Pandas 1.0.5,Scikit-Learn 0.23.1 Tensor Flow Version: 2.1.0, Keras Version: 2.2.4-tf, Python 3.7.7 (default, May 6 2020, 11:45:54) [MSC v.1916 64 bit (AMD64)],Pandas 1.0.5 ,Scikit-Learn 0.23.1
I had similar issue.我有类似的问题。 It got fixed after I downgraded CUDA from 11 to 10.1 version ( NVIDIA Link ).
在我将 CUDA 从 11 版本降级到 10.1 版本( NVIDIA Link )后,它得到了修复。
As per TF documentation:根据 TF 文档:
CUDA® Toolkit —TensorFlow supports CUDA 10.1 (TensorFlow >= 2.1.0)
CUDA® Toolkit —TensorFlow 支持 CUDA 10.1 (TensorFlow >= 2.1.0)
EDIT (more info below):编辑(更多信息如下):
You can find the compatible driver at: https://www.nvidia.com/en-us/drivers/results/149127/您可以在以下位置找到兼容的驱动程序: https://www.nvidia.com/en-us/drivers/results/149127/
I use Python 3.7
along with the tensorflow-gpu
installed in a conda
environment.我使用
Python 3.7
以及安装在conda
环境中的tensorflow-gpu
。
NOTE: If you installed TF with pip install tensorflow
, it may not have the required python packages for cuda downloaded.注意:如果您使用
pip install tensorflow
,它可能没有下载 Z39466FE22B062A3868CFE0 所需的 python 包。 I would recommend you uninstall/re-install with:我建议您卸载/重新安装:
pip install tensorflow-gpu
Here's my output for a quick test:这是我的 output 用于快速测试:
import tensorflow as tf
print(tf.__version__)
print(tf.config.experimental.list_physical_devices('GPU'))
2.1.0
[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]
For your reference:供你参考:
nvidia-smi
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 431.70 Driver Version: 431.70 CUDA Version: 10.1 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce RTX 206... WDDM | 00000000:01:00.0 On | N/A |
| 32% 44C P8 21W / 175W | 510MiB / 8192MiB | 3% Default |
+-------------------------------+----------------------+----------------------+
nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Fri_Feb__8_19:08:26_Pacific_Standard_Time_2019
Cuda compilation tools, release 10.1, V10.1.105
From cudnn.h
(Path: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include
)来自
cudnn.h
(路径: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include
)
Please note that you need to manually move the files to this location.请注意,您需要手动将文件移动到此位置。 Please refer to the installation instructions:
请参考安装说明:
Download: https://developer.nvidia.com/compute/machine-learning/cudnn/secure/7.6.5.32/Production/10.1_20191031/cudnn-10.1-windows10-x64-v7.6.5.32.zip下载: https://developer.nvidia.com/compute/machine-learning/cudnn/secure/7.6.5.32/Production/10.1_20191031/cudnn-10.1-windows10-x64-v7.6.5.32.ZCDCD2229A8D84017
Instructions: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#install-windows说明: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#install-windows
#define CUDNN_MAJOR 7
#define CUDNN_MINOR 6
#define CUDNN_PATCHLEVEL 5
Hope this helps!希望这可以帮助!
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