import random
from examples.NIPS.MNIST.noisy_sequence_detection.scenario001.generate_data import generate_data
from itertools import islice
def contains_element_n_times(l, x, n):
gen = (True for i in l if i == x)
return next(islice(gen, n - 1, None), False)
def get_correct_digit_for_initiated_at(digit, last_digits, threshold,
available_digits, appearances):
if contains_element_n_times(last_digits, digit, appearances):
return digit, True
return None, None
if __name__ == '__main__':
generate_data(
scenario_function=lambda *args, **kwargs:
get_correct_digit_for_initiated_at(*args, **kwargs, appearances=2),
test_function=lambda *args, **kwargs:
get_correct_digit_for_initiated_at(*args, **kwargs, appearances=2),
relevant_digits=2,
noises_function=lambda: [0.0])
import random
from examples.NIPS.MNIST.noisy_sequence_detection.scenario001.generate_data import generate_data
from examples.NIPS.MNIST.noisy_sequence_detection.scenario103_2.generate_data import get_correct_digit_for_initiated_at
from examples.NIPS.MNIST.noisy_sequence_detection.scenario108_2.generate_data import get_initiated_at_scenario108
if __name__ == '__main__':
available_digits = list(range(10))
swap_from = random.choice(available_digits)
swap_to = random.choice(available_digits)
# Ensure that we are not swapping a number for itself
while swap_from == swap_to:
swap_to = random.choice(available_digits)
with open('swap.txt', 'w') as o:
o.write('{},{}'.format(swap_from, swap_to))
generate_data(
scenario_function=lambda *args, **kwargs: get_initiated_at_scenario108(
*args, **kwargs, swap=(swap_from, swap_to)),
test_function=get_correct_digit_for_initiated_at,
relevant_digits=2)
import random
from examples.NIPS.MNIST.noisy_sequence_detection.scenario001.generate_data import generate_data
def get_correct_digit_for_initiated_at(digit, last_digits, threshold, available_digits):
if digit in last_digits:
return digit, True
return None, None
if __name__ == '__main__':
generate_data(
scenario_function=get_correct_digit_for_initiated_at,
test_function=get_correct_digit_for_initiated_at,
relevant_digits=3,
noises_function=lambda: [0.0]
)
import random
from examples.NIPS.MNIST.noisy_sequence_detection.scenario001.generate_data import generate_data
def get_digit_for_initiated_at(digit, last_digits, threshold,
available_digits):
if digit == last_digits[-1]:
return digit, True
elif random.random() < threshold:
return random.choice(available_digits), False
return None, None
if __name__ == '__main__':
generate_data(scenario_function=get_digit_for_initiated_at)
import random
from examples.NIPS.MNIST.noisy_sequence_detection.scenario001.generate_data import generate_data
from examples.NIPS.MNIST.noisy_sequence_detection.scenario103_2.generate_data import get_initiated_at_scenario103, \
get_correct_digit_for_initiated_at
if __name__ == '__main__':
generate_data(
scenario_function=get_initiated_at_scenario103,
test_function=get_correct_digit_for_initiated_at,
relevant_digits=4
)
5: 0.6,
6: 0.7,
7: 0.8,
8: 0.9,
9: 1.0,
}
def get_probability(t, probabilities=None):
if probabilities is None:
probabilities = DEFAULT_PROBABILITIES
return probabilities[t[1]]
def filter_by_probability(t, probabilities=None):
return random.random() < get_probability(t, probabilities)
if __name__ == '__main__':
assignment = get_random_assignment(list(range(10)))
with open('assignment.txt', 'w') as o:
o.write(str(assignment))
filtered_trainset = list(filter(filter_by_probability, trainset))
generate_data(
training_set=filtered_trainset,
)
import random
from examples.NIPS.MNIST.noisy_sequence_detection.scenario001.generate_data import generate_data
from examples.NIPS.MNIST.noisy_sequence_detection.scenario004.generate_data import get_random_assignment
from examples.NIPS.MNIST.noisy_sequence_detection.scenario103_2.generate_data import get_correct_digit_for_initiated_at
from examples.NIPS.MNIST.noisy_sequence_detection.scenario104_2.generate_data import get_initiated_at_scenario104
if __name__ == '__main__':
assignment = get_random_assignment(list(range(10)))
with open('assignment.txt', 'w') as o:
o.write(str(assignment))
generate_data(
scenario_function=lambda *args, **kwargs: get_initiated_at_scenario104(
*args, **kwargs, assignment=assignment),
test_function=get_correct_digit_for_initiated_at,
relevant_digits=4)
from examples.NIPS.MNIST.noisy_sequence_detection.scenario001.generate_data import generate_data
def get_digit_for_initiated_at(digit, last_digits, threshold, available_digits,
swap):
if digit == last_digits[-1]:
if digit == swap[0] and random.random() < threshold:
return swap[1], False
else:
return digit, True
return None, None
if __name__ == '__main__':
available_digits = list(range(10))
swap_from = random.choice(available_digits)
swap_to = random.choice(available_digits)
# Ensure that we are not swapping a number for itself
while swap_from == swap_to:
swap_to = random.choice(available_digits)
with open('swap.txt', 'w') as o:
o.write('{},{}'.format(swap_from, swap_to))
generate_data(
scenario_function=lambda *args, **kwargs: get_digit_for_initiated_at(
*args, **kwargs, swap=(swap_from, swap_to)))
return None, None
def check_swap_for_itself(assignment):
for i, a in enumerate(assignment):
if i == a:
return True
return False
def get_random_assignment(digits):
assignment = digits
while check_swap_for_itself(assignment):
random.shuffle(assignment)
return assignment
if __name__ == '__main__':
assignment = get_random_assignment(list(range(10)))
with open('assignment.txt', 'w') as o:
o.write(str(assignment))
generate_data(
scenario_function=lambda *args, **kwargs: get_digit_for_initiated_at(
*args, **kwargs, assignment=assignment))
# True label is used
return digit, True
elif random.random() < threshold:
# Random label is added
return random.choice(available_digits), False
return None, None
def noises(min_noise=0.0, max_noise=1.1, noise_step=0.2):
return np.arange(min_noise, max_noise, noise_step)
def folder_name(noise):
return 'noise_{0:.2f}/'.format(noise).replace('.', '_')
if __name__ == '__main__':
assignment = get_random_assignment(list(range(10)))
with open('assignment.txt', 'w') as o:
o.write(str(assignment))
generate_data(
noises_function=noises,
folder_name=folder_name,
scenario_function=lambda *args, **kwargs: get_digit_for_initiated_at(
*args, **kwargs, assignment=assignment
)
)
