def random_centered_test(x, y):
def condition(DNA):
return max_layer(DNA, 15)
center = ((-1, 1, 3, x, y), (0, 3, 5, x, y), (1, 5, 2), (2, ), (3, -1, 0),
(3, 0, 1), (3, 1, 2))
version = 'final'
space = space = DNA_Graph(center, 1, (x, y), condition,
((0, 0, 1), (0, 0, 1, 1), (0, 1, 0, 0),
(1, 0, 0, 0)), version)
center = space.center
node_c = space.graph.key2node.get(center)
Funct.set_num_particles(node_c.kids[0], 10)
print(f'the center is {center}')
Selector = Cen_rand_select()
k = 10
while k > 0:
Selector.update(space)
Selector.print_observation()
print(Selector.get_predicted_actions())
k = k - 1
actions = Selector.get_predicted_actions()
space = space = DNA_Graph(center, 1, (x, y), condition, actions, version,
Creator_s)
space.imprimir()
def linear_filter(x, y):
ks = [2]
center = ((0, 3, ks[0], x, y), (1, ks[0], 2), (2, ))
space = DNA_Graph(center, 5, (x, y))
print('linear_filter: done')
space.imprimir()
print(space.type)
return space
def add_filter_i(x, y):
def condition(DNA):
return max_layer(DNA, 10)
center = ((0, 3, 4, 2, 2), (0, 7, 4, x, y), (1, 4, 2), (2, ))
space = DNA_Graph(center, 2, (x, y), condition, (0, (0, 1, 0, 0)))
space.imprimir()
#print(space.key2node(center))
return space
def linear_kernel_width(x, y):
ks = [2]
center = ((0, 3, int(2 * ks[0]), 2, 2), (0, int(2 * ks[0]), ks[0], x - 1,
y - 1), (1, ks[0], 2), (2, ))
print('linear_kernel_width: done')
space = DNA_Graph(center, 5, (x, y), (0, (0, 1, 0, 0)))
print(space.type)
space.imprimir()
#print(space.key2node(center))
return space
def linear_kernel_depth(x, y):
def condition(DNA):
return max_layer(DNA, 10)
center = ((0, 3, 10, 1, 3, 3), (0, 1, 20, 3, 3, 3), (0, 1, 20, 160, 7, 7),
(1, 20, 2), (2, ))
print('linear_kernel_depth: done')
space = DNA_Graph(center, 5, (x, y), condition, (0, (0, 0, 1, 1)))
space.imprimir()
print(space.length())
return space
def kernel_height_creator(x, y):
def condition(DNA):
return max_layer(DNA, 10)
creator = Creator(((0, 1, 0, 0), (0, 0, 1, 1)), condition)
center = ((0, 3, 4, 2, 2), (0, 4, 5, x - 1, y - 1), (1, 5, 2), (2, ))
space = space = DNA_Graph(center, 20, (x, y), condition, (0, (0, 0, 1, 1)))
print('linear_filter: done')
space.imprimir()
print(space.length())
def DNA_Creator_s(x, y):
def condition(DNA):
output = True
if DNA:
for num_layer in range(0, len(DNA) - 3):
layer = DNA[num_layer]
x_l = layer[3]
y_l = layer[4]
output = output and (x_l < x) and (y_l < y)
if output:
return max_layer(DNA, 3)
center = ((0, 3, 5, 3, 3), (0, 8, 8, 3, 3), (0, 11, 5, x, y), (1, 5, 2),
(2, ))
version = 'inclusion'
space = DNA_Graph(center, 2, (x, y), condition,
((0, (0, 0, 1, 1)), (1, (0, 1, 0, 0))), version,
Creator_s)
space.imprimir()
print(space.length())
def DNA_test_f(x, y):
def condition(DNA):
return max_layer(DNA, 15)
center = ((-1, 1, 3, x, y), (0, 3, 5, 3, 3), (0, 5, 5, x - 2, y - 2),
(1, 5, 2), (2, ), (3, -1, 0), (3, 0, 1), (3, 1, 2), (3, 2, 3))
version = 'final'
space = space = DNA_Graph(center, 2, (x, y), condition,
((0, 0, 1), (0, 0, 1, 1), (0, 1, 0, 0),
(1, 0, 0, 0)), version)
space.imprimir()
print(space.length())
def initialize():
S = 100
Comp = 2
dataGen = GeneratorFromImage.GeneratorFromImage(Comp, S, cuda=False)
dataGen.dataConv2d()
x = dataGen.size[1]
y = dataGen.size[2]
ks = [2]
def condition(DNA):
return max_layer(DNA, 10)
center = ((0, 3, ks[0], x, y), (1, ks[0], 2), (2, ))
space = DNA_Graph(center, 10, (x, y), condition, (0, (1, 1, 0, 0)))
Phase_space = DNA_Phase_space(space)
return Phase_space
def kernel_increase_i(x, y):
def condition(DNA):
output = True
if DNA:
for num_layer in range(0, len(DNA) - 3):
layer = DNA[num_layer]
x_l = layer[3]
y_l = layer[4]
output = output and (x_l < x) and (y_l < y)
if output:
return max_layer(DNA, 10)
center = ((0, 3, 5, 3, 3), (0, 3, 8, 3, 3), (0, 7, 5, x, y), (1, 5, 2),
(2, ))
version = 'inclusion'
space = space = DNA_Graph(center, 4, (x, y), condition, (0, (0, 0, 1, 1)),
version)
space.imprimir()
print(space.length())