add visualize module

This commit is contained in:
wls2002
2023-06-29 10:20:48 +08:00
parent 01b7731231
commit f5c1ce72f9
7 changed files with 121 additions and 92 deletions

View File

@@ -6,3 +6,5 @@ from .population import update_species, create_next_generation, speciate
from .genome.activations import act_name2func
from .genome.aggregations import agg_name2func
from .visualize import Genome

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@@ -1,88 +0,0 @@
from collections import defaultdict
import numpy as np
def check_array_valid(nodes, cons, input_keys, output_keys):
nodes_dict, cons_dict = array2object(nodes, cons, input_keys, output_keys)
# assert is_DAG(cons_dict.keys()), "The genome is not a DAG!"
def array2object(nodes, cons, input_keys, output_keys):
"""
Convert a genome from array to dict.
:param nodes: (N, 5)
:param cons: (C, 4)
:param output_keys:
:param input_keys:
:return: nodes_dict[key: (bias, response, act, agg)], cons_dict[(i_key, o_key): (weight, enabled)]
"""
# update nodes_dict
nodes_dict = {}
for i, node in enumerate(nodes):
if np.isnan(node[0]):
continue
key = int(node[0])
assert key not in nodes_dict, f"Duplicate node key: {key}!"
if key in input_keys:
assert np.all(np.isnan(node[1:])), f"Input node {key} must has None bias, response, act, or agg!"
nodes_dict[key] = (None,) * 4
else:
assert np.all(~np.isnan(node[1:])), f"Normal node {key} must has non-None bias, response, act, or agg!"
bias = node[1]
response = node[2]
act = node[3]
agg = node[4]
nodes_dict[key] = (bias, response, act, agg)
# check nodes_dict
for i in input_keys:
assert i in nodes_dict, f"Input node {i} not found in nodes_dict!"
for o in output_keys:
assert o in nodes_dict, f"Output node {o} not found in nodes_dict!"
# update connections
cons_dict = {}
for i, con in enumerate(cons):
if np.all(np.isnan(con)):
pass
elif np.all(~np.isnan(con)):
i_key = int(con[0])
o_key = int(con[1])
if (i_key, o_key) in cons_dict:
assert False, f"Duplicate connection: {(i_key, o_key)}!"
assert i_key in nodes_dict, f"Input node {i_key} not found in nodes_dict!"
assert o_key in nodes_dict, f"Output node {o_key} not found in nodes_dict!"
weight = con[2]
enabled = (con[3] == 1)
cons_dict[(i_key, o_key)] = (weight, enabled)
else:
assert False, f"Connection {i} must has all None or all non-None!"
return nodes_dict, cons_dict
def is_DAG(edges):
all_nodes = set()
for a, b in edges:
if a == b: # cycle
return False
all_nodes.union({a, b})
for node in all_nodes:
visited = {n: False for n in all_nodes}
def dfs(n):
if visited[n]:
return False
visited[n] = True
for a, b in edges:
if a == n:
if not dfs(b):
return False
return True
if not dfs(node):
return False
return True

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@@ -0,0 +1,112 @@
import jax
import numpy as np
class Genome:
def __init__(self, nodes, cons, config):
self.config = config
self.nodes, self.cons = array2object(nodes, cons, config)
if config['renumber_nodes']:
self.renumber()
def __repr__(self):
return f'Genome(\n' \
f'\tinput_keys: {self.config["input_idx"]}, \n' \
f'\toutput_keys: {self.config["output_idx"]}, \n' \
f'\tnodes: \n\t\t' \
f'{self.repr_nodes()} \n' \
f'\tconnections: \n\t\t' \
f'{self.repr_conns()} \n)'
def repr_nodes(self):
nodes_info = []
for key, value in self.nodes.items():
bias, response, act, agg = value
act_func = self.config['activation_option_names'][int(act)] if act is not None else None
agg_func = self.config['aggregation_option_names'][int(agg)] if agg is not None else None
s = f"{key}: (bias: {bias}, response: {response}, act: {act_func}, agg: {agg_func})"
nodes_info.append(s)
return ',\n\t\t'.join(nodes_info)
def repr_conns(self):
conns_info = []
for key, value in self.cons.items():
weight, enabled = value
s = f"{key}: (weight: {weight}, enabled: {enabled})"
conns_info.append(s)
return ',\n\t\t'.join(conns_info)
def renumber(self):
nodes2new_nodes = {}
new_id = len(self.config['input_idx']) + len(self.config['output_idx'])
for key in self.nodes.keys():
if key in self.config['input_idx'] or key in self.config['output_idx']:
nodes2new_nodes[key] = key
else:
nodes2new_nodes[key] = new_id
new_id += 1
new_nodes, new_cons = {}, {}
for key, value in self.nodes.items():
new_nodes[nodes2new_nodes[key]] = value
for key, value in self.cons.items():
i_key, o_key = key
new_cons[(nodes2new_nodes[i_key], nodes2new_nodes[o_key])] = value
self.nodes = new_nodes
self.cons = new_cons
def array2object(nodes, cons, config):
"""
Convert a genome from array to dict.
:param nodes: (N, 5)
:param cons: (C, 4)
:return: nodes_dict[key: (bias, response, act, agg)], cons_dict[(i_key, o_key): (weight, enabled)]
"""
nodes, cons = jax.device_get((nodes, cons))
# update nodes_dict
nodes_dict = {}
for i, node in enumerate(nodes):
if np.isnan(node[0]):
continue
key = int(node[0])
assert key not in nodes_dict, f"Duplicate node key: {key}!"
if key in config['input_idx']:
assert np.all(np.isnan(node[1:])), f"Input node {key} must has None bias, response, act, or agg!"
nodes_dict[key] = (None,) * 4
else:
assert np.all(
~np.isnan(node[1:])), f"Normal node {key} must has non-None bias, response, act, or agg!"
bias = node[1]
response = node[2]
act = node[3]
agg = node[4]
nodes_dict[key] = (bias, response, act, agg)
# check nodes_dict
for i in config['input_idx']:
assert i in nodes_dict, f"Input node {i} not found in nodes_dict!"
for o in config['output_idx']:
assert o in nodes_dict, f"Output node {o} not found in nodes_dict!"
# update connections
cons_dict = {}
for i, con in enumerate(cons):
if np.all(np.isnan(con)):
pass
elif np.all(~np.isnan(con)):
i_key = int(con[0])
o_key = int(con[1])
if (i_key, o_key) in cons_dict:
assert False, f"Duplicate connection: {(i_key, o_key)}!"
assert i_key in nodes_dict, f"Input node {i_key} not found in nodes_dict!"
assert o_key in nodes_dict, f"Output node {o_key} not found in nodes_dict!"
weight = con[2]
enabled = (con[3] == 1)
cons_dict[(i_key, o_key)] = (weight, enabled)
else:
assert False, f"Connection {i} must has all None or all non-None!"
return nodes_dict, cons_dict

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@@ -65,3 +65,6 @@ weight_replace_rate = 0.1
[gene-enable]
enable_mutate_rate = 0.01
[visualize]
renumber_nodes = True

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@@ -1,8 +1,8 @@
import numpy as np
from configs import Configer
from algorithms.neat.pipeline import Pipeline
from algorithms.neat import Genome
from pipeline import Pipeline
xor_inputs = np.array([[0, 0], [0, 1], [1, 0], [1, 1]], dtype=np.float32)
xor_outputs = np.array([[0], [1], [1], [0]], dtype=np.float32)
@@ -22,8 +22,8 @@ def main():
config = Configer.load_config("xor.ini")
pipeline = Pipeline(config, seed=6)
nodes, cons = pipeline.auto_run(evaluate)
print(nodes)
print(cons)
g = Genome(nodes, cons, config)
print(g)
if __name__ == '__main__':