CODEWITHSUNDEEP
pythontensorflow
EricP
EricP

Reputation: 5

Tensorflow can not found RTX 3070

I have encountered a problem when I tried to install tensorflow-gpu in my anaconda environment.

When I tested the availability of GPU after import of tensorflow, it seems that a .dll library (cusolver64_10.dll, provided normally with CUDA package) is missing and the test failed.

From Google, I saw that a solution is to copy the file from previous version of CUDA. Is it the right thing to do?

CUDA and CUDA DNN were installed following Nvidia documentation and tests were OK (regarding samples from CUDA folders).

My system info:

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).

I tried with pip install tensorflow-gpu but doesnt't work.

What I obtained :

(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

Upvotes: 0

Views: 3568

Answers (2)

Albert Myšák
Albert Myšák

Reputation: 194

rename cusolver64_10.dll to cusolver64_11.dll

Upvotes: 1

user11530462
user11530462

Reputation:

From comments

Installed Cuda11.0 and cuDNN 8.0.4. Tensorflow was installed as follow : pip install tf-nightly-gpu numpy==1.19.3. GPU is now available (paraphrased from EricP)

Upvotes: 0

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