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remove useless codes

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This commit is contained in:
wls2002
2023-05-07 16:30:26 +08:00
parent 890c928b0f
commit cec40b254f
24 changed files with 3 additions and 2601 deletions
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84
examples/distance_test.py
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@@ -1,84 +0,0 @@
from typing import Callable, List
from functools import partial
import numpy as np
from utils import Configer
from algorithms.neat.genome.numpy import analysis, distance
from algorithms.neat.genome.numpy import create_initialize_function, create_mutate_function
def real_distance(nodes1, connections1, nodes2, connections2, input_idx, output_idx):
nodes1, connections1 = analysis(nodes1, connections1, input_idx, output_idx)
nodes2, connections2 = analysis(nodes2, connections2, input_idx, output_idx)
compatibility_coe = 0.5
disjoint_coe = 1.
node_distance = 0.0
if nodes1 or nodes2: # otherwise, both are empty
disjoint_nodes = 0
for k2 in nodes2:
if k2 not in nodes1:
disjoint_nodes += 1
for k1, n1 in nodes1.items():
n2 = nodes2.get(k1)
if n2 is None:
disjoint_nodes += 1
else:
if n1[0] is None:
continue
d = abs(n1[0] - n2[0]) + abs(n1[1] - n2[1])
d += 1 if n1[2] != n2[2] else 0
d += 1 if n1[3] != n2[3] else 0
node_distance += d
max_nodes = max(len(nodes1), len(nodes2))
node_distance = (compatibility_coe * node_distance + disjoint_coe * disjoint_nodes) / max_nodes
connection_distance = 0.0
if connections1 or connections2:
disjoint_connections = 0
for k2 in connections2:
if k2 not in connections1:
disjoint_connections += 1
for k1, c1 in connections1.items():
c2 = connections2.get(k1)
if c2 is None:
disjoint_connections += 1
else:
# Homologous genes compute their own distance value.
d = abs(c1[0] - c2[0])
d += 1 if c1[1] != c2[1] else 0
connection_distance += d
max_conn = max(len(connections1), len(connections2))
connection_distance = (compatibility_coe * connection_distance + disjoint_coe * disjoint_connections) / max_conn
return node_distance + connection_distance
def main():
config = Configer.load_config()
keys_idx = config.basic.num_inputs + config.basic.num_outputs
pop_size = config.neat.population.pop_size
init_func = create_initialize_function(config)
pop_nodes, pop_connections, input_idx, output_idx = init_func()
mutate_func = create_mutate_function(config, input_idx, output_idx, batch=True)
while True:
pop_nodes, pop_connections = mutate_func(pop_nodes, pop_connections, list(range(keys_idx, keys_idx + pop_size)))
keys_idx += pop_size
for i in range(pop_size):
for j in range(pop_size):
nodes1, connections1 = pop_nodes[i], pop_connections[i]
nodes2, connections2 = pop_nodes[j], pop_connections[j]
numpy_d = distance(nodes1, connections1, nodes2, connections2)
real_d = real_distance(nodes1, connections1, nodes2, connections2, input_idx, output_idx)
assert np.isclose(numpy_d, real_d), f'{numpy_d} != {real_d}'
print(numpy_d, real_d)
if __name__ == '__main__':
np.random.seed(0)
main()

24
examples/error_forward_fix.py
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@@ -1,24 +0,0 @@
import numpy as np
from jax import numpy as jnp
from algorithms.neat.genome.genome import analysis
from algorithms.neat.genome import create_forward_function
error_nodes = np.load('error_nodes.npy')
error_connections = np.load('error_connections.npy')
node_dict, connection_dict = analysis(error_nodes, error_connections, np.array([0, 1]), np.array([2, ]))
print(node_dict, connection_dict, sep='\n')
N = error_nodes.shape[0]
xor_inputs = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
func = create_forward_function(error_nodes, error_connections, N, jnp.array([0, 1]), jnp.array([2, ]),
batch=True, debug=True)
out = func(np.array([1, 0]))
print(error_nodes)
print(error_connections)
print(out)

11
examples/fix_too_large_distance.py
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@@ -1,11 +0,0 @@
import numpy as np
from algorithms.neat.genome import distance
r_nodes = np.load('too_large_distance_r_nodes.npy')
r_connections = np.load('too_large_distance_r_connections.npy')
nodes = np.load('too_large_distance_nodes.npy')
connections = np.load('too_large_distance_connections.npy')
d1 = distance(r_nodes, r_connections, nodes, connections)
d2 = distance(nodes, connections, r_nodes, r_connections)
print(d1, d2)

71
examples/genome_test.py
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@@ -1,71 +0,0 @@
import time
import jax.random
from utils import Configer
from algorithms.neat.genome.genome import *
from algorithms.neat.species import SpeciesController
from algorithms.neat.genome.forward import create_forward_function
from algorithms.neat.genome.mutate import create_mutate_function
if __name__ == '__main__':
N = 10
pop_nodes, pop_connections, input_idx, output_idx = initialize_genomes(10000, N, 2, 1,
default_act=9, default_agg=0)
inputs = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
# forward = create_forward_function(pop_nodes, pop_connections, 5, input_idx, output_idx, batch=True)
nodes, connections = pop_nodes[0], pop_connections[0]
forward = create_forward_function(pop_nodes, pop_connections, N, input_idx, output_idx, batch=True)
out = forward(inputs)
print(out.shape)
print(out)
config = Configer.load_config()
s_c = SpeciesController(config.neat)
s_c.speciate(pop_nodes, pop_connections, 0)
s_c.speciate(pop_nodes, pop_connections, 0)
print(s_c.genome_to_species)
start = time.time()
for i in range(100):
print(i)
s_c.speciate(pop_nodes, pop_connections, i)
print(time.time() - start)
seed = jax.random.PRNGKey(42)
mutate_func = create_mutate_function(config, input_idx, output_idx, batch=False)
print(nodes, connections, sep='\n')
print(*mutate_func(seed, nodes, connections, 100), sep='\n')
randseeds = jax.random.split(seed, 10000)
new_node_keys = jax.random.randint(randseeds[0], minval=0, maxval=10000, shape=(10000,))
batch_mutate_func = create_mutate_function(config, input_idx, output_idx, batch=True)
pop_nodes, pop_connections = batch_mutate_func(randseeds, pop_nodes, pop_connections, new_node_keys)
print(pop_nodes, pop_connections, sep='\n')
start = time.time()
for i in range(100):
print(i)
pop_nodes, pop_connections = batch_mutate_func(randseeds, pop_nodes, pop_connections, new_node_keys)
print(time.time() - start)
print(nodes, connections, sep='\n')
nodes, connections = add_node(6, nodes, connections)
nodes, connections = add_node(7, nodes, connections)
print(nodes, connections, sep='\n')
nodes, connections = add_connection(6, 7, nodes, connections)
nodes, connections = add_connection(0, 7, nodes, connections)
nodes, connections = add_connection(1, 7, nodes, connections)
print(nodes, connections, sep='\n')
nodes, connections = delete_connection(6, 7, nodes, connections)
print(nodes, connections, sep='\n')
nodes, connections = delete_node(6, nodes, connections)
print(nodes, connections, sep='\n')
nodes, connections = delete_node(7, nodes, connections)
print(nodes, connections, sep='\n')

8
examples/xor.py
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@@ -18,7 +18,6 @@ def evaluate(forward_func: Callable) -> List[float]:
"""
outs = forward_func(xor_inputs)
fitnesses = 4 - np.sum((outs - xor_outputs) ** 2, axis=(1, 2))
# print(fitnesses)
return fitnesses.tolist() # returns a list
@@ -29,13 +28,6 @@ def main():
pipeline = Pipeline(config, seed=11323)
pipeline.auto_run(evaluate)
# for _ in range(100):
# s = time.time()
# forward_func = pipeline.ask(batch=True)
# fitnesses = evaluate(forward_func)
# pipeline.tell(fitnesses)
# print(time.time() - s)
if __name__ == '__main__':
main()