PyCompiledNN

This repository contains Python bindings for CompiledNN (written by B-Human).

Installation

This package requires the following dependencies:

• Python 3 (with NumPy) (Ubuntu/Debian: python3, python3-numpy)
• Boost Python (with NumPy) (Ubuntu/Debian: libboost-python-dev, libboost-numpy-dev)
• HDF5 (Ubuntu/Debian: libhdf5-dev)
• Protocol Buffers (both compiler and library) (Ubuntu/Debian: protobuf-compiler, libprotobuf-dev)

PyCompiledNN can be installed via pip install git+https://github.com/h3ndrk/PyCompiledNN.git.

Development

1. Make sure all submodules are cloned: git submodule update --init
2. Configure project: cmake -Bbuild .
3. Build project: cmake --build build
4. Observe the file PyCompiledNN.so in the build directory

For testing, you should be able to import the module in Python without errors:

1. Change into build directory: cd build
2. Run an interactive Python REPL: python
3. Import the module: import PyCompiledNN

Example

The API is very similar to the C++ version:

import PyCompiledNN

model = PyCompiledNN.Model()
model.load('model.hdf5')
# Optionally, indicate which input tensors should be converted from unsigned chars to floats in the beginning.
# model.setInputUInt8(0);
nn = PyCompiledNN.CompiledNN()
nn.compile(model)
# ... fill nn.input(i) with data
nn.apply()
# ... obtain the results from nn.output(i)

The input() and output() methods return NumPy ndarrays:

input_array = numpy.zeros((32, 32, 1))
numpy.copyto(nn.input(0), input_array, casting='no')
nn.apply()
print(nn.output(0))