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--- compute:pythongpu [2024/12/11 15:31] – bjorns
+++ compute:pythongpu [2024/12/11 15:48] (current) – bjorns
@@ Line 10: / Line 10: @@
 ''pip install torch''\\
 \\
-The new Python virtual environment has been created and activated, torch package installed\\
+The new Python virtual environment has been created and activated, **torch** package installed\\
-And the correct CUDA library is also installed\\
+And the correct **CUDA library** is also installed\\
 Please run a simple test with python code to make sure you can communicate with the GPU\\
 One example command to test torch\\
 ''if torch.cuda.is_available() print("GPU")''
 \\
-But you must run this code test with sbatch\\
+But you must run this code test with **sbatch**, send your job to the cluster\\
-Create a python file dummy.py with these command\\
+Create a python file dummy.py with the test-GPU command\\
-Update the sbatch script file, mine is called **oneJob.sh**
+\\
+Update the sbatch script file, mine is called **oneJob.sh**\\
 Remove lines below last #SBatch\\
 Add 2 lines\\
 ''source myTorch/bin/activate''\\
 ''python3 dummy.py''\\
-[SAVE]
+[SAVE]\\
-Then run the command sbatch oneJob.sh\\
+Run the command ''sbatch oneJob.sh''\\
-The repsonse should be **Submitted batch job XXX**\\
+The response should be **Submitted batch job XXX**\\
 Then check your log file (default name is myJob.log) for the result\\
 \\
+Installing Tensorflow is same process, we recommend using a different virtual environment if you want to try both of them\\
+Make sure to instruct pip in this way, to get all necessary packages ''pip install "tensorflow[and-cuda]"''\\
 \\
 == Those version have also been used before and known to work ==