dfc8f9198e
add ipynb test for testing whether add node or add conn will not change the output for the network.
79 lines
2.2 KiB
Python
79 lines
2.2 KiB
Python
import jax.numpy as jnp
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import jax.random
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from utils import mutate_float
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from . import BaseConnGene
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class DefaultConnGene(BaseConnGene):
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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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def __init__(
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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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):
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super().__init__()
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self.weight_init_mean = weight_init_mean
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self.weight_init_std = weight_init_std
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self.weight_mutate_power = weight_mutate_power
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self.weight_mutate_rate = weight_mutate_rate
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self.weight_replace_rate = weight_replace_rate
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def new_zero_attrs(self, state):
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return jnp.array([0.0]) # weight = 0
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def new_identity_attrs(self, state):
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return jnp.array([1.0]) # weight = 1
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def new_random_attrs(self, state, randkey):
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weight = (
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jax.random.normal(randkey, ()) * self.weight_init_std
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+ self.weight_init_mean
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)
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return jnp.array([weight])
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def mutate(self, state, randkey, attrs):
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weight = attrs[0]
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weight = mutate_float(
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randkey,
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weight,
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self.weight_init_mean,
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self.weight_init_std,
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self.weight_mutate_power,
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self.weight_mutate_rate,
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self.weight_replace_rate,
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)
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return jnp.array([weight])
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def distance(self, state, attrs1, attrs2):
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weight1 = attrs1[0]
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weight2 = attrs2[0]
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return jnp.abs(weight1 - weight2)
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def forward(self, state, attrs, inputs):
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weight = attrs[0]
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return inputs * weight
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def repr(self, state, conn, precision=2, idx_width=3, func_width=8):
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in_idx, out_idx, weight = conn
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in_idx = int(in_idx)
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out_idx = int(out_idx)
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weight = round(float(weight), precision)
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return "{}(in: {:<{idx_width}}, out: {:<{idx_width}}, weight: {:<{float_width}})".format(
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self.__class__.__name__,
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in_idx,
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out_idx,
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weight,
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idx_width=idx_width,
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float_width=precision + 3,
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)
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