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disable activation in the output node of network;

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we recommend to use output_transform;
change hyperparameters (strong) in XOR example;
This commit is contained in:
wls2002
2024-05-22 11:09:25 +08:00
parent bb80f12640
commit 1fe5d5fca2
7 changed files with 59 additions and 14 deletions
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17
tensorneat/examples/func_fit/xor.py
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@@ -2,6 +2,7 @@ from pipeline import Pipeline
from algorithm.neat import *
from problem.func_fit import XOR3d
from utils import Act
if __name__ == '__main__':
pipeline = Pipeline(
@@ -10,13 +11,25 @@ if __name__ == '__main__':
genome=DefaultGenome(
num_inputs=3,
num_outputs=1,
max_nodes=50,
max_conns=100,
max_nodes=100,
max_conns=200,
node_gene=DefaultNodeGene(
activation_default=Act.tanh,
activation_options=(Act.tanh,),
),
output_transform=Act.sigmoid, # the activation function for output node
),
pop_size=10000,
species_size=10,
compatibility_threshold=3.5,
survival_threshold=0.01, # magic
),
mutation=DefaultMutation(
node_add=0.05,
conn_add=0.2,
node_delete=0,
conn_delete=0,
)
),
problem=XOR3d(),
generation_limit=10000,

5
tensorneat/examples/func_fit/xor3d_hyperneat.py
View File

@@ -28,14 +28,17 @@ if __name__ == '__main__':
activation_default=Act.tanh,
activation_options=(Act.tanh,),
),
output_transform=Act.tanh, # the activation function for output node in NEAT
),
pop_size=10000,
species_size=10,
compatibility_threshold=3.5,
survival_threshold=0.03,
),
),
activation=Act.sigmoid,
activation=Act.tanh,
activate_time=10,
output_transform=Act.sigmoid, # the activation function for output node in HyperNEAT
),
problem=XOR3d(),
generation_limit=300,

12
tensorneat/examples/func_fit/xor_recurrent.py
View File

@@ -2,8 +2,7 @@ from pipeline import Pipeline
from algorithm.neat import *
from problem.func_fit import XOR3d
from utils.activation import ACT_ALL
from utils.aggregation import AGG_ALL
from utils.activation import ACT_ALL, Act
if __name__ == '__main__':
pipeline = Pipeline(
@@ -18,14 +17,21 @@ if __name__ == '__main__':
activate_time=5,
node_gene=DefaultNodeGene(
activation_options=ACT_ALL,
# aggregation_options=AGG_ALL,
activation_replace_rate=0.2
),
output_transform=Act.sigmoid
),
pop_size=10000,
species_size=10,
compatibility_threshold=3.5,
survival_threshold=0.03,
),
mutation=DefaultMutation(
node_add=0.05,
conn_add=0.2,
node_delete=0,
conn_delete=0,
)
),
problem=XOR3d(),
generation_limit=10000,