Dead Kernel Demo_part3

[az1fr3]

19:26:41.322 [warn] Cancel all remaining cells due to dead kernel
19:26:41.334 [info] Process Execution: d:\IA\OVoice\New Open Voice.conda\python.exe -c "import ipykernel; print(ipykernel.version); print("5dc3a68c-e34e-4080-9c3e-2a532b2ccb4d"); print(ipykernel.file)"
19:26:41.718 [info] Process Execution: d:\IA\OVoice\New Open Voice.conda\python.exe -m ipykernel_launcher --f=\AppData\Roaming\jupyter\runtime\kernel-v2-8688O2x3hM6AXBGT.json
> cwd: d:\IA\OVoice\New Open Voice\OpenVoice
19:26:47.230 [info] Restarted 6e2daa18-5462-4621-bf05-57652a2a5b2c
19:27:42.489 [error] Disposing session as kernel process died ExitCode: 3221226505, Reason:

[dosubot]

Hey @az1fr3! I'm here to assist you with any bugs, questions, or contributions. Feel free to ask for help while we wait for a human maintainer.

I found a similar closed issue, Kernel died, which might be relevant to your problem. The suggested solutions are:

For Ubuntu:

1. Locate the cuDNN library file:

   find ~ -name "libcudnn_cnn_infer.so.8"

2. Set the LD_LIBRARY_PATH:

   export LD_LIBRARY_PATH=/path/to/cudnn/lib:$LD_LIBRARY_PATH

For Windows:

1. Download and extract the appropriate version of cuDNN from the NVIDIA cuDNN download page.
2. Copy the necessary files to your CUDA installation directory.
3. Set the environment variables to include the CUDA paths.
4. Verify the installation by running:

   nvcc --version

   and a simple PyTorch script to check CUDA and cuDNN availability.

For detailed steps, refer to the issue here ^[1].

To continue talking to Dosu, mention @dosu.

[HengDora]

I encountered a similar problem and was able to resolve it by following the instructions in this comment:

#186 (comment)