tony/tensorneat-mend
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All function with state will update the state and return it.

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Remove randkey args in functions with state, since it can attach the randkey by states.
This commit is contained in:
wls2002
2024-05-25 20:45:57 +08:00
parent 5626fddf41
commit 79d53ea7af
12 changed files with 84 additions and 70 deletions
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4
tensorneat/algorithm/neat/ga/crossover/base.py
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@@ -3,8 +3,8 @@ from utils import State
class BaseCrossover:
def setup(self, key, state=State()):
def setup(self, state=State()):
return state
def __call__(self, state, key, genome, nodes1, nodes2, conns1, conns2):
def __call__(self, state, genome, nodes1, nodes2, conns1, conns2):
raise NotImplementedError

10
tensorneat/algorithm/neat/ga/crossover/default.py
View File

@@ -5,12 +5,12 @@ from .base import BaseCrossover
class DefaultCrossover(BaseCrossover):
def __call__(self, state, key, genome, nodes1, conns1, nodes2, conns2):
def __call__(self, state, genome, nodes1, conns1, nodes2, conns2):
"""
use genome1 and genome2 to generate a new genome
notice that genome1 should have higher fitness than genome2 (genome1 is winner!)
"""
randkey_1, randkey_2, key = jax.random.split(key, 3)
randkey1, randkey2, randkey = jax.random.split(state.randkey, 3)
# crossover nodes
keys1, keys2 = nodes1[:, 0], nodes2[:, 0]
@@ -20,16 +20,16 @@ class DefaultCrossover(BaseCrossover):
# For not homologous genes, use the value of nodes1(winner)
# For homologous genes, use the crossover result between nodes1 and nodes2
new_nodes = jnp.where(jnp.isnan(nodes1) | jnp.isnan(nodes2), nodes1,
self.crossover_gene(randkey_1, nodes1, nodes2, is_conn=False))
self.crossover_gene(randkey1, nodes1, nodes2, is_conn=False))
# crossover connections
con_keys1, con_keys2 = conns1[:, :2], conns2[:, :2]
conns2 = self.align_array(con_keys1, con_keys2, conns2, is_conn=True)
new_conns = jnp.where(jnp.isnan(conns1) | jnp.isnan(conns2), conns1,
self.crossover_gene(randkey_2, conns1, conns2, is_conn=True))
self.crossover_gene(randkey2, conns1, conns2, is_conn=True))
return new_nodes, new_conns
return state.update(randkey=randkey), new_nodes, new_conns
def align_array(self, seq1, seq2, ar2, is_conn: bool):
"""