adjust default parameter; successful run recurrent-xor example

tensorneat/genome/gene/conn/__init__.py

@@ -1,2 +1,2 @@
-from .base import BaseConnGene
-from .default import DefaultConnGene
+from .base import BaseConn
+from .default import DefaultConn

tensorneat/genome/gene/conn/base.py

@@ -1,8 +1,7 @@
-import jax
-from .. import BaseGene
+from ..base import BaseGene
 
 
-class BaseConnGene(BaseGene):
+class BaseConn(BaseGene):
     "Base class for connection genes."
     fixed_attrs = ["input_index", "output_index"]
 

tensorneat/genome/gene/conn/default.py

@@ -2,10 +2,10 @@ import jax.numpy as jnp
 import jax.random
 import sympy as sp
 from tensorneat.common import mutate_float
-from .base import BaseConnGene
+from .base import BaseConn
 
 
-class DefaultConnGene(BaseConnGene):
+class DefaultConn(BaseConn):
     "Default connection gene, with the same behavior as in NEAT-python."
 
     custom_attrs = ["weight"]
@@ -14,9 +14,9 @@ class DefaultConnGene(BaseConnGene):
         self,
         weight_init_mean: float = 0.0,
         weight_init_std: float = 1.0,
-        weight_mutate_power: float = 0.5,
-        weight_mutate_rate: float = 0.8,
-        weight_replace_rate: float = 0.1,
+        weight_mutate_power: float = 0.15,
+        weight_mutate_rate: float = 0.2,
+        weight_replace_rate: float = 0.015,
     ):
         super().__init__()
         self.weight_init_mean = weight_init_mean