def experiments() -> None: REPS = 10 lab = Lab( MNISTMLP, REPS, 'lista2/wyniki', hidden_size=128, batch_size=32, weights_range=(-0.5, 0.5), alpha=0.01, activation_name='relu', ) # Hidden size h_size = Experiment( title='h_size', f_name='h_size_1024', test_parameter=( 'hidden_size', [ 16, 128, 512, 2048, ], ), ) lab.add_experiment(h_size) # Alpha alpha = Experiment( title='alpha', f_name='alpha_1024', test_parameter=( 'alpha', [ 0.0001, 0.001, 0.01, 0.1, 1.0, ], ), ) lab.add_experiment(alpha) # Weight range w_range = Experiment( title='w_range', f_name='w_range_1024', test_parameter=( 'weights_range', [ (0.0, 0.0), (-0.1, 0.1), (-0.5, 0.5), (-2.0, 2.0), ], ), ) lab.add_experiment(w_range) # Batch batch_size = Experiment( title='batch_size', f_name='batch_size_1024', test_parameter=( 'batch_size', [ 1, 8, 32, 128, 1024, ], ), ) lab.add_experiment(batch_size) # ReLU activation = Experiment( title='activation', f_name='activation_1024', test_parameter=( 'activation_name', [ 'sigmoid', 'relu', ], ), ) lab.add_experiment(activation) lab.run()
from lab.experiments import Experiment from lab.lab import Lab from lista4.conv import ConvMNIST if __name__ == "__main__": REPS = 10 lab = Lab( ConvMNIST, REPS, 'lista4/wyniki', ) # Kernel size ker = Experiment( title='kernel', f_name='kernel', test_parameter=( 'kernel_size', [ 3, 5, 7, ], ), ) lab.add_experiment(ker) lab.run()
def experiments() -> None: REPS = 10 ## PERCEPTRON perceptron_lab = Lab( ANDPerceptron, REPS, '/lista1/wyniki', bipolar=False, theta=0, bias=True, weight_range=(-0.5, 0.5), alpha=0.01, ) # Theta perceptron_theta_uni = Experiment( title='Perceptron, uni, theta', f_name='per_theta_uni', test_parameter=('theta', [-1.0, -0.8, -0.5, -0.2, 0.0, 0.2, 0.5, 0.8, 1.0]), bias=False, ) perceptron_lab.add_experiment(perceptron_theta_uni) perceptron_theta_bi = Experiment( title='Perceptron, bi, theta', f_name='per_theta_bi', test_parameter=('theta', [-1.0, -0.8, -0.5, -0.2, 0.0, 0.2, 0.5, 0.8, 1.0]), bias=False, ) perceptron_lab.add_experiment(perceptron_theta_bi) # Weight range perceptron_w_uni = Experiment( title='Perceptron, uni, w', f_name='per_w_uni', test_parameter=( 'weight_range', [ (0.0, 0.0), (-0.1, 0.1), (-0.2, 0.2), (-0.5, 0.5), (-0.8, 0.8), (-1.0, 1.0), ], ), ) perceptron_lab.add_experiment(perceptron_w_uni) perceptron_w_bi = Experiment( title='Perceptron, bi, theta', f_name='per_w_bi', test_parameter=( 'weight_range', [ (0.0, 0.0), (-0.1, 0.1), (-0.2, 0.2), (-0.5, 0.5), (-0.8, 0.8), (-1.0, 1.0), ], ), ) perceptron_lab.add_experiment(perceptron_w_bi) # Alpha perceptron_alpha_uni = Experiment( title='Perceptron, uni, alpha', f_name='per_alpha_uni', test_parameter=('alpha', [0.0001, 0.001, 0.01, 0.1, 1.0]), ) perceptron_lab.add_experiment(perceptron_alpha_uni) perceptron_alpha_bi = Experiment( title='Perceptron, bi, alpha', f_name='per_alpha_bi', test_parameter=('alpha', [0.0001, 0.001, 0.01, 0.1, 1.0]), ) perceptron_lab.add_experiment(perceptron_alpha_bi) ## ADALINE adaline_lab = Lab( ANDAdaline, REPS, '/lista1/wyniki', theta=0, bias=True, weight_range=(-0.5, 0.5), alpha=0.01, ) # Weight range adaline_w = Experiment( title='Adaline, w', f_name='ada_w', test_parameter=( 'weight_range', [ (0.0, 0.0), (-0.1, 0.1), (-0.2, 0.2), (-0.5, 0.5), (-0.8, 0.8), (-1.0, 1.0), ], ), ) adaline_lab.add_experiment(adaline_w) # Alpha adaline_alpha = Experiment( title='Adaline, alpha', f_name='ada_alpha', test_parameter=('alpha', [0.0001, 0.001, 0.01, 0.1, 1.0]), ) adaline_lab.add_experiment(adaline_alpha) # Epsilon adaline_epsilon = Experiment( title='Adaline, epsilon', f_name='ada_epsilon', test_parameter=('epsilon', [0]), ) adaline_lab.add_experiment(adaline_epsilon) perceptron_lab.run() adaline_lab.run()