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