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Merge pull request #10 from AlexanderJYu/quadrotor_notebook
planarquadrotor notebook
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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 1, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"%load_ext autoreload\n", | ||
"%autoreload 2" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 2, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"import jax.numpy as jnp\n", | ||
"import numpy as np\n", | ||
"import matplotlib.pyplot as plt\n", | ||
"import jax\n", | ||
"from jax import lax\n", | ||
"from deluca.envs import PlanarQuadrotor\n", | ||
"from deluca.agents import ILQR\n" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 3, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"name": "stderr", | ||
"output_type": "stream", | ||
"text": [ | ||
"W1209 02:34:56.329764 4343987648 xla_bridge.py:131] No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n" | ||
] | ||
}, | ||
{ | ||
"name": "stdout", | ||
"output_type": "stream", | ||
"text": [ | ||
"c = 374122.0319286693\n", | ||
"cC = 3861.0703039268997\n", | ||
"iLQR : t = 2, c = 3861.070304\n", | ||
"c = 3861.0703039268997\n", | ||
"cC = 219.25601885420733\n", | ||
"iLQR : t = 3, c = 219.256019\n", | ||
"c = 219.25601885420733\n", | ||
"cC = 69.37626506797743\n", | ||
"iLQR : t = 4, c = 69.376265\n", | ||
"c = 69.37626506797743\n", | ||
"cC = 54.80947011412863\n", | ||
"iLQR : t = 5, c = 54.809470\n", | ||
"c = 54.80947011412863\n", | ||
"cC = 52.380773285980005\n", | ||
"iLQR : t = 6, c = 52.380773\n", | ||
"c = 52.380773285980005\n", | ||
"cC = 51.873685827995054\n", | ||
"iLQR : t = 7, c = 51.873686\n", | ||
"c = 51.873685827995054\n", | ||
"cC = 52.30835658833143\n", | ||
"iLQR : t = 8, c = 51.873686\n", | ||
"c = 51.873685827995054\n", | ||
"cC = 51.818456885242966\n", | ||
"iLQR : t = 9, c = 51.818457\n", | ||
"c = 51.818456885242966\n", | ||
"cC = 52.42826316876129\n", | ||
"iLQR : t = 10, c = 51.818457\n" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"agent = ILQR()\n", | ||
"agent.train(PlanarQuadrotor(placebo=0), 10)" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 4, | ||
"metadata": { | ||
"pycharm": { | ||
"name": "#%%\n" | ||
} | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"def loop(context, x):\n", | ||
" env, agent = context\n", | ||
" control = agent(env.state)\n", | ||
" _, reward, _, _ = env.step(control)\n", | ||
" return (env, agent), reward" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 7, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"name": "stdout", | ||
"output_type": "stream", | ||
"text": [ | ||
"[1. 1. 0. 0. 0. 0.]\n", | ||
"reward_forloop = 51.818456885242966\n" | ||
] | ||
} | ||
], | ||
"source": [ | ||
" # for loop version\n", | ||
"T = 100\n", | ||
"env = PlanarQuadrotor(placebo=0)\n", | ||
"print(env.reset())\n", | ||
"reward = 0\n", | ||
"for i in range(T):\n", | ||
" (env, agent), r = loop((env, agent), 0)\n", | ||
" reward += r\n", | ||
"reward_forloop = reward\n", | ||
"print('reward_forloop = ' + str(reward_forloop))" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 8, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"name": "stdout", | ||
"output_type": "stream", | ||
"text": [ | ||
"[1. 1. 0. 0. 0. 0.]\n", | ||
"reward_scan sum = 51.81845688524296\n" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"# scan version\n", | ||
"# env = PlanarQuadrotor(placebo=0)\n", | ||
"agent.reset()\n", | ||
"print(env.reset())\n", | ||
"xs = jnp.array(jnp.arange(T))\n", | ||
"_,reward_scan = lax.scan(loop, (env, agent), xs)\n", | ||
"\n", | ||
"# correctness test\n", | ||
"print('reward_scan sum = ' + str(jnp.sum(reward_scan)))" | ||
] | ||
} | ||
], | ||
"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": "3.7.5" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 1 | ||
} |