No GPU detected in VSCode for tensorflow – Ubuntu

I have installed tensorflow and the required dependencies for GPU support for Ubuntu 22.04 as mentioned in https://www.tensorflow.org/install/pip.

I tested that the GPU was detected as mentioned in the above tutorial and it detected my Nvidia GTX 1060. But if I try to run tensorflow on GPU in VSCode, the GPU is not detected.

I have a python script test-tf.py with the following code:

import tensorflow as tf
print(tf.config.list_physical_devices('GPU'))

When I run this, I get the following:

[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]

When I run the same code in a .ipynb file in VSCode, I get:

[]
2022-12-27 18:59:38.079947: I tensorflow/compiler/xla/stream_executor/cuda/cuda_gpu_executor.cc:981] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2022-12-27 18:59:38.080624: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2022-12-27 18:59:38.080767: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcublas.so.11'; dlerror: libcublas.so.11: cannot open shared object file: No such file or directory
2022-12-27 18:59:38.080843: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcublasLt.so.11'; dlerror: libcublasLt.so.11: cannot open shared object file: No such file or directory
2022-12-27 18:59:38.080894: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcufft.so.10'; dlerror: libcufft.so.10: cannot open shared object file: No such file or directory
2022-12-27 18:59:38.080940: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcurand.so.10'; dlerror: libcurand.so.10: cannot open shared object file: No such file or directory
2022-12-27 18:59:38.080986: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcusolver.so.11'; dlerror: libcusolver.so.11: cannot open shared object file: No such file or directory
2022-12-27 18:59:38.081032: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcusparse.so.11'; dlerror: libcusparse.so.11: cannot open shared object file: No such file or directory
2022-12-27 18:59:38.081076: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudnn.so.8'; dlerror: libcudnn.so.8: cannot open shared object file: No such file or directory
2022-12-27 18:59:38.081087: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1934] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...

If I run the same .ipynb file using Jupyter Notebook, the GPU is detected as expected. It is not detected only when using the notebook from VSCode. I have made sure to use the proper conda environment.