add sympy support; which can transfer your network into sympy expression;
add visualize in genome; add related tests.
This commit is contained in:
wls2002
@@ -2,189 +2,110 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 22,
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"id": "initial_id",
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"metadata": {
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"collapsed": true,
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"ExecuteTime": {
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"end_time": "2024-06-06T11:55:39.434327400Z",
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"start_time": "2024-06-06T11:55:39.361327400Z"
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}
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},
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"execution_count": 1,
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"outputs": [
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{
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"data": {
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"text/plain": "Array([[[2, 4],\n [1, 3]],\n\n [[4, 3],\n [2, 1]],\n\n [[3, 1],\n [4, 2]],\n\n [[1, 2],\n [3, 4]],\n\n [[2, 4],\n [1, 3]],\n\n [[4, 3],\n [2, 1]],\n\n [[3, 1],\n [4, 2]],\n\n [[1, 2],\n [3, 4]]], dtype=int32)"
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"text/plain": "<algorithm.neat.genome.default.DefaultGenome at 0x7f6709872650>"
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},
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"execution_count": 22,
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"execution_count": 1,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import jax, jax.numpy as jnp\n",
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"a = jnp.array([\n",
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" [1, 2],\n",
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" [3, 4]\n",
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"])\n",
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"def rot_boards(board):\n",
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" def rot(a, _):\n",
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" a = jnp.rot90(a)\n",
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" return a, a # carry, y\n",
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" \n",
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" _, boards = jax.lax.scan(rot, board, jnp.arange(4, dtype=jnp.int32))\n",
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" return boards\n",
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"a1 = rot_boards(a)\n",
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"a2 = rot_boards(a)\n",
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"\n",
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"a = jnp.concatenate([a1, a2], axis=0)\n",
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"a"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"outputs": [
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{
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"data": {
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"text/plain": "Array([[2, 4, 1, 3],\n [4, 3, 2, 1],\n [3, 1, 4, 2],\n [1, 2, 3, 4],\n [2, 4, 1, 3],\n [4, 3, 2, 1],\n [3, 1, 4, 2],\n [1, 2, 3, 4]], dtype=int32)"
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},
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"execution_count": 21,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"a = a.reshape(8, -1)\n",
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"a"
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"from algorithm.neat import *\n",
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"from utils import Act, Agg\n",
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"genome = DefaultGenome(\n",
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" num_inputs=27,\n",
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" num_outputs=8,\n",
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" max_nodes=100,\n",
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" max_conns=200,\n",
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" node_gene=DefaultNodeGene(\n",
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" activation_options=(Act.tanh,),\n",
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" activation_default=Act.tanh,\n",
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" ),\n",
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" output_transform=Act.tanh,\n",
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")\n",
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"state = genome.setup()\n",
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"genome"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2024-06-06T11:55:31.121054800Z",
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"start_time": "2024-06-06T11:55:31.075517200Z"
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"end_time": "2024-06-09T12:08:22.569123400Z",
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"start_time": "2024-06-09T12:08:19.331863800Z"
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}
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},
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"id": "639cdecea840351d"
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"id": "b2b214a5454c4814"
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"outputs": [],
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"source": [
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"state = state.register(data=jnp.zeros((1, 27)))\n",
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"# try to save the genome object\n",
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"import pickle\n",
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"\n",
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"with open('genome.pkl', 'wb') as f:\n",
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" genome.__dict__[\"state\"] = state\n",
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" pickle.dump(genome, f)"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2024-06-09T12:09:01.943445900Z",
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"start_time": "2024-06-09T12:09:01.919416Z"
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}
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},
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"id": "28348dfc458e8473"
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"outputs": [],
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"source": [
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"action = [\"up\", \"right\", \"down\", \"left\"]\n",
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"lr_flip_action = [\"up\", \"left\", \"down\", \"right\"]\n",
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"def action_rot90(li):\n",
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" first = li[0]\n",
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" return li[1:] + [first]\n",
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"\n",
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"a = a\n",
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"rl_flip_a = jnp.fliplr(a)"
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"# try to load the genome object\n",
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"with open('genome.pkl', 'rb') as f:\n",
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" genome = pickle.load(f)\n",
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" state = genome.state\n",
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" del genome.__dict__[\"state\"]"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2024-06-06T11:22:36.417287600Z",
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"start_time": "2024-06-06T11:22:36.414285500Z"
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"end_time": "2024-06-09T12:10:28.621539400Z",
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"start_time": "2024-06-09T12:10:28.612540100Z"
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}
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},
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"id": "92b75cd0e870a28c"
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"id": "c91be9fe3d2b5d5d"
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[[1 2]\n",
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" [3 4]] ['up', 'right', 'down', 'left']\n",
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"[[2 1]\n",
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" [4 3]] ['up', 'left', 'down', 'right']\n",
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"[[2 4]\n",
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" [1 3]] ['right', 'down', 'left', 'up']\n",
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"[[1 3]\n",
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" [2 4]] ['left', 'down', 'right', 'up']\n",
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"[[4 3]\n",
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" [2 1]] ['down', 'left', 'up', 'right']\n",
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"[[3 4]\n",
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" [1 2]] ['down', 'right', 'up', 'left']\n",
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"[[3 1]\n",
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" [4 2]] ['left', 'up', 'right', 'down']\n",
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"[[4 2]\n",
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" [3 1]] ['right', 'up', 'left', 'down']\n"
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]
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}
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],
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"source": [
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"for i in range(4):\n",
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" print(a, action)\n",
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" print(rl_flip_a, lr_flip_action)\n",
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" a = jnp.rot90(a)\n",
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" rl_flip_a = jnp.rot90(rl_flip_a)\n",
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" action = action_rot90(action)\n",
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" lr_flip_action = action_rot90(lr_flip_action)"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2024-06-06T11:22:36.919614600Z",
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"start_time": "2024-06-06T11:22:36.860704600Z"
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}
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},
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"id": "55e802e0dbcc9c7f"
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 15,
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"outputs": [
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{
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"data": {
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"text/plain": "Array([[4, 3],\n [2, 1]], dtype=int32)"
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"text/plain": "State ({'data': Array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]], dtype=float32)})"
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},
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"execution_count": 6,
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"jnp.rot90(a, k=2)"
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"state"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2024-06-06T11:12:48.186719Z",
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"start_time": "2024-06-06T11:12:48.151161900Z"
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"end_time": "2024-06-09T12:10:34.103124Z",
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"start_time": "2024-06-09T12:10:34.096124300Z"
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}
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},
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"id": "16f8de3cadaa257a"
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"outputs": [
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{
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"data": {
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"text/plain": "Array([[2, 1],\n [4, 3]], dtype=int32)"
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# flip left-right\n",
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"jnp.fliplr(a)"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2024-06-06T11:14:28.668195300Z",
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"start_time": "2024-06-06T11:14:28.631570500Z"
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}
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},
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"id": "1fffa4e597ab5732"
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"id": "6852e4e58b81dd9"
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},
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{
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"cell_type": "code",
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@@ -194,7 +115,7 @@
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"metadata": {
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"collapsed": false
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},
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"id": "ca53c916dcff12ae"
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"id": "97a50322218a0427"
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}
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],
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"metadata": {
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