visu.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "from omegaconf import OmegaConf\n",
    "\n",
    "\n",
    "dir = Path(\"/workspace/src/output/results_old/walker2d_uni\")\n",
    "\n",
    "# # Create directory ablation_1/ if it does not exist\n",
    "# ablation_dir = dir / \"ablation_1\"\n",
    "# ablation_dir.mkdir(exist_ok=True)\n",
    "\n",
    "# # Create directory ablation_2/ if it does not exist\n",
    "# ablation_dir = dir / \"ablation_2\"\n",
    "# ablation_dir.mkdir(exist_ok=True)\n",
    "\n",
    "# # Create directory ablation_3/ if it does not exist\n",
    "# ablation_dir = dir / \"ablation_3\"\n",
    "# ablation_dir.mkdir(exist_ok=True)\n",
    "\n",
    "dir_iter = list(dir.iterdir())\n",
    "for algo_dir in dir_iter:\n",
    "\tif not algo_dir.is_dir() or algo_dir.name != \"dcg_me\":\n",
    "\t\tcontinue\n",
    "\talgo_dir_iter = list(algo_dir.iterdir())\n",
    "\tfor run_dir in algo_dir_iter:\n",
    "\t\tif not run_dir.is_dir():\n",
    "\t\t\tcontinue\n",
    "\t\tconfig = OmegaConf.load(run_dir / \".hydra\" / \"config.yaml\")\n",
    "\t\t(run_dir / \".hydra\" / \"config.yaml\").rename(run_dir / \".hydra\" / \"config.yaml.old\")\n",
    "\t\tif \"dc_actor\" not in config.algo:\n",
    "\t\t\tconfig.algo.dc_actor = True\n",
    "\t\tif config.algo.name == \"dcg_me\" and config.algo.dc_actor == False and config.algo.ai_batch_size == 0:\n",
    "\t\t\t# Ablation Actor\n",
    "\t\t\tconfig.algo.name = \"ablation_1\"\n",
    "\t\t\tOmegaConf.save(config=config, f=run_dir / \".hydra\" / \"config.yaml\")\n",
    "\t\t\tablation_dir = dir / \"ablation_1\"\n",
    "\t\t\tablation_dir.mkdir(exist_ok=True)\n",
    "\t\t\trun_dir.rename(ablation_dir / run_dir.name)\n",
    "\t\telif config.algo.name == \"dcg_me\" and config.algo.actor_batch_size == 0 and config.algo.qpg_batch_size == 128 and config.algo.ai_batch_size == 0:\n",
    "\t\t\t# Ablation AI\n",
    "\t\t\tconfig.algo.name = \"ablation_2\"\n",
    "\t\t\tOmegaConf.save(config=config, f=run_dir / \".hydra\" / \"config.yaml\")\n",
    "\t\t\tablation_dir = dir / \"ablation_2\"\n",
    "\t\t\tablation_dir.mkdir(exist_ok=True)\n",
    "\t\t\trun_dir.rename(ablation_dir / run_dir.name)\n",
    "\t\telif config.algo.name == \"dcg_me\" and config.algo.actor_batch_size == 64 and config.algo.qpg_batch_size == 128 and config.algo.ai_batch_size == 0:\n",
    "\t\t\t# DCG-MAP-Elites\n",
    "\t\t\tconfig.algo.name = \"ablation_3\"\n",
    "\t\t\tOmegaConf.save(config=config, f=run_dir / \".hydra\" / \"config.yaml\")\n",
    "\t\t\tablation_dir = dir / \"ablation_3\"\n",
    "\t\t\tablation_dir.mkdir(exist_ok=True)\n",
    "\t\t\trun_dir.rename(ablation_dir / run_dir.name)\n",
    "\t\telif config.algo.name == \"dcg_me\" and config.algo.dc_actor == True and config.algo.actor_batch_size == 0 and config.algo.qpg_batch_size == 64 and config.algo.ai_batch_size == 64:\n",
    "\t\t\t# DCRL-MAP-Elites\n",
    "\t\t\tOmegaConf.save(config=config, f=run_dir / \".hydra\" / \"config.yaml\")\n",
    "\t\telse:\n",
    "\t\t\traise ValueError"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: '/project/output/results/humanoid_uni/dcg_me/2023-10-12_070304_680643/.hydra/config.yaml'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[1], line 16\u001b[0m\n\u001b[1;32m     12\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mutils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m get_env, get_config, get_repertoire\n\u001b[1;32m     15\u001b[0m run_dir \u001b[38;5;241m=\u001b[39m Path(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m/project/output/results/humanoid_uni/dcg_me/2023-10-12_070304_680643\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 16\u001b[0m config \u001b[38;5;241m=\u001b[39m \u001b[43mget_config\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrun_dir\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/workspace/src/utils.py:121\u001b[0m, in \u001b[0;36mget_config\u001b[0;34m(run_dir)\u001b[0m\n\u001b[1;32m    120\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_config\u001b[39m(run_dir):\n\u001b[0;32m--> 121\u001b[0m     config \u001b[38;5;241m=\u001b[39m \u001b[43mOmegaConf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrun_dir\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m.hydra\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mconfig.yaml\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m    122\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m config\n",
      "File \u001b[0;32m/venv/lib/python3.10/site-packages/omegaconf/omegaconf.py:189\u001b[0m, in \u001b[0;36mOmegaConf.load\u001b[0;34m(file_)\u001b[0m\n\u001b[1;32m    186\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01m_utils\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m get_yaml_loader\n\u001b[1;32m    188\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(file_, (\u001b[38;5;28mstr\u001b[39m, pathlib\u001b[38;5;241m.\u001b[39mPath)):\n\u001b[0;32m--> 189\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mio\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mos\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mabspath\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfile_\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mr\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mutf-8\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m f:\n\u001b[1;32m    190\u001b[0m         obj \u001b[38;5;241m=\u001b[39m yaml\u001b[38;5;241m.\u001b[39mload(f, Loader\u001b[38;5;241m=\u001b[39mget_yaml_loader())\n\u001b[1;32m    191\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mgetattr\u001b[39m(file_, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mread\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m):\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/project/output/results/humanoid_uni/dcg_me/2023-10-12_070304_680643/.hydra/config.yaml'"
     ]
    }
   ],
   "source": [
    "import functools\n",
    "from pathlib import Path\n",
    "\n",
    "import jax\n",
    "import jax.numpy as jnp\n",
    "\n",
    "from qdax.environments import behavior_descriptor_extractor\n",
    "from qdax.core.neuroevolution.buffers.buffer import QDTransition\n",
    "from qdax.core.neuroevolution.networks.networks import MLP\n",
    "from qdax.tasks.brax_envs import reset_based_scoring_function_brax_envs as scoring_function\n",
    "\n",
    "from utils import get_env, get_config, get_repertoire\n",
    "\n",
    "\n",
    "run_dir = Path(\"/project/output/results/humanoid_uni/dcg_me/2023-10-12_070304_680643\")\n",
    "config = get_config(run_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "repertoire = get_repertoire(run_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Init a random key\n",
    "random_key = jax.random.PRNGKey(config.seed)\n",
    "\n",
    "# Init environment\n",
    "env = get_env(config)\n",
    "reset_fn = jax.jit(env.reset)\n",
    "\n",
    "# Init policy network\n",
    "policy_layer_sizes = config.policy_hidden_layer_sizes + (env.action_size,)\n",
    "policy_network = MLP(\n",
    "    layer_sizes=policy_layer_sizes,\n",
    "    kernel_init=jax.nn.initializers.lecun_uniform(),\n",
    "    final_activation=jnp.tanh,\n",
    ")\n",
    "\n",
    "# Define the fonction to play a step with the policy in the environment\n",
    "def play_step_fn(env_state, policy_params, random_key):\n",
    "    actions = policy_network.apply(policy_params, env_state.obs)\n",
    "    state_desc = env_state.info[\"state_descriptor\"]\n",
    "    next_state = env.step(env_state, actions)\n",
    "\n",
    "    transition = QDTransition(\n",
    "        obs=env_state.obs,\n",
    "        next_obs=next_state.obs,\n",
    "        rewards=next_state.reward,\n",
    "        dones=next_state.done,\n",
    "        truncations=next_state.info[\"truncation\"],\n",
    "        actions=actions,\n",
    "        state_desc=state_desc,\n",
    "        next_state_desc=next_state.info[\"state_descriptor\"],\n",
    "        desc=jnp.zeros(env.behavior_descriptor_length,) * jnp.nan,\n",
    "        desc_prime=jnp.zeros(env.behavior_descriptor_length,) * jnp.nan,\n",
    "    )\n",
    "\n",
    "    return next_state, policy_params, random_key, transition\n",
    "\n",
    "# Prepare the scoring function\n",
    "bd_extraction_fn = behavior_descriptor_extractor[config.env.name]\n",
    "scoring_fn = functools.partial(\n",
    "    scoring_function,\n",
    "    episode_length=config.env.episode_length,\n",
    "    play_reset_fn=reset_fn,\n",
    "    play_step_fn=play_step_fn,\n",
    "    behavior_descriptor_extractor=bd_extraction_fn,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "NUM_EVALUATION = 4\n",
    "random_keys = jax.random.split(random_key, NUM_EVALUATION)\n",
    "fitnesses, descriptors, extra_scores, random_keys = jax.vmap(scoring_fn, in_axes=(None, 0))(repertoire.genotypes, random_keys)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import functools\n",
    "import pickle\n",
    "\n",
    "import jax\n",
    "import jax.numpy as jnp\n",
    "from flax import serialization\n",
    "\n",
    "from qdax import environments\n",
    "from qdax.tasks.brax_envs import reset_based_scoring_function_brax_envs as scoring_function\n",
    "from qdax.tasks.brax_envs import reset_based_scoring_actor_dc_function_brax_envs as scoring_actor_dc_function\n",
    "from qdax.core.neuroevolution.buffers.buffer import QDTransition\n",
    "from qdax.core.neuroevolution.networks.networks import MLP, MLPDC\n",
    "\n",
    "from brax.v1.io import html\n",
    "from IPython.display import HTML\n",
    "from omegaconf import OmegaConf\n",
    "from utils import get_env, get_config"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load experiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "\n",
    "run_dir = Path(\"/project/output/results/ant_omni/dcg_me/2023-10-11_075315_268825\")\n",
    "config = get_config(run_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Init a random key\n",
    "random_key = jax.random.PRNGKey(config.seed)\n",
    "\n",
    "# Init environment\n",
    "env = get_env(config)\n",
    "reset_fn = jax.jit(env.reset)\n",
    "step_fn = jax.jit(env.step)\n",
    "\n",
    "# Init policy network\n",
    "policy_layer_sizes = config.policy_hidden_layer_sizes + (env.action_size,)\n",
    "policy_network = MLP(\n",
    "    layer_sizes=policy_layer_sizes,\n",
    "    kernel_init=jax.nn.initializers.lecun_uniform(),\n",
    "    final_activation=jnp.tanh,\n",
    ")\n",
    "actor_dc_network = MLPDC(\n",
    "    layer_sizes=policy_layer_sizes,\n",
    "    kernel_init=jax.nn.initializers.lecun_uniform(),\n",
    "    final_activation=jnp.tanh,\n",
    ")\n",
    "\n",
    "def play_step_fn(env_state, policy_params, random_key):\n",
    "    actions = policy_network.apply(policy_params, env_state.obs)\n",
    "    state_desc = env_state.info[\"state_descriptor\"]\n",
    "    next_state = env.step(env_state, actions)\n",
    "\n",
    "    transition = QDTransition(\n",
    "        obs=env_state.obs,\n",
    "        next_obs=next_state.obs,\n",
    "        rewards=next_state.reward,\n",
    "        dones=next_state.done,\n",
    "        truncations=next_state.info[\"truncation\"],\n",
    "        actions=actions,\n",
    "        state_desc=state_desc,\n",
    "        next_state_desc=next_state.info[\"state_descriptor\"],\n",
    "        desc=jnp.zeros(env.behavior_descriptor_length,) * jnp.nan,\n",
    "        desc_prime=jnp.zeros(env.behavior_descriptor_length,) * jnp.nan,\n",
    "    )\n",
    "\n",
    "    return next_state, policy_params, random_key, transition\n",
    "\n",
    "# Prepare the scoring function\n",
    "bd_extraction_fn = environments.behavior_descriptor_extractor[config.env.name]\n",
    "scoring_fn = functools.partial(\n",
    "    scoring_function,\n",
    "    episode_length=config.env.episode_length,\n",
    "    play_reset_fn=reset_fn,\n",
    "    play_step_fn=play_step_fn,\n",
    "    behavior_descriptor_extractor=bd_extraction_fn,\n",
    ")\n",
    "\n",
    "def play_step_actor_dc_fn(env_state, actor_dc_params, desc, random_key):\n",
    "    actions = actor_dc_network.apply(actor_dc_params, env_state.obs, desc/config.env.max_bd)\n",
    "    state_desc = env_state.info[\"state_descriptor\"]\n",
    "    next_state = env.step(env_state, actions)\n",
    "\n",
    "    transition = QDTransition(\n",
    "        obs=env_state.obs,\n",
    "        next_obs=next_state.obs,\n",
    "        rewards=next_state.reward,\n",
    "        dones=next_state.done,\n",
    "        truncations=next_state.info[\"truncation\"],\n",
    "        actions=actions,\n",
    "        state_desc=state_desc,\n",
    "        next_state_desc=next_state.info[\"state_descriptor\"],\n",
    "        desc=jnp.zeros(env.behavior_descriptor_length,) * jnp.nan,\n",
    "        desc_prime=desc/config.env.max_bd,\n",
    "    )\n",
    "\n",
    "    return next_state, actor_dc_params, desc, random_key, transition\n",
    "\n",
    "# Prepare the scoring function\n",
    "scoring_actor_dc_fn = jax.jit(functools.partial(\n",
    "    scoring_actor_dc_function,\n",
    "    episode_length=config.env.episode_length,\n",
    "    play_reset_fn=reset_fn,\n",
    "    play_step_actor_dc_fn=play_step_actor_dc_fn,\n",
    "    behavior_descriptor_extractor=bd_extraction_fn,\n",
    "))\n",
    "\n",
    "# Build the reconstruction function\n",
    "fake_obs = jnp.zeros(shape=(env.observation_size,))\n",
    "fake_desc = jnp.zeros(shape=(env.behavior_descriptor_length,))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load repertoire"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from jax.flatten_util import ravel_pytree\n",
    "from qdax.core.containers.mapelites_repertoire import MapElitesRepertoire\n",
    "\n",
    "\n",
    "random_key, random_subkey = jax.random.split(random_key)\n",
    "fake_params = policy_network.init(random_subkey, fake_obs)\n",
    "\n",
    "_, reconstruction_fn = ravel_pytree(fake_params)\n",
    "\n",
    "# Build the repertoire\n",
    "repertoire = MapElitesRepertoire.load(reconstruction_fn=reconstruction_fn, path=str(run_dir) + \"/repertoire/\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rollout"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Policy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode length: 250/250\n",
      "Fitness: 849.4724731445312\n",
      "Desired descriptor: [30 30]\n",
      "Repertoire descriptor: [28.760014 29.178423]\n",
      "Observed descriptor: [29.251493 27.96182 ]\n"
     ]
    }
   ],
   "source": [
    "descriptor_desired = jnp.array([30, 30])\n",
    "index = jnp.argmin(jnp.linalg.norm(repertoire.descriptors - descriptor_desired, axis=1))\n",
    "descriptor_repertoire = repertoire.descriptors[index]\n",
    "policy_params = jax.tree_util.tree_map(lambda x: x[index], repertoire.genotypes)\n",
    "\n",
    "random_key, subkey = jax.random.split(random_key)\n",
    "state = reset_fn(subkey)\n",
    "rollout = [state]\n",
    "while True:\n",
    "    actions = policy_network.apply(policy_params, state.obs)\n",
    "    state = step_fn(state, actions)\n",
    "\n",
    "    if state.done:\n",
    "        break\n",
    "    else:\n",
    "        rollout.append(state)\n",
    "\n",
    "if env.state_descriptor_name == \"feet_contact\":\n",
    "    descriptor = sum([s.info[\"state_descriptor\"] for s in rollout]) / len(rollout)\n",
    "elif env.state_descriptor_name == \"xy_position\":\n",
    "    descriptor = rollout[-1].info[\"state_descriptor\"]\n",
    "else:\n",
    "    raise NotImplementedError\n",
    "\n",
    "print(\"Episode length: {}/{}\".format(len(rollout), config.env.episode_length))\n",
    "print(\"Fitness: {}\".format(sum([s.reward for s in rollout])))\n",
    "print(\"Desired descriptor: {}\".format(descriptor_desired))\n",
    "print(\"Repertoire descriptor: {}\".format(descriptor_repertoire))\n",
    "print(\"Observed descriptor: {}\".format(descriptor))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<html>\n",
       "  <head>\n",
       "    <title>brax visualizer</title>\n",
       "    <style>\n",
       "      body {\n",
       "        margin: 0;\n",
       "        padding: 0;\n",
       "      }\n",
       "      #brax-viewer {\n",
       "        margin: 0;\n",
       "        padding: 0;\n",
       "        height: 480px;\n",
       "      }\n",
       "    </style>\n",
       "  </head>\n",
       "  <body>\n",
       "    <script type=\"application/javascript\">\n",
       "    var system = {\"config\": {\"bodies\": [{\"name\": \"$ Torso\", \"colliders\": [{\"capsule\": {\"radius\": 0.25, \"length\": 0.5, \"end\": 1}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 10.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"Aux 1\", \"colliders\": [{\"rotation\": {\"x\": 90.0, \"y\": -45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.44284272, \"end\": 0}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"$ Body 4\", \"colliders\": [{\"rotation\": {\"x\": 90.0, \"y\": -45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.7256854, \"end\": -1}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"Aux 2\", \"colliders\": [{\"rotation\": {\"x\": 90.0, \"y\": 45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.44284272, \"end\": 0}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"$ Body 7\", \"colliders\": [{\"rotation\": {\"x\": 90.0, \"y\": 45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.7256854, \"end\": -1}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"Aux 3\", \"colliders\": [{\"rotation\": {\"x\": -90.0, \"y\": 45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.44284272, \"end\": 0}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"$ Body 10\", \"colliders\": [{\"rotation\": {\"x\": -90.0, \"y\": 45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.7256854, \"end\": -1}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"Aux 4\", \"colliders\": [{\"rotation\": {\"x\": -90.0, \"y\": -45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.44284272, \"end\": 0}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"$ Body 13\", \"colliders\": [{\"rotation\": {\"x\": -90.0, \"y\": -45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.7256854, \"end\": -1}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"Ground\", \"colliders\": [{\"plane\": {}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"rotation\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"all\": true}}], \"joints\": [{\"name\": \"$ Torso_Aux 1\", \"stiffness\": 18000.0, \"parent\": \"$ Torso\", \"child\": \"Aux 1\", \"parentOffset\": {\"x\": 0.2, \"y\": 0.2, \"z\": 0.0}, \"childOffset\": {\"x\": -0.1, \"y\": -0.1, \"z\": 0.0}, \"rotation\": {\"y\": -90.0, \"x\": 0.0, \"z\": 0.0}, \"angularDamping\": 20.0, \"angleLimit\": [{\"min\": -30.0, \"max\": 30.0}], \"springDamping\": 80.0}, {\"name\": \"Aux 1_$ Body 4\", \"stiffness\": 18000.0, \"parent\": \"Aux 1\", \"child\": \"$ Body 4\", \"parentOffset\": {\"x\": 0.1, \"y\": 0.1, \"z\": 0.0}, \"childOffset\": {\"x\": -0.2, \"y\": -0.2, \"z\": 0.0}, \"rotation\": {\"z\": 135.0, \"x\": 0.0, \"y\": 0.0}, \"angularDamping\": 20.0, \"angleLimit\": [{\"min\": 30.0, \"max\": 70.0}], \"springDamping\": 80.0}, {\"name\": \"$ Torso_Aux 2\", \"stiffness\": 18000.0, \"parent\": \"$ Torso\", \"child\": \"Aux 2\", \"parentOffset\": {\"x\": -0.2, \"y\": 0.2, \"z\": 0.0}, \"childOffset\": {\"x\": 0.1, \"y\": -0.1, \"z\": 0.0}, \"rotation\": {\"y\": -90.0, \"x\": 0.0, \"z\": 0.0}, \"angularDamping\": 20.0, \"angleLimit\": [{\"min\": -30.0, \"max\": 30.0}], \"springDamping\": 80.0}, {\"name\": \"Aux 2_$ Body 7\", \"stiffness\": 18000.0, \"parent\": \"Aux 2\", \"child\": \"$ Body 7\", \"parentOffset\": {\"x\": -0.1, \"y\": 0.1, \"z\": 0.0}, \"childOffset\": {\"x\": 0.2, \"y\": -0.2, \"z\": 0.0}, \"rotation\": {\"z\": 45.0, \"x\": 0.0, \"y\": 0.0}, \"angularDamping\": 20.0, \"angleLimit\": [{\"min\": -70.0, \"max\": -30.0}], \"springDamping\": 80.0}, {\"name\": \"$ Torso_Aux 3\", \"stiffness\": 18000.0, \"parent\": \"$ Torso\", \"child\": \"Aux 3\", \"parentOffset\": {\"x\": -0.2, \"y\": -0.2, \"z\": 0.0}, \"childOffset\": {\"x\": 0.1, \"y\": 0.1, \"z\": 0.0}, \"rotation\": {\"y\": -90.0, \"x\": 0.0, \"z\": 0.0}, \"angularDamping\": 20.0, \"angleLimit\": [{\"min\": -30.0, \"max\": 30.0}], \"springDamping\": 80.0}, {\"name\": \"Aux 3_$ Body 10\", \"stiffness\": 18000.0, \"parent\": \"Aux 3\", \"child\": \"$ Body 10\", \"parentOffset\": {\"x\": -0.1, \"y\": -0.1, \"z\": 0.0}, \"childOffset\": {\"x\": 0.2, \"y\": 0.2, \"z\": 0.0}, \"rotation\": {\"z\": 135.0, \"x\": 0.0, \"y\": 0.0}, \"angularDamping\": 20.0, \"angleLimit\": [{\"min\": -70.0, \"max\": -30.0}], \"springDamping\": 80.0}, {\"name\": \"$ Torso_Aux 4\", \"stiffness\": 18000.0, \"parent\": \"$ Torso\", \"child\": \"Aux 4\", \"parentOffset\": {\"x\": 0.2, \"y\": -0.2, \"z\": 0.0}, \"childOffset\": {\"x\": -0.1, \"y\": 0.1, \"z\": 0.0}, \"rotation\": {\"y\": -90.0, \"x\": 0.0, \"z\": 0.0}, \"angularDamping\": 20.0, \"angleLimit\": [{\"min\": -30.0, \"max\": 30.0}], \"springDamping\": 80.0}, {\"name\": \"Aux 4_$ Body 13\", \"stiffness\": 18000.0, \"parent\": \"Aux 4\", \"child\": \"$ Body 13\", \"parentOffset\": {\"x\": 0.1, \"y\": -0.1, \"z\": 0.0}, \"childOffset\": {\"x\": -0.2, \"y\": 0.2, \"z\": 0.0}, \"rotation\": {\"z\": 45.0, \"x\": 0.0, \"y\": 0.0}, \"angularDamping\": 20.0, \"angleLimit\": [{\"min\": 30.0, \"max\": 70.0}], \"springDamping\": 80.0}], \"actuators\": [{\"name\": \"$ Torso_Aux 1\", \"joint\": \"$ Torso_Aux 1\", \"strength\": 350.0, \"torque\": {}}, {\"name\": \"Aux 1_$ Body 4\", \"joint\": \"Aux 1_$ Body 4\", \"strength\": 350.0, \"torque\": {}}, {\"name\": \"$ Torso_Aux 2\", \"joint\": \"$ Torso_Aux 2\", \"strength\": 350.0, \"torque\": {}}, {\"name\": \"Aux 2_$ Body 7\", \"joint\": \"Aux 2_$ Body 7\", \"strength\": 350.0, \"torque\": {}}, {\"name\": \"$ Torso_Aux 3\", \"joint\": \"$ Torso_Aux 3\", \"strength\": 350.0, \"torque\": {}}, {\"name\": \"Aux 3_$ Body 10\", \"joint\": \"Aux 3_$ Body 10\", \"strength\": 350.0, \"torque\": {}}, {\"name\": \"$ Torso_Aux 4\", \"joint\": \"$ Torso_Aux 4\", \"strength\": 350.0, \"torque\": {}}, {\"name\": \"Aux 4_$ Body 13\", \"joint\": \"Aux 4_$ Body 13\", \"strength\": 350.0, \"torque\": {}}], \"friction\": 1.0, \"gravity\": {\"z\": -9.8, \"x\": 0.0, \"y\": 0.0}, \"angularDamping\": -0.05, \"baumgarteErp\": 0.1, \"collideInclude\": [{\"first\": \"$ Torso\", \"second\": \"Ground\"}, {\"first\": \"$ Body 4\", \"second\": \"Ground\"}, {\"first\": \"$ Body 7\", \"second\": \"Ground\"}, {\"first\": \"$ Body 10\", \"second\": \"Ground\"}, {\"first\": \"$ Body 13\", \"second\": \"Ground\"}], \"dt\": 0.05, \"substeps\": 10, \"frozen\": {\"all\": false}, 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-0.7852316498756409], [0.1413869708776474, -0.04773251712322235, 0.011432742699980736, -0.9887369275093079], [0.13128110766410828, -0.254484087228775, 0.16848531365394592, -0.9431945085525513], [0.08237636089324951, -0.044196512550115585, 0.002705623395740986, -0.995617151260376], [0.08590227365493774, -0.20511797070503235, -0.19415214657783508, -0.9554331302642822], [-0.21118374168872833, -0.04896160215139389, -0.009706933051347733, -0.9761711359024048], [-0.18245123326778412, 0.13959573209285736, -0.29888227581977844, -0.9262257218360901], [1.0, 0.0, 0.0, 0.0]], [[-0.12254648655653, -0.05004139244556427, -0.006323766428977251, -0.9911801815032959], [-0.3122864067554474, -0.04782240837812424, -0.01847519911825657, -0.9486037492752075], [-0.2651810944080353, 0.47075486183166504, 0.24294866621494293, -0.8056331872940063], [0.13839460909366608, -0.04664226993918419, 0.0061721946112811565, -0.9892589449882507], [0.12840355932712555, -0.2499733567237854, 0.16156017780303955, -0.9460043907165527], [0.10327602922916412, -0.053630631417036057, 0.005178623367100954, -0.9931923151016235], [0.10844461619853973, -0.21331006288528442, -0.18982486426830292, -0.9522107243537903], [-0.32570481300354004, -0.04872116446495056, -0.014647198840975761, -0.9441017508506775], [-0.29925644397735596, 0.07973143458366394, -0.2737736403942108, -0.9105693101882935], [1.0, 0.0, 0.0, 0.0]], [[-0.11625306308269501, -0.06507004052400589, -0.002312952885404229, -0.9910830855369568], [-0.3029009997844696, -0.06281617283821106, -0.017044709995388985, -0.9507967829704285], [-0.2685568928718567, 0.43579715490341187, 0.23768360912799835, -0.825508713722229], [0.13312816619873047, -0.06487267464399338, 0.012857003137469292, -0.9888898730278015], [0.11941610276699066, -0.2675186097621918, 0.16712108254432678, -0.9414054751396179], [0.14927536249160767, -0.06225384771823883, 0.016162043437361717, -0.9867016077041626], [0.15779387950897217, -0.2138468623161316, -0.1915448158979416, -0.9448181390762329], [-0.37646186351776123, -0.060291022062301636, -0.018019555136561394, -0.9242926239967346], [-0.3332897126674652, 0.08572611957788467, -0.35420534014701843, -0.869544506072998], [1.0, 0.0, 0.0, 0.0]], [[-0.11055610328912735, -0.08545367419719696, -0.0041659739799797535, -0.9901806712150574], [-0.332730233669281, -0.08513288199901581, -0.0232409555464983, -0.9388838410377502], [-0.30290326476097107, 0.41614094376564026, 0.21417593955993652, -0.8301838040351868], [0.10174208879470825, -0.08130931854248047, 0.010395780205726624, -0.9914278984069824], [0.08906996250152588, -0.2764533758163452, 0.1710936278104782, -0.9414706826210022], [0.1520848125219345, -0.08358599245548248, 0.016402507200837135, -0.9846901297569275], [0.1709776371717453, -0.2298784703016281, -0.19179362058639526, -0.9386893510818481], [-0.3324922025203705, -0.08543676882982254, -0.02040071412920952, -0.9390066266059875], [-0.2609714865684509, 0.1216239407658577, -0.43419572710990906, -0.8535664677619934], [1.0, 0.0, 0.0, 0.0]], [[-0.12141302227973938, -0.088027723133564, -0.0009176585590466857, -0.9886907339096069], [-0.3643418550491333, -0.08511025458574295, -0.02557654306292534, -0.9270152449607849], [-0.3276783227920532, 0.4302930533885956, 0.19576449692249298, -0.818016529083252], [0.016174104064702988, -0.08546161651611328, 0.011004169471561909, -0.9961494207382202], [0.0040644011460244656, -0.26684892177581787, 0.19053256511688232, -0.9447076320648193], [0.1443035900592804, -0.08802349865436554, 0.020204788073897362, -0.9854035973548889], [0.1563221514225006, -0.23923444747924805, -0.1852085441350937, -0.940227746963501], [-0.2302062213420868, -0.0865556001663208, -0.006414335686713457, -0.9692636728286743], [-0.16842994093894958, 0.1928146630525589, -0.4377377927303314, -0.8618813753128052], [1.0, 0.0, 0.0, 0.0]]], \"debug\": false};\n",
       "    </script>\n",
       "    <div id=\"brax-viewer\"></div>\n",
       "    <script type=\"module\">\n",
       "      import {Viewer} from 'https://cdn.jsdelivr.net/gh/google/brax@v0.1.0/js/viewer.js';\n",
       "      const domElement = document.getElementById('brax-viewer');\n",
       "      var viewer = new Viewer(domElement, system);\n",
       "    </script>\n",
       "  </body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = html.render(env.sys, [state.qp for state in rollout])\n",
    "with open(run_dir / \"rollout.html\", \"w\") as f:\n",
    "    f.write(a)\n",
    "\n",
    "HTML(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Descriptor-conditioned actor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "random_key, subkey = jax.random.split(random_key)\n",
    "actor_dc_params = actor_dc_network.init(subkey, fake_obs, fake_desc)\n",
    "\n",
    "with open(run_dir / \"actor.pickle\", \"rb\") as params_file:\n",
    "    state_dict = pickle.load(params_file)\n",
    "actor_dc_params = serialization.from_state_dict(actor_dc_params, state_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def normalize_desc(desc):\n",
    "    return 2*(desc - env.behavior_descriptor_limits[0])/(env.behavior_descriptor_limits[1] - env.behavior_descriptor_limits[0]) - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode length: 250/250\n",
      "Fitness: 845.4260864257812\n",
      "Desired descriptor: [30 30]\n",
      "Observed descriptor: [27.339926 26.786737]\n"
     ]
    }
   ],
   "source": [
    "descriptor_desired = jnp.array([30, 30])\n",
    "\n",
    "random_key, subkey = jax.random.split(random_key)\n",
    "state = reset_fn(subkey)\n",
    "rollout = [state]\n",
    "while True:\n",
    "    descriptor_desired_normalized = normalize_desc(descriptor_desired)\n",
    "    actions = actor_dc_network.apply(actor_dc_params, state.obs, descriptor_desired_normalized)\n",
    "    state = step_fn(state, actions)\n",
    "\n",
    "    if state.done:\n",
    "        break\n",
    "    else:\n",
    "        rollout.append(state)\n",
    "\n",
    "if env.state_descriptor_name == \"feet_contact\":\n",
    "    descriptor = sum([s.info[\"state_descriptor\"] for s in rollout]) / len(rollout)\n",
    "elif env.state_descriptor_name == \"xy_position\":\n",
    "    descriptor = rollout[-1].info[\"state_descriptor\"]\n",
    "else:\n",
    "    raise NotImplementedError\n",
    "\n",
    "print(\"Episode length: {}/{}\".format(len(rollout), config.env.episode_length))\n",
    "print(\"Fitness: {}\".format(sum([s.reward for s in rollout])))\n",
    "print(\"Desired descriptor: {}\".format(descriptor_desired))\n",
    "print(\"Observed descriptor: {}\".format(descriptor))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<html>\n",
       "  <head>\n",
       "    <title>brax visualizer</title>\n",
       "    <style>\n",
       "      body {\n",
       "        margin: 0;\n",
       "        padding: 0;\n",
       "      }\n",
       "      #brax-viewer {\n",
       "        margin: 0;\n",
       "        padding: 0;\n",
       "        height: 480px;\n",
       "      }\n",
       "    </style>\n",
       "  </head>\n",
       "  <body>\n",
       "    <script type=\"application/javascript\">\n",
       "    var system = {\"config\": {\"bodies\": [{\"name\": \"$ Torso\", \"colliders\": [{\"capsule\": {\"radius\": 0.25, \"length\": 0.5, \"end\": 1}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 10.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"Aux 1\", \"colliders\": [{\"rotation\": {\"x\": 90.0, \"y\": -45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.44284272, \"end\": 0}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"$ Body 4\", \"colliders\": [{\"rotation\": {\"x\": 90.0, \"y\": -45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.7256854, \"end\": -1}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"Aux 2\", \"colliders\": [{\"rotation\": {\"x\": 90.0, \"y\": 45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.44284272, \"end\": 0}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"$ Body 7\", \"colliders\": [{\"rotation\": {\"x\": 90.0, \"y\": 45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.7256854, \"end\": -1}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"Aux 3\", \"colliders\": [{\"rotation\": {\"x\": -90.0, \"y\": 45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.44284272, \"end\": 0}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"$ Body 10\", \"colliders\": [{\"rotation\": {\"x\": -90.0, \"y\": 45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.7256854, \"end\": -1}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"Aux 4\", \"colliders\": [{\"rotation\": {\"x\": -90.0, \"y\": -45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.44284272, \"end\": 0}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"$ Body 13\", \"colliders\": [{\"rotation\": {\"x\": -90.0, \"y\": -45.0, \"z\": 0.0}, \"capsule\": {\"radius\": 0.08, \"length\": 0.7256854, \"end\": -1}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"rotation\": {\"x\": 0.0, \"y\": 0.0, \"z\": 0.0}, \"all\": false}}, {\"name\": \"Ground\", \"colliders\": [{\"plane\": {}, \"material\": {\"friction\": 1.0, \"elasticity\": 0.0}, \"color\": \"\", \"hidden\": false, \"noContact\": false}], \"inertia\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"mass\": 1.0, \"frozen\": {\"position\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"rotation\": {\"x\": 1.0, \"y\": 1.0, \"z\": 1.0}, \"all\": true}}], \"joints\": [{\"name\": \"$ Torso_Aux 1\", \"stiffness\": 18000.0, \"parent\": \"$ Torso\", \"child\": \"Aux 1\", \"parentOffset\": {\"x\": 0.2, \"y\": 0.2, \"z\": 0.0}, \"childOffset\": {\"x\": -0.1, \"y\": -0.1, \"z\": 0.0}, \"rotation\": {\"y\": -90.0, \"x\": 0.0, \"z\": 0.0}, \"angularDamping\": 20.0, \"angleLimit\": [{\"min\": -30.0, \"max\": 30.0}], \"springDamping\": 80.0}, {\"name\": \"Aux 1_$ Body 4\", \"stiffness\": 18000.0, \"parent\": \"Aux 1\", \"child\": \"$ Body 4\", \"parentOffset\": {\"x\": 0.1, \"y\": 0.1, \"z\": 0.0}, \"childOffset\": {\"x\": -0.2, \"y\": -0.2, \"z\": 0.0}, \"rotation\": {\"z\": 135.0, \"x\": 0.0, \"y\": 0.0}, \"angularDamping\": 20.0, \"angleLimit\": [{\"min\": 30.0, \"max\": 70.0}], \"springDamping\": 80.0}, {\"name\": \"$ Torso_Aux 2\", \"stiffness\": 18000.0, \"parent\": \"$ Torso\", \"child\": \"Aux 2\", \"parentOffset\": {\"x\": -0.2, \"y\": 0.2, \"z\": 0.0}, \"childOffset\": {\"x\": 0.1, \"y\": -0.1, \"z\": 0.0}, \"rotation\": {\"y\": -90.0, \"x\": 0.0, \"z\": 0.0}, \"angularDamping\": 20.0, \"angleLimit\": [{\"min\": -30.0, \"max\": 30.0}], \"springDamping\": 80.0}, {\"name\": \"Aux 2_$ Body 7\", \"stiffness\": 18000.0, \"parent\": \"Aux 2\", \"child\": \"$ Body 7\", \"parentOffset\": {\"x\": -0.1, \"y\": 0.1, \"z\": 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       "    </script>\n",
       "    <div id=\"brax-viewer\"></div>\n",
       "    <script type=\"module\">\n",
       "      import {Viewer} from 'https://cdn.jsdelivr.net/gh/google/brax@v0.1.0/js/viewer.js';\n",
       "      const domElement = document.getElementById('brax-viewer');\n",
       "      var viewer = new Viewer(domElement, system);\n",
       "    </script>\n",
       "  </body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = html.render(env.sys, [state.qp for state in rollout])\n",
    "with open(run_dir / \"rollout.html\", \"w\") as f:\n",
    "    f.write(a)\n",
    "\n",
    "HTML(a)"
   ]
  }
 ],
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