mkserge:

Edit: So I dug into the source code a bit, and it looks like pytorch has a completely separate implementation of cuDNN inside it’s own codebase. Is this true?


No, PyTorch uses the official cudnn release and either links it dynamically or statically.
Note that you are using the runtime container, so nvcc isn’t installed either:
root@f79b17da2a55:/workspace# nvcc --version
bash: nvcc: command not found

Also, the lib path is also empty:
root@f79b17da2a55:/workspace# ls /usr/local/nvidia
ls: cannot access '/usr/local/nvidia': No such file or directory

If you want to build applications inside the container, use the devel container:
root@389363a6c5ec:/workspace# find /usr/ -name libcudnn.so
/usr/lib/x86_64-linux-gnu/libcudnn.so
root@389363a6c5ec:/workspace# nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Wed_Jul_22_19:09:09_PDT_2020
Cuda compilation tools, release 11.0, V11.0.221
Build cuda_11.0_bu.TC445_37.28845127_0