187 lines
6.9 KiB
Python
187 lines
6.9 KiB
Python
from typing import Tuple
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import jax
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from jax import Array, numpy as jnp, vmap
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from config import NeatConfig
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from core import State, Gene, Genome
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from utils import check_cycles, fetch_random, fetch_first, I_INT, unflatten_conns
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def mutate(config: NeatConfig, gene: Gene, state: State, randkey, genome: Genome, new_node_key):
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"""
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Mutate a population of genomes
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"""
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k1, k2 = jax.random.split(randkey)
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genome = mutate_structure(config, gene, state, k1, genome, new_node_key)
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genome = mutate_values(gene, state, randkey, genome)
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return genome
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def mutate_structure(config: NeatConfig, gene: Gene, state: State, randkey, genome: Genome, new_node_key):
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def mutate_add_node(key_, genome_: Genome):
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i_key, o_key, idx = choice_connection_key(key_, genome_.conns)
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def nothing():
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return genome_
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def successful_add_node():
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# disable the connection
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new_genome = genome_.update_conns(genome_.conns.at[idx, 2].set(False))
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# add a new node
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new_genome = new_genome.add_node(new_node_key, gene.new_node_attrs(state))
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# add two new connections
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new_genome = new_genome.add_conn(i_key, new_node_key, True, gene.new_conn_attrs(state))
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new_genome = new_genome.add_conn(new_node_key, o_key, True, gene.new_conn_attrs(state))
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return new_genome
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# if from_idx == I_INT, that means no connection exist, do nothing
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return jax.lax.cond(idx == I_INT, nothing, successful_add_node)
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def mutate_delete_node(key_, genome_: Genome):
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# TODO: Do we really need to delete a node?
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# randomly choose a node
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key, idx = choice_node_key(key_, genome_.nodes, state.input_idx, state.output_idx,
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allow_input_keys=False, allow_output_keys=False)
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def nothing():
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return genome_
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def successful_delete_node():
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# delete the node
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new_genome = genome_.delete_node_by_pos(idx)
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# delete all connections
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new_conns = jnp.where(((new_genome.conns[:, 0] == key) | (new_genome.conns[:, 1] == key))[:, None],
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jnp.nan, new_genome.conns)
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return new_genome.update_conns(new_conns)
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return jax.lax.cond(idx == I_INT, nothing, successful_delete_node)
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def mutate_add_conn(key_, genome_: Genome):
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# randomly choose two nodes
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k1_, k2_ = jax.random.split(key_, num=2)
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i_key, from_idx = choice_node_key(k1_, genome_.nodes, state.input_idx, state.output_idx,
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allow_input_keys=True, allow_output_keys=True)
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o_key, to_idx = choice_node_key(k2_, genome_.nodes, state.input_idx, state.output_idx,
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allow_input_keys=False, allow_output_keys=True)
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conn_pos = fetch_first((genome_.conns[:, 0] == i_key) & (genome_.conns[:, 1] == o_key))
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def nothing():
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return genome_
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def successful():
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return genome_.add_conn(i_key, o_key, True, gene.new_conn_attrs(state))
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def already_exist():
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return genome_.update_conns(genome_.conns.at[conn_pos, 2].set(True))
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is_already_exist = conn_pos != I_INT
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if config.network_type == 'feedforward':
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u_cons = unflatten_conns(genome_.nodes, genome_.conns)
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cons_exist = jnp.where(~jnp.isnan(u_cons[0, :, :]), True, False)
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is_cycle = check_cycles(genome_.nodes, cons_exist, from_idx, to_idx)
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choice = jnp.where(is_already_exist, 0, jnp.where(is_cycle, 1, 2))
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return jax.lax.switch(choice, [already_exist, nothing, successful])
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elif config.network_type == 'recurrent':
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return jax.lax.cond(is_already_exist, already_exist, successful)
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else:
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raise ValueError(f"Invalid network type: {config.network_type}")
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def mutate_delete_conn(key_, genome_: Genome):
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# randomly choose a connection
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i_key, o_key, idx = choice_connection_key(key_, genome_.conns)
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def nothing():
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return genome_
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def successfully_delete_connection():
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return genome_.delete_conn_by_pos(idx)
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return jax.lax.cond(idx == I_INT, nothing, successfully_delete_connection)
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k1, k2, k3, k4 = jax.random.split(randkey, num=4)
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r1, r2, r3, r4 = jax.random.uniform(k1, shape=(4,))
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def no(k, g):
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return g
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genome = jax.lax.cond(r1 < config.node_add, mutate_add_node, no, k1, genome)
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genome = jax.lax.cond(r2 < config.node_delete, mutate_delete_node, no, k2, genome)
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genome = jax.lax.cond(r3 < config.conn_add, mutate_add_conn, no, k3, genome)
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genome = jax.lax.cond(r4 < config.conn_delete, mutate_delete_conn, no, k4, genome)
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return genome
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def mutate_values(gene: Gene, state: State, randkey, genome: Genome):
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k1, k2 = jax.random.split(randkey, num=2)
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nodes_keys = jax.random.split(k1, num=genome.nodes.shape[0])
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conns_keys = jax.random.split(k2, num=genome.conns.shape[0])
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nodes_attrs, conns_attrs = genome.nodes[:, 1:], genome.conns[:, 3:]
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new_nodes_attrs = vmap(gene.mutate_node, in_axes=(None, 0, 0))(state, nodes_keys, nodes_attrs)
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new_conns_attrs = vmap(gene.mutate_conn, in_axes=(None, 0, 0))(state, conns_keys, conns_attrs)
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# nan nodes not changed
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new_nodes_attrs = jnp.where(jnp.isnan(nodes_attrs), jnp.nan, new_nodes_attrs)
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new_conns_attrs = jnp.where(jnp.isnan(conns_attrs), jnp.nan, new_conns_attrs)
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new_nodes = genome.nodes.at[:, 1:].set(new_nodes_attrs)
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new_conns = genome.conns.at[:, 3:].set(new_conns_attrs)
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return genome.update(new_nodes, new_conns)
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def choice_node_key(rand_key: Array, nodes: Array,
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input_keys: Array, output_keys: Array,
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allow_input_keys: bool = False, allow_output_keys: bool = False) -> Tuple[Array, Array]:
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"""
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Randomly choose a node key from the given nodes. It guarantees that the chosen node not be the input or output node.
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:param rand_key:
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:param nodes:
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:param input_keys:
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:param output_keys:
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:param allow_input_keys:
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:param allow_output_keys:
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:return: return its key and position(idx)
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"""
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node_keys = nodes[:, 0]
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mask = ~jnp.isnan(node_keys)
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if not allow_input_keys:
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mask = jnp.logical_and(mask, ~jnp.isin(node_keys, input_keys))
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if not allow_output_keys:
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mask = jnp.logical_and(mask, ~jnp.isin(node_keys, output_keys))
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idx = fetch_random(rand_key, mask)
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key = jnp.where(idx != I_INT, nodes[idx, 0], jnp.nan)
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return key, idx
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def choice_connection_key(rand_key: Array, conns: Array):
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"""
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Randomly choose a connection key from the given connections.
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:return: i_key, o_key, idx
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"""
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idx = fetch_random(rand_key, ~jnp.isnan(conns[:, 0]))
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i_key = jnp.where(idx != I_INT, conns[idx, 0], jnp.nan)
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o_key = jnp.where(idx != I_INT, conns[idx, 1], jnp.nan)
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return i_key, o_key, idx
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