Sparse Sampling Neural Networks (Masters Thesis)

Created by Ryan Goy, Arda Sahiner, and Avideh Zakhor from UC Berkeley

See the paper here

Dependencies

• python3
• Tensorflow 1.3+
• Pillow
• Pandas
• scipy
• numpy
• pyntcloud
• matplotlib
• psutil

Run instructions

cd src/cpp
bash compile_probe.sh
cd ../python
python main.py

Bugs and how to resolve them

Fatal error: nsync_cv.h: No such file or directory

sudo find / -name nsync_cv.h

Then, edit the mutix.h file reference in the error and change the nsync_cv.h and nsync_mu.h to any of the paths listed from the find command.

ValueError: invalid literal for float(): ...

This seems to occur randomly when reading in the dataset. Navigate to the problem file and search for the invalid character and delete it.

undefined symbol: _ZN10tensorflow8internal21CheckOpMessageBuilder9NewStringB5cxx11Ev

Add (or delete) the flag -D_GLIBCXX_USE_CXX11_ABI=0

libcudart.so.9.1: cannot open shared object file: No such file or directory

Run the following lines:

export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64"
export CUDA_HOME="/usr/local/cuda"

This will have to be run per terminal instance. To add it permanently, add it to the ~/.bashrc file.

InvalidArgumentError (see above for traceback): No OpKernel was registered to support Op 'Probe' with these attrs. Registered devices: [CPU]

This might mean that NVML is not initialized properly. Run nvidia-smi to confirm. Rebooting often solves this issue.

Memory error or Bus error at the start of training.

Usually these errors are associated with memmapping. After the first run, the probing data is saved to a memmap to avoid redudant calculation. If parameters change between runs, then ensure the flag --load_probe_output is set to False.