Hii everyone…
I am training a final laye ron the ConvNeXt_tiny model using the CIFAR-10 and Fashion-MNIST dataset. My code was working perfectly 2 days ago on kaggle on a P100 GPU. But today it started to show this error. I tried looking for it on various places but it was most probably due to some version mismatch. After that I ran the same code on the 2 T4 GPu provided by the Kaggle and it is going perfectly fine. What could be the issue and how to fix it?
this is the error that I am getting
AcceleratorError: CUDA error: no kernel image is available for execution on the device Search for cudaErrorNoKernelImageForDevice' in https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__TYPES.html for more information. CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1 Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.