Jupyter notebook Tensorflow GPU Fix

Hi, I'm on the right environment on jupyterlab, my gpu is available, yet when I train a model, it's my cpu doing the work, anything to resolve this issue ?

how to use gpu in jupyter notebook for python 3.8.17 version?

I need to use tensorflow, but with python >= 3.8, but tensorflow-directml doesnt seems to be available with this version, what can I do? Sorry for the inconvenience

How to use with dedictaed NVIDIA GPU? Thanks, in advance

my gpu is still not detected
ROG Strix G533ZW,
RTX 3070 TI ,
Windows 11

of the many tutorials that I have followed, your tutorial is very good... and can run very well in my computer..Thank you very much 🤓😎

it is on false

it says module tenserflow. _API.v2.test has no attribute ’is_gpu_avialable’

my gpu is still not detected

Mine is saying false

My organization was ready to write a check for an Nvidia GTX workstation but after the relentless pains experienced on a smaller box (a 3090) with getting TensorFlow, CUDA, and Python working together we decided to pass. Even when all indicators seemed to say everything was loaded and working, we’d get endless errors and warnings when running the simplest Python neural network. If you don’t have the budget for a dedicated specialist it’s just not worth it. AI on a GPU may get the hype, but it’s nowhere near ready for prime-time for most companies, schools or organizations. Sad, really. Would love to be using it daily

bro when i run my deep learning models , my kernel dies , any solution to resolve the issue

how to install keras after this ?

When i try to import tensorflowo, i get this error:

Could not find 'nvcuda.dll'. TensorFlow requires that this DLL be installed in a directory that is named in your %PATH% environment variable. Typically it is installed in 'C:\Windows\System32'. If it is not present, ensure that you have a CUDA-capable GPU with the correct driver installed.

I have an integerated and dedicate GPU, when i run the test, in Task Manager shows only Integrated GPU working, not Dedicated GPU...Any solutions ?..
Integrated : AMD Radeon R7
Dedicated : AMD Radeon RX 560

when i start training model, is it normal the cuda usage only run about 0-20 %

when i test tensorflow.config.experimental.list_physical_devices()
result is : [PhysicalDevice(name='/physical_device:CPU:0', device_type='CPU'), PhysicalDevice(name='/physical_device:DML:0', device_type='DML'), PhysicalDevice(name='/physical_device:DML:1', device_type='DML')]

I got it working and it says true i run is_gpu_available but when i actually run a basic model in jupyter lab it and check the performance it doesnt use the gpu or the cpu and is really slow.