tf.test.is_gpu_available()) возвращает False
print(tf.test.is_gpu_available())
print(tf.test.is_built_with_cuda())
Возвращает
False
True
Tensorflow - 2.7.0 CUDA - 11.2
Что я сделал не так? Помогите
Ответы (1 шт):
Следуйте гайду по установке Tensorflow + GPU
Software requirements
The following NVIDIA® software must be installed on your system:
- NVIDIA® GPU drivers —CUDA® 11.2 requires 450.80.02 or higher.
- CUDA® Toolkit —TensorFlow supports CUDA® 11.2 (TensorFlow >= 2.5.0)
- CUPTI ships with the CUDA® Toolkit.
- cuDNN SDK 8.1.0 cuDNN versions). (Optional) TensorRT 7 to improve latency and throughput for inference on some models.
Windows setup
See the hardware requirements and software requirements listed above. Read the CUDA® install guide for Windows.
Make sure the installed NVIDIA software packages match the versions listed above. In particular, TensorFlow will not load without the cuDNN64_8.dll file. To use a different version, see the Windows build from source guide.
Add the CUDA®, CUPTI, and cuDNN installation directories to the %PATH% environmental variable. For example, if the CUDA® Toolkit is installed to C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.0 and cuDNN to C:\tools\cuda, update your %PATH% to match:
SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.0\bin;%PATH%
SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.0\extras\CUPTI\lib64;%PATH%
SET PATH=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.0\include;%PATH%
SET PATH=C:\tools\cuda\bin;%PATH%