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Description
Hello,
I've just created a bug report at colab but I suspect that the problem might be at the Keras NLP side. Therefore, I'll replicate it here:
Hello!
Current behavior
In google colab, after importing keras-nlp, access to GPU is lost:
!pip install keras-nlp
import tensorflow
print(tensorflow.test.gpu_device_name())
The output of tensorflow.test.gpu_device_name() is an empty string.
At this point in time, it seems impossible to use GPU with Keras NLP.
!nvidia-smi does have output.
Sat Nov 18 02:47:16 2023
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.105.17 Driver Version: 525.105.17 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |
| N/A 50C P8 10W / 70W | 3MiB / 15360MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
Expected behavior
The output of tensorflow.test.gpu_device_name() should be something like /device:GPU:0.
May the force be with you,
JP.