I am running Tacotron2 on Windows with Conda environment with an RTX 3090.
I can get to run but in Windows, it seems like it uses twice as much VRAM as compared to my Linux counter parts.
I’ve tried using python 3.6 and 3.7. installing pytorch through pip and conda. using cudatoolkit.
CudaToolkits pre-v11 tell me its not sm_86 compatible and freeze.
I didn’t always have this issue but I’ve gone back to my conda env backups, and those don’t help.
Is there any scripts that can tell me which cuda version that its using? I removed all the cuda paths but somehow my conda env still knew where to find it and run.
My colab graphics card is 16GB and can do a batch of 48. While my windows graphics card is 24GB and can only do 32 batch size.
Colab Link:
  
      
      colab.research.google.com
  
  
    

Google Colaboratory