def UnitTestNN():
fa = NeuralNet(2, 3)
input, output = [], []
for i in range(10000):
x, y = rd.random(), rd.random()
input.append([x, y])
output.append([x * y, x - y, x + y])
fa.getTrainingData(np.vstack(np.array(input)), np.vstack(np.array(output)))
fa.train()
fa.saveTheta("test.theta")
fa.loadTheta("test.theta")
for i in range(20):
x, y = 3 * rd.random(), 3 * rd.random()
approx = fa.computeOutput(np.array([x, y]))
print("in:", [x, y])
print(" out:", approx)
print(" real:", [x * y, x - y, x + y])
def UnitTestNN():
fa = NeuralNet(2,3)
input, output = [], []
for i in range(10000):
x,y = rd.random(), rd.random()
input.append([x,y])
output.append([x*y, x-y, x+y])
fa.getTrainingData(np.vstack(np.array(input)), np.vstack(np.array(output)))
fa.train()
fa.saveTheta("test.theta")
fa.loadTheta("test.theta")
for i in range(20):
x,y = 3*rd.random(), 3*rd.random()
approx = fa.computeOutput(np.array([x,y]))
print("in:", [x,y])
print(" out:", approx)
print(" real:", [x*y, x-y, x+y])
