NNKit: A Python framework for creating dynamic neural networks.
Project description
NNKit: A Python framework for creating dynamic neural networks
NNKit is a framework for creating and training neural network models, based on dynamic computation graphs. See this post for more info on how the framework works.
Dependencies:
Installation:
You can pip install nnkit, in which case Numpy will also be installed. Otherwise you can download the source and manually install numpy if necessary.
Modules:
The following is a list of modules, nodes and optimizers, along with the framework version in which they were added.
activation:
ReLU (1.0)
LReLU (1.0)
Sigmoid (1.0)
Tanh (1.0)
Softmax (1.0)
arithmetic:
Multiply (1.0)
Add (1.0)
loss:
L1 (1.0)
L2 (1.0)
Cross Entropy (1.0)
Huber (1.4.0)
normalization:
Batch Normalization (1.0)
regularization:
L2 (1.0)
Dropout (1.0)
optimization:
Gradient descent / momentum (1.0)
Adam / RMSProp (1.0)
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