262 lines
8.2 KiB
Plaintext
262 lines
8.2 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"outputs": [],
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"source": [
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"import jax, jax.numpy as jnp\n",
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"\n",
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"from algorithm.neat import *\n",
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"from algorithm.neat.genome.advance import AdvanceInitialize\n",
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"from algorithm.neat.gene.node.default_without_response import NodeGeneWithoutResponse\n",
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"from utils.graph import topological_sort_python\n",
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"from utils import Act, Agg\n",
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"\n",
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"import numpy as np"
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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": "2024-06-12T21:48:58.065855900Z",
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"start_time": "2024-06-12T21:48:57.292767Z"
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}
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},
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"id": "9531a569d9ecf774"
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"outputs": [],
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"source": [
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"genome = AdvanceInitialize(\n",
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" num_inputs=3,\n",
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" num_outputs=3,\n",
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" hidden_cnt=2,\n",
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" max_nodes=50,\n",
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" max_conns=500,\n",
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" node_gene=NodeGeneWithoutResponse(\n",
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" # activation_default=Act.tanh,\n",
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" aggregation_default=Agg.sum,\n",
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" # activation_options=(Act.tanh,),\n",
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" aggregation_options=(Agg.sum,),\n",
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" ),\n",
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" output_transform=jnp.tanh,\n",
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")\n",
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"\n",
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"state = genome.setup()\n",
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"\n",
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"randkey = jax.random.PRNGKey(42)\n",
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"nodes, conns = genome.initialize(state, randkey)\n",
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"\n",
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"network = genome.network_dict(state, nodes, conns)"
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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": "2024-06-12T21:49:03.858545Z",
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"start_time": "2024-06-12T21:48:58.071859800Z"
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}
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},
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"id": "4013c9f9d5472eb7"
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"outputs": [
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{
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"data": {
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"text/plain": "{'nodes': {0: {'idx': 0,\n 'bias': array(0.22059791, dtype=float32),\n 'agg': 'sum',\n 'act': 'sigmoid'},\n 1: {'idx': 1,\n 'bias': array(0.7715081, dtype=float32),\n 'agg': 'sum',\n 'act': 'sigmoid'},\n 2: {'idx': 2,\n 'bias': array(1.1184921, dtype=float32),\n 'agg': 'sum',\n 'act': 'sigmoid'},\n 3: {'idx': 3,\n 'bias': array(0.6967973, dtype=float32),\n 'agg': 'sum',\n 'act': 'sigmoid'},\n 4: {'idx': 4,\n 'bias': array(0.85948837, dtype=float32),\n 'agg': 'sum',\n 'act': 'sigmoid'},\n 5: {'idx': 5,\n 'bias': array(0.19332138, dtype=float32),\n 'agg': 'sum',\n 'act': 'sigmoid'},\n 6: {'idx': 6,\n 'bias': array(-0.31763914, dtype=float32),\n 'agg': 'sum',\n 'act': 'sigmoid'},\n 7: {'idx': 7,\n 'bias': array(0.05656302, dtype=float32),\n 'agg': 'sum',\n 'act': 'sigmoid'}},\n 'conns': {(0, 6): {'in': 0,\n 'out': 6,\n 'weight': array(1.6676894, dtype=float32)},\n (0, 7): {'in': 0, 'out': 7, 'weight': array(-0.05250553, dtype=float32)},\n (1, 6): {'in': 1, 'out': 6, 'weight': array(0.10137014, dtype=float32)},\n (1, 7): {'in': 1, 'out': 7, 'weight': array(-0.12093307, dtype=float32)},\n (2, 6): {'in': 2, 'out': 6, 'weight': array(-1.8677292, dtype=float32)},\n (2, 7): {'in': 2, 'out': 7, 'weight': array(-0.4195783, dtype=float32)},\n (6, 3): {'in': 6, 'out': 3, 'weight': array(1.2615877, dtype=float32)},\n (6, 4): {'in': 6, 'out': 4, 'weight': array(-0.27593768, dtype=float32)},\n (6, 5): {'in': 6, 'out': 5, 'weight': array(-0.5819819, dtype=float32)},\n (7, 3): {'in': 7, 'out': 3, 'weight': array(0.59301573, dtype=float32)},\n (7, 4): {'in': 7, 'out': 4, 'weight': array(0.19493186, dtype=float32)},\n (7, 5): {'in': 7, 'out': 5, 'weight': array(0.18183969, dtype=float32)}}}"
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},
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"execution_count": 3,
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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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"network"
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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": "2024-06-12T21:49:03.873543600Z",
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"start_time": "2024-06-12T21:49:03.867543Z"
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}
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},
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"id": "188006cebb04847"
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"outputs": [],
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"source": [
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"import sympy as sp\n",
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"\n",
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"# symbols, args_symbols, input_symbols, nodes_exprs, output_exprs, forward_func = genome.sympy_func(state, network)\n",
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"symbols, args_symbols, input_symbols, nodes_exprs, output_exprs, jax_forward_func = genome.sympy_func(state, network, sympy_output_transform=sp.tanh)\n",
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"symbols, args_symbols, input_symbols, nodes_exprs, output_exprs, np_forward_func = genome.sympy_func(state, network, sympy_output_transform=sp.tanh, backend='numpy')\n"
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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": "2024-06-12T21:50:37.527882500Z",
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"start_time": "2024-06-12T21:50:37.518559400Z"
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}
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},
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"id": "addea793fc002900"
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"outputs": [
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{
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"data": {
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"text/plain": "(array([1.0719017 , 0.09353136, 0.22664611], dtype=float32), dtype('float32'))"
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},
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"execution_count": 12,
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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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"random_inputs = np.random.randn(3).astype(np.float32)\n",
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"random_inputs, random_inputs.dtype"
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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": "2024-06-12T21:50:38.178769100Z",
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"start_time": "2024-06-12T21:50:38.155744Z"
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}
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},
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"id": "3aa7c874f3a5743f"
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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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{
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"data": {
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"text/plain": "Array([ 0.9743453, 0.5764604, -0.3080282], dtype=float32, weak_type=True)"
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},
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"execution_count": 13,
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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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"transformed = genome.transform(state, nodes, conns)\n",
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"res = genome.forward(state, transformed, random_inputs)\n",
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"res"
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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": "2024-06-12T21:50:48.747287900Z",
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"start_time": "2024-06-12T21:50:48.560675400Z"
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}
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},
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"id": "fe3449a5bc688bc3"
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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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"data": {
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"text/plain": "(array([ 0.9743453, 0.5764604, -0.3080282], dtype=float32),\n array([ 0.9743453 , 0.57646036, -0.3080282 ], dtype=float32),\n array([ 0.9743453, 0.5764604, -0.3080282], dtype=float32))"
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},
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"execution_count": 14,
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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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"res1 = np.array(jax_forward_func(random_inputs), dtype=np.float32)\n",
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"res2 = np.array(np_forward_func(random_inputs), dtype=np.float32)\n",
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"res = np.array(genome.forward(state, transformed, random_inputs))\n",
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"res1, res2, res"
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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": "2024-06-12T21:51:15.098948600Z",
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"start_time": "2024-06-12T21:51:14.908948500Z"
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}
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},
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"id": "a874d434509f1092"
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},
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{
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"cell_type": "code",
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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([ True, True, True]), array([ True, False, True]))"
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},
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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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"res1 == res, res2 == res"
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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": "2024-06-12T21:51:25.857465200Z",
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"start_time": "2024-06-12T21:51:25.851465300Z"
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}
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},
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"id": "d226e5bd6e2d44d6"
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},
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{
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"cell_type": "code",
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"execution_count": 23,
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"outputs": [
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{
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"data": {
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"text/plain": "array([False, False, True])"
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},
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"execution_count": 23,
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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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"np.floor(res1 * 10000000) / 10000000 == np.floor(res2 * 10000000) / 10000000"
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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": "2024-06-12T21:00:19.851215800Z",
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"start_time": "2024-06-12T21:00:19.836443700Z"
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}
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},
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"id": "2a36ce6afc59ee8a"
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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