Files
tensorneat-mend/tensorneat/tmp.ipynb
wls2002 b3e442c688 add sympy support; which can transfer your network into sympy expression;
add visualize in genome;
add related tests.
2024-06-12 21:36:35 +08:00

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"data": {
"text/plain": "<algorithm.neat.genome.default.DefaultGenome at 0x7f6709872650>"
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"source": [
"import jax, jax.numpy as jnp\n",
"from algorithm.neat import *\n",
"from utils import Act, Agg\n",
"genome = DefaultGenome(\n",
" num_inputs=27,\n",
" num_outputs=8,\n",
" max_nodes=100,\n",
" max_conns=200,\n",
" node_gene=DefaultNodeGene(\n",
" activation_options=(Act.tanh,),\n",
" activation_default=Act.tanh,\n",
" ),\n",
" output_transform=Act.tanh,\n",
")\n",
"state = genome.setup()\n",
"genome"
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"execution_count": 4,
"outputs": [],
"source": [
"state = state.register(data=jnp.zeros((1, 27)))\n",
"# try to save the genome object\n",
"import pickle\n",
"\n",
"with open('genome.pkl', 'wb') as f:\n",
" genome.__dict__[\"state\"] = state\n",
" pickle.dump(genome, f)"
],
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"cell_type": "code",
"execution_count": 13,
"outputs": [],
"source": [
"# try to load the genome object\n",
"with open('genome.pkl', 'rb') as f:\n",
" genome = pickle.load(f)\n",
" state = genome.state\n",
" del genome.__dict__[\"state\"]"
],
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