nnkit 1.3

NNKit: A dynamic neural network framework.

# NNKit: A dynamic neural network framework.

NNKit is a framework for training neural network models.

It is based on the concept of dynamic computation graphs, where graphs are implicitly generated on each forward pass as nodes are passed into other nodes as inputs

This dynamic approach makes it practical to implement recurrent topologies for varying length inputs and allows generating graphs with a minimal amount of code.

#### Modules The following is a list of net nodes and optimizers in the framework, 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)

## normalization: * Batch Normalization (1.0)

## regularization: * L2 (1.0) * Dropout (1.0)

## training: * Gradient descent w/ momentum (1.0) * Adam / RMSProp (1.0)