This is the same as the "example1.py" in the "neurons" folder.
"""
# batteries
import sys
sys.path.append("../../src/")
# spiral framework
from spiral.helper import colored
from spiral.nn import globals
from spiral.nn.impl import Feedforward
if __name__ == "__main__":
globals.runInDebug = True
settings = {"Inputs": 3, "Outputs": 1, "Layers": 2, "NeuronsPerLayer": 2}
nn = Feedforward(**settings)
nn.createNet()
nn.createDefaultSynapses()
inputs = [1.0, 2.0, 3.0]
weights = [0.3, 0.4, -0.1, -0.8, -0.25, 0.25, 1.0, 0.8, 0.7, 0.1, 0.1, 0.2]
nn.update(inputs, weights)
print colored("Neural Network output: %r", fg="yellow") % nn.output(0)
def train (self, Inputs, Output):
Feedforward.update (self, Inputs, self.Weights)
self._calculateDeltas ()
import sys
sys.path.append("../../src/")
# spiral framework
from spiral.helper import colored
from spiral.nn import globals
from spiral.nn.impl import Feedforward
if __name__ == "__main__":
globals.runInDebug = False
settings = {
"Inputs": 3,
"Outputs": 1,
"Layers": 2,
"NeuronsPerLayer": 2,
"AddBias": True
}
nn = Feedforward(**settings)
nn.createNet()
nn.createDefaultSynapses()
inputs = [1.0, 2.0, 3.0]
weights= [ 0.3, 0.4, -0.1, -0.8, -0.25, 0.25, \
1.0, 0.8, 0.7, 0.1, \
0.1, 0.2, 1.0, 0.3, 0.24, 0.324, 0.12 ]
nn.update(inputs, weights)
print "Neural Network epoch completed in: %r seconds" % nn.timeUpdate()
print colored("Neural Network output: %r", fg="yellow") % nn.output(0)
def train(self, Inputs, Output):
Feedforward.update(self, Inputs, self.Weights)
self._calculateDeltas()
