def Profile_Activation_Functions():
# First, initialize two networks. One will use Rational activation functions
# and the other will use Tanh.
Rational_NN = Network.Neural_Network(Num_Hidden_Layers=5,
Neurons_Per_Layer=100,
Input_Dim=3,
Output_Dim=1,
Activation_Function="Rational")
Tanh_NN = Network.Neural_Network(Num_Hidden_Layers=5,
Neurons_Per_Layer=100,
Input_Dim=3,
Output_Dim=1,
Activation_Function="Tanh")
# Now generate some random data.
Data = torch.rand((20000, 3), dtype=torch.float32, requires_grad=True)
# Pass the data through both networks, time it.
Rational_Timer = Timing.Timer()
Tanh_Timer = Timing.Timer()
Rational_Timer.Start()
Rational_NN(Data)
Rational_Time = Rational_Timer.Stop()
Tanh_Timer.Start()
Tanh_NN(Data)
Tanh_Time = Tanh_Timer.Stop()
# Print results.
print("Rational: %fs" % Rational_Time)
print("Tanh: %fs" % Tanh_Time)
