Tensorflow找不到RTX 3070

Question

当我尝试在我的anaconda环境中安装tensorflow-gpu时遇到了一个问题。

当我在导入tensorflow之后测试图形处理器的可用性时，似乎缺少.dll库(cusolver64_10.dll，通常随CUDA包提供)，测试失败。

从Google那里，我看到一个解决方案是从以前版本的CUDA中复制文件。这是正确的做法吗？

CUDA和CUDA DNN是按照Nvidia文档和测试正常安装的(关于CUDA文件夹中的示例)。

我的系统信息：

OS : Windows 10
Visual Studio Community 2019
Cuda toolkit : Cuda compilation tools, release 11.1, V11.1.105 (from nvcc --version)
GPU : Geforce RTX 3070, driver version : 460.79, CUDA 11.2 (from nvidia-smi)
Cuda DNN : version 8.05.39
CPU : Ryzen 9 3900 XT
Framework: Anaconda (conda 4.9.2), virtual environment created with python 3.8, installation of tensorflow from pip tf-nightly-gpu (tf-nightly-gpu==2.5.0.dev20201213).

我试着用pip install tensorflow-gpu，但不起作用。

我得到的是：

(deeplearning) C:\Users\Utilisateur>python
Python 3.8.0 (default, Nov  6 2019, 16:00:02) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
2020-12-14 10:13:14.134389: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
>>> print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))
2020-12-14 10:13:20.542276: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll
2020-12-14 10:13:20.573713: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1727] Found device 0 with properties:
pciBusID: 0000:2b:00.0 name: GeForce RTX 3070 computeCapability: 8.6
coreClock: 1.815GHz coreCount: 46 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s
2020-12-14 10:13:20.573798: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll
2020-12-14 10:13:20.580384: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll
2020-12-14 10:13:20.580485: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll
2020-12-14 10:13:20.584557: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll
2020-12-14 10:13:20.585655: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll
2020-12-14 10:13:20.586334: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'cusolver64_10.dll'; dlerror: cusolver64_10.dll not found
2020-12-14 10:13:20.589176: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll
2020-12-14 10:13:20.589742: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll
2020-12-14 10:13:20.589814: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1764] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
Num GPUs Available:  0

Answer 1

将cusolver64_10.dll重命名为cusolver64_11.dll

Answer 2

来自评论

安装了Cuda11.0和cuDNN 8.0.4。Tensorflow的安装方式如下：pip install tf-nightly-gpu numpy==1.19.3。图形处理器现已面市(转译自EricP)