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An implementation of KFAC for TensorFlow
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README.md

K-FAC: Kronecker-Factored Approximate Curvature

Travis

K-FAC in TensorFlow is an implementation of K-FAC, an approximate second-order optimization method, in TensorFlow. When applied to feedforward and convolutional neural networks, K-FAC can converge >3.5x faster in >14x fewer iterations than SGD with Momentum.

Installation

kfac is compatible with Python 2 and 3 and can be installed directly via pip,

# Assumes tensorflow or tensorflow-gpu installed
$ pip install kfac

# Installs with tensorflow-gpu requirement
$ pip install 'kfac[tensorflow_gpu]'

# Installs with tensorflow (cpu) requirement
$ pip install 'kfac[tensorflow]'

KFAC DOCS

Please check KFAC docs for detailed description with examples of how to use KFAC.

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