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The aim of the FeedForwardDNNTrain project is to perform basic training of feed forward deep nueral network, based on CUDAMat, which provides a Python matrix class that performs matrix calculations on CUDA-enabled GPUs from Python.

Example:

import numpy as np 
import cudamat as cm 

cm.cublas_init()

# create two random matrices and copy them to the GPU
a = cm.CUDAMatrix(np.random.rand(32, 256))
b = cm.CUDAMatrix(np.random.rand(256, 32))

# perform calculations on the GPU
c = cm.dot(a, b)
d = c.sum(axis = 0)

# copy d back to the host (CPU) and print
print(d.asarray())

You can obtain the latest release from the repository by typing:

git clone https://github.com/ustcwanglin/FeedForwardDNNTrain.git

FeedForwardDNNTrain uses setuptools and can be installed via pip. For details, please see INSTALL.md.

If you want to contribute new features or improvements, you're welcome to fork FeedForwardDNNTrain on github and send us your pull requests! Please see CONTRIBUTE.md if you need any help with that.