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()