tony/tensorneat-mend
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

odify genome for the official release

Browse Source
This commit is contained in:
root
2024-07-10 11:24:11 +08:00
parent 075460f896
commit ee8ec84202
83 changed files with 588 additions and 611 deletions
Download Patch File Download Diff File Expand all files Collapse all files

488
examples/interpret_visualize/genome_sympy.ipynb Normal file
View File

File diff suppressed because one or more lines are too long

37
examples/interpret_visualize/genome_sympy.py Normal file
View File

@@ -0,0 +1,37 @@
import jax, jax.numpy as jnp
from algorithm.neat import *
from algorithm.neat.genome.dense import DenseInitialize
from utils.graph import topological_sort_python
from tensorneat.common import *
if __name__ == "__main__":
genome = DenseInitialize(
num_inputs=3,
num_outputs=1,
max_nodes=50,
max_conns=500,
)
state = genome.setup()
randkey = jax.random.PRNGKey(42)
nodes, conns = genome.initialize(state, randkey)
network = genome.network_dict(state, nodes, conns)
input_idx, output_idx = genome.get_input_idx(), genome.get_output_idx()
res = genome.sympy_func(state, network, sympy_input_transform=lambda x: 999999999*x, sympy_output_transform=SympyStandardSigmoid)
(symbols,
args_symbols,
input_symbols,
nodes_exprs,
output_exprs,
forward_func,) = res
print(symbols)
print(output_exprs[0].subs(args_symbols))
inputs = jnp.zeros(3)
print(forward_func(inputs))

2455
examples/interpret_visualize/graph.svg Normal file
View File

File diff suppressed because it is too large Load Diff
Side by Side

After

Width:  |  Height:  |  Size: 90 KiB

191
examples/interpret_visualize/network.json Normal file
View File

@@ -0,0 +1,191 @@
{
"nodes": {
"0": {
"bias": 0.13710324466228485,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"1": {
"bias": -1.4202250242233276,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"2": {
"bias": -0.4653860926628113,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"3": {
"bias": 0.5835710167884827,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"4": {
"bias": 2.187405824661255,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"5": {
"bias": 0.24963024258613586,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"6": {
"bias": -0.966821551322937,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"7": {
"bias": 0.4452081620693207,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"8": {
"bias": -0.07293166220188141,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"9": {
"bias": -0.1625899225473404,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"10": {
"bias": -0.8576332330703735,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"11": {
"bias": -0.18487468361854553,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"12": {
"bias": 1.4335486888885498,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"13": {
"bias": -0.8690621256828308,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"14": {
"bias": -0.23014676570892334,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"15": {
"bias": 0.7880322337150574,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"16": {
"bias": -0.22258250415325165,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"17": {
"bias": 0.2773352861404419,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"18": {
"bias": -0.40279051661491394,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"19": {
"bias": 1.092000961303711,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"20": {
"bias": -0.4063087999820709,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"21": {
"bias": 0.3895529806613922,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"22": {
"bias": -0.18007506430149078,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"23": {
"bias": -0.8112533092498779,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"24": {
"bias": 0.2946726381778717,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"25": {
"bias": -1.118497371673584,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"26": {
"bias": 1.3674490451812744,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"27": {
"bias": -1.6514816284179688,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"28": {
"bias": 0.9440701603889465,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"29": {
"bias": 1.564852237701416,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
},
"30": {
"bias": -0.5568665266036987,
"res": 1.0,
"agg": "sum",
"act": "sigmoid"
}
},
"conns": {

2455
examples/interpret_visualize/network.svg Normal file
View File

File diff suppressed because it is too large Load Diff
Side by Side

After

Width:  |  Height:  |  Size: 89 KiB

103
examples/interpret_visualize/visualize_genome.ipynb Normal file
View File

File diff suppressed because one or more lines are too long

13
examples/interpret_visualize/visualize_genome.py Normal file
View File

@@ -0,0 +1,13 @@
import networkx as nx
import matplotlib.pyplot as plt
# 创建一个空白的有向图
G = nx.DiGraph()
# 添加边
G.add_edge('A', 'B')
G.add_edge('A', 'C')
G.add_edge('B', 'C')
G.add_edge('C', 'D')
# 绘制有向图