NeuralEngine is a small Deep learning framework I built for fast Neural Network creation and evaluation. This framework is built around numpy in order to aid fast CPU compute
The design of this framework allows easy notations, allowing the user to create, train an evaluate models with ease.
from neuralengine import Layer
import neuralengine
import numpy
model = neuralengine.Network([
Layer.Input(40),
Layer.Dense(42,activation=neuralengine.sigmoid),
Layer.Dense(100),
Layer.Dense(20),
Layer.Dense(2)])
model[numpy.random.randn(40)] = numpy.ones(2)
# equivalent square(model(numpy.random.randn(40)) - numpy.ones(40)).mean().backward().step()Neural also has a simple and elegant notation for Adverserial Networks
with Adverserial(gen):
# G(X) must be tuned for D(G(X)) == 1
gen[np.random.uniform(-1,1,5)] &= des,1
des[gen[np.random.uniform(-1, 1, 5)]] = 0
python main.py