generate_ann.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from neat import NEAT\n",
    "from phenotype import genome_to_network_params\n",
    "import jax.numpy as jnp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "neat = NEAT(5, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "pop = neat.create_initial_population(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'node_id': 6, 'node_type': 'output'}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neat.population[0].__dict__ ['nodes'][6].__dict__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'weights': Array([[0., 0., 0.],\n",
       "        [0., 0., 0.],\n",
       "        [0., 0., 0.],\n",
       "        [0., 0., 0.],\n",
       "        [0., 0., 0.]], dtype=float32)}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genome_to_network_params(neat.population[3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "neat.evolve()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<genotype.Genome at 0x7f41de2324d0>,\n",
       " <genotype.Genome at 0x7f41de24c910>,\n",
       " <genotype.Genome at 0x7f41de24d210>,\n",
       " <genotype.Genome at 0x7f41de24d210>,\n",
       " <genotype.Genome at 0x7f41de24d210>,\n",
       " <genotype.Genome at 0x7f41de24db10>,\n",
       " <genotype.Genome at 0x7f41de24d210>,\n",
       " <genotype.Genome at 0x7f41de24d210>,\n",
       " <genotype.Genome at 0x7f41de2324d0>,\n",
       " <genotype.Genome at 0x7f41de232dd0>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neat.population"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<genotype.NodeGene at 0x7f41de231f30>,\n",
       " <genotype.NodeGene at 0x7f41de231270>,\n",
       " <genotype.NodeGene at 0x7f41de231ed0>,\n",
       " <genotype.NodeGene at 0x7f41de2322f0>,\n",
       " <genotype.NodeGene at 0x7f41de232350>,\n",
       " <genotype.NodeGene at 0x7f41de231fc0>,\n",
       " <genotype.NodeGene at 0x7f41de232410>,\n",
       " <genotype.NodeGene at 0x7f41de232470>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neat.population[0].nodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "neat.population[4].nodes[0].node_type\n",
    "genome = neat.population[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'input'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genome.nodes[0].node_type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1"
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 },
 "nbformat": 4,
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}