{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "x83dMPapQBN6"
},
"source": [
"# Gyroscope DDPG/TD3/SAC training (spinup library)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {},
"colab_type": "code",
"id": "8inmkEG5QHqx"
},
"outputs": [],
"source": [
"from google.colab import drive\n",
"drive.mount('/content/drive')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"colab_type": "code",
"executionInfo": {
"elapsed": 655,
"status": "ok",
"timestamp": 1584030129316,
"user": {
"displayName": "Matthieu Le Cauchois",
"photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgY9gRlHHK-FHlINeRnTJw_wewJsr639GH8MAWl=s64",
"userId": "10992927378504656501"
},
"user_tz": -60
},
"id": "DnnJGcnsQvZC",
"outputId": "9d6d1408-da29-44ed-af74-4ebdc2bd865a"
},
"outputs": [],
"source": [
"cd drive/My\\ Drive/Colab Notebooks/DDPG_uda_v0/"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"colab": {},
"colab_type": "code",
"id": "fuJhdd479TpP"
},
"outputs": [
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/javascript": [
"if (typeof Jupyter !== \"undefined\") { window.__context = { glowscript_container: $(\"#glowscript\").removeAttr(\"id\")};}else{ element.textContent = ' ';}"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"ename": "ModuleNotFoundError",
"evalue": "No module named 'spinup'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mvpython\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mspinup\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'spinup'"
]
}
],
"source": [
"import gym\n",
"from gym import spaces\n",
"from gym.utils import seeding\n",
"from os import path\n",
"from scipy.integrate import solve_ivp\n",
"import random\n",
"import torch\n",
"import numpy as np\n",
"from collections import deque\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline\n",
"from vpython import *\n",
"\n",
"import spinup"
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "O0O0t5ZR9Tp6"
},
"source": [
"## Environment Class and Modules"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"colab": {},
"colab_type": "code",
"id": "Al_k1rtvQBOM"
},
"outputs": [],
"source": [
"class GyroscopeEnv(gym.Env):\n",
" \n",
" \n",
" \"\"\"\n",
" GyroscopeEnv is a double gimbal control moment gyroscope (DGCMG) with 2 input voltage u1 and u2 \n",
" on the two gimbals, and disk speed assumed constant (parameter w). Simulation is based on the \n",
" Quanser 3-DOF gyroscope setup.\n",
" \n",
" \n",
" **STATE:**\n",
" The state consists of the angle and angular speed of the outer red gimbal (theta = x1, thetadot = x2),\n",
" the angle and angular speed of the inner blue gimbal (phi = x3, phidot = x4), the difference to the reference\n",
" for tracking on theta and phi (tracking error theta = diff_x1, tracking error phi = diff_x3), and the \n",
" disk speed (disk speed = w):\n",
" \n",
" state = [x1, x2, x3, x4, diff_x1, diff_x3, w]\n",
" \n",
" **ACTIONS:**\n",
" The actions are the input voltage to create the red and blue gimbal torque (red voltage = u1, blue voltage = u2),\n",
" and are continuous in a range of -10 and 10V:\n",
" \n",
" action = [u1,u2]\n",
" \n",
" \"\"\"\n",
" \n",
" \n",
" metadata = {\n",
" 'render.modes' : ['human', 'rgb_array'],\n",
" 'video.frames_per_second' : 30\n",
" }\n",
"\n",
" def __init__(self):\n",
" \n",
" # Inertias in Kg*m2\n",
" self.Jbx1 = 0.0019\n",
" self.Jbx2 = 0.0008\n",
" self.Jbx3 = 0.0012\n",
" self.Jrx1 = 0.0179\n",
" self.Jdx1 = 0.0028\n",
" self.Jdx3 = 0.0056\n",
" \n",
" # Combined inertias\n",
" self.J1 = self.Jbx1 - self.Jbx3 + self.Jdx1 - self.Jdx3\n",
" self.J2 = self.Jbx1 + self.Jdx1 + self.Jrx1\n",
" self.J3 = self.Jbx2 + self.Jdx1\n",
"\n",
" # Motor constants\n",
" self.Kamp = 0.5 # A/V\n",
" self.Ktorque = 0.0704 # Nm/A\n",
" self.eff = 0.86\n",
" self.nRed = 1.5\n",
" self.nBlue = 1\n",
" self.KtotRed = self.Kamp*self.Ktorque*self.eff*self.nRed \n",
" self.KtotBlue = self.Kamp*self.Ktorque*self.eff*self.nBlue \n",
" \n",
" # Time step in s\n",
" self.dt = 0.05\n",
" \n",
" # Error\n",
" self.int_diff_x1 = 0\n",
" self.int_diff_x3 = 0\n",
" \n",
" # Action space\n",
" self.maxVoltage = 10 # V\n",
" self.highAct = np.array([self.maxVoltage,self.maxVoltage])\n",
" self.action_space = spaces.Box(low = -self.highAct, high = self.highAct, dtype=np.float32) \n",
" \n",
" # Observation space (here it is equal to state space)\n",
" self.maxSpeed = 100 * 2 * np.pi / 60\n",
" self.maxAngle = np.pi\n",
" self.maxdiskSpeed = 300 * 2 * np.pi / 60\n",
" self.highObs = np.array([self.maxAngle,self.maxSpeed,self.maxAngle,self.maxSpeed,self.maxAngle,self.maxAngle,self.maxdiskSpeed])\n",
" self.observation_space = spaces.Box(low = -self.highObs, high = self.highObs, dtype=np.float32)\n",
"\n",
" # Seed for random number generation\n",
" self.seed()\n",
" \n",
" self.viewer = None\n",
"\n",
" def seed(self, seed=None):\n",
" self.np_random, seed = seeding.np_random(seed)\n",
" return [seed]\n",
" \n",
" \n",
"\n",
" def step(self,u):\n",
" x1, x2, x3, x4, x1_ref, x3_ref, w= self.state \n",
" u1,u2 = u\n",
" \n",
" # Angle error\n",
" diff_x1 = angle_normalize(x1 - x1_ref)\n",
" diff_x3 = angle_normalize(x3 - x3_ref)\n",
" \n",
" # Integral of error\n",
" self.int_diff_x1 = self.int_diff_x1 + diff_x1\n",
" self.int_diff_x3 = self.int_diff_x3 + diff_x3\n",
" \n",
" # Reward 1: differentiable reward (LQR obj function)\n",
" reward = -((3*diff_x1)**2 + (3*diff_x3)**2 + (.2*x2)**2 + (.2*x4)**2 + (.1*u1)**2 + (.1*u2)**2)\\\n",
" #-(0.01*abs(self.int_diff_x1) + 0.01*abs(self.int_diff_x3))\n",
"\n",
" \"\"\"# Count time spent in goal:\n",
" if abs(diff_x1)<0.05 and abs(diff_x3)<0.05:\n",
" self.countGoal +=1\n",
" else:\n",
" self.countGoal = 0\n",
" \n",
" # Reward 2: sparse reward for staying in goal range for a long time \n",
" if self.countGoal >= (self.timeGoal)/self.dt: #max expected reward over length becomes 0 + (totaltime-goaltime)\n",
" reward += 1\"\"\"\n",
"\n",
"\n",
" results = solve_ivp(fun = dxdt, t_span = (0, self.dt), y0 = [x1,x2,x3,x4], method='RK45', args=(u1,u2,self))\n",
" \n",
" x1 = angle_normalize(results.y[0][-1])\n",
" x2 = np.clip(results.y[1][-1],-self.maxSpeed,self.maxSpeed)\n",
" x3 = angle_normalize(results.y[2][-1])\n",
" x4 = np.clip(results.y[3][-1],-self.maxSpeed,self.maxSpeed)\n",
" \n",
" self.state = np.asarray([x1,x2,x3,x4,x1_ref, x3_ref,w])\n",
"\n",
" return (self.state, reward, False, {})\n",
"\n",
" def reset(self, state = None):\n",
" \n",
" \n",
" # Generate random state (for training) or use given state (for simulation)\n",
" if state is None:\n",
" self.state = self.np_random.uniform(low=-self.highObs, high=self.highObs)\n",
" else:\n",
" self.state = state\n",
"\n",
" \n",
" return self.state\n",
"\n",
"\n",
" def render(self, mode='human'):\n",
" return None\n",
" \n",
" def close(self):\n",
" if self.viewer:\n",
" self.viewer.close()\n",
" self.viewer = None\n",
" \n",
"def dxdt(t, x, u1, u2, gyro):\n",
" \n",
" # Rewrite constants shorter\n",
" J1 = gyro.J1\n",
" J2 = gyro.J2\n",
" J3 = gyro.J3\n",
" Jdx3 = gyro.Jdx3\n",
" KtotRed = gyro.KtotRed\n",
" KtotBlue = gyro.KtotBlue\n",
" w = x[-1]\n",
"\n",
" # Convert input voltage to input torque\n",
" u1,u2 = KtotRed*u1, KtotBlue*u2\n",
" \n",
" # Equations of motion \n",
" dx_dt = [0, 0, 0, 0]\n",
" dx_dt[0] = x[1]\n",
" dx_dt[1] = (u1+J1*np.sin(2*x[2])*x[1]*x[3]-Jdx3*np.cos(x[2])*x[3]*w)/(J2 + J1*np.power(np.sin(x[2]),2))\n",
" dx_dt[2] = x[3]\n",
" dx_dt[3] = (u2 - J1*np.cos(x[2])*np.sin(x[2])*np.power(x[1],2)+Jdx3*np.cos(x[2])*x[1]*w)/J3\n",
" return dx_dt\n",
" \n",
"def angle_normalize(x):\n",
" return (((x+np.pi) % (2*np.pi)) - np.pi) # To keep the angles between -pi and pi\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "be0wYIeBQBOc"
},
"source": [
"## Training"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 533
},
"colab_type": "code",
"executionInfo": {
"elapsed": 654004,
"status": "error",
"timestamp": 1584037207187,
"user": {
"displayName": "Matthieu Le Cauchois",
"photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgY9gRlHHK-FHlINeRnTJw_wewJsr639GH8MAWl=s64",
"userId": "10992927378504656501"
},
"user_tz": -60
},
"id": "fLyFHs0yQBOd",
"outputId": "260489ff-5e40-416a-e529-5a0cfcaefceb"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Warning: Log dir model already exists! Storing info there anyway.\n",
"\u001b[32;1mLogging data to model/progress.txt\u001b[0m\n",
"\u001b[36;1mSaving config:\n",
"\u001b[0m\n",
"{\n",
" \"ac_kwargs\":\t{},\n",
" \"act_noise\":\t0.1,\n",
" \"actor_critic\":\t\"MLPActorCritic\",\n",
" \"batch_size\":\t100,\n",
" \"env_fn\":\t\"GyroscopeEnv\",\n",
" \"epochs\":\t120,\n",
" \"exp_name\":\t\"v0\",\n",
" \"gamma\":\t0.95,\n",
" \"logger\":\t{\n",
" \"\":\t{\n",
" \"epoch_dict\":\t{},\n",
" \"exp_name\":\t\"v0\",\n",
" \"first_row\":\ttrue,\n",
" \"log_current_row\":\t{},\n",
" \"log_headers\":\t[],\n",
" \"output_dir\":\t\"model\",\n",
" \"output_file\":\t{\n",
" \"<_io.TextIOWrapper name='model/progress.txt' mode='w' encoding='UTF-8'>\":\t{\n",
" \"mode\":\t\"w\"\n",
" }\n",
" }\n",
" }\n",
" },\n",
" \"logger_kwargs\":\t{\n",
" \"exp_name\":\t\"v0\",\n",
" \"output_dir\":\t\"model\"\n",
" },\n",
" \"max_ep_len\":\t110,\n",
" \"noise_clip\":\t0.5,\n",
" \"num_test_episodes\":\t10,\n",
" \"pi_lr\":\t0.001,\n",
" \"policy_delay\":\t2,\n",
" \"polyak\":\t0.995,\n",
" \"q_lr\":\t0.001,\n",
" \"replay_size\":\t1000000,\n",
" \"save_freq\":\t1,\n",
" \"seed\":\t0,\n",
" \"start_steps\":\t20000,\n",
" \"steps_per_epoch\":\t2200,\n",
" \"target_noise\":\t0.2,\n",
" \"update_after\":\t800,\n",
" \"update_every\":\t50\n",
"}\n",
"\u001b[32;1m\n",
"Number of parameters: \t pi: 68354, \t q1: 68609, \t q2: 68609\n",
"\u001b[0m\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/matthieulc/Documents/MA2/PS1/ps1venv/lib/python3.6/site-packages/gym/logger.py:30: UserWarning: \u001b[33mWARN: Box bound precision lowered by casting to float32\u001b[0m\n",
" warnings.warn(colorize('%s: %s'%('WARN', msg % args), 'yellow'))\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 1 |\n",
"| AverageEpRet | -6.44e+03 |\n",
"| StdEpRet | 1.49e+03 |\n",
"| MaxEpRet | -4.55e+03 |\n",
"| MinEpRet | -9.52e+03 |\n",
"| AverageTestEpRet | -7.13e+03 |\n",
"| StdTestEpRet | 1.25e+03 |\n",
"| MaxTestEpRet | -4.01e+03 |\n",
"| MinTestEpRet | -8.49e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.2e+03 |\n",
"| AverageQ1Vals | -123 |\n",
"| StdQ1Vals | 54.5 |\n",
"| MaxQ1Vals | 0.0809 |\n",
"| MinQ1Vals | -364 |\n",
"| AverageQ2Vals | -123 |\n",
"| StdQ2Vals | 54.6 |\n",
"| MaxQ2Vals | 1.77 |\n",
"| MinQ2Vals | -373 |\n",
"| LossPi | 112 |\n",
"| LossQ | 1.95e+03 |\n",
"| Time | 15.8 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 2 |\n",
"| AverageEpRet | -6.72e+03 |\n",
"| StdEpRet | 1.81e+03 |\n",
"| MaxEpRet | -4.58e+03 |\n",
"| MinEpRet | -1.07e+04 |\n",
"| AverageTestEpRet | -8.21e+03 |\n",
"| StdTestEpRet | 1.1e+03 |\n",
"| MaxTestEpRet | -6.46e+03 |\n",
"| MinTestEpRet | -1.01e+04 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 4.4e+03 |\n",
"| AverageQ1Vals | -276 |\n",
"| StdQ1Vals | 98.9 |\n",
"| MaxQ1Vals | -54.4 |\n",
"| MinQ1Vals | -672 |\n",
"| AverageQ2Vals | -276 |\n",
"| StdQ2Vals | 99.2 |\n",
"| MaxQ2Vals | -51.6 |\n",
"| MinQ2Vals | -686 |\n",
"| LossPi | 256 |\n",
"| LossQ | 2.12e+03 |\n",
"| Time | 42.1 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 3 |\n",
"| AverageEpRet | -7.08e+03 |\n",
"| StdEpRet | 1.22e+03 |\n",
"| MaxEpRet | -4.94e+03 |\n",
"| MinEpRet | -9.27e+03 |\n",
"| AverageTestEpRet | -5.91e+03 |\n",
"| StdTestEpRet | 1.83e+03 |\n",
"| MaxTestEpRet | -3.79e+03 |\n",
"| MinTestEpRet | -9.63e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 6.6e+03 |\n",
"| AverageQ1Vals | -414 |\n",
"| StdQ1Vals | 128 |\n",
"| MaxQ1Vals | -36.3 |\n",
"| MinQ1Vals | -952 |\n",
"| AverageQ2Vals | -414 |\n",
"| StdQ2Vals | 128 |\n",
"| MaxQ2Vals | -26.8 |\n",
"| MinQ2Vals | -950 |\n",
"| LossPi | 382 |\n",
"| LossQ | 2.76e+03 |\n",
"| Time | 67.9 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 4 |\n",
"| AverageEpRet | -7.06e+03 |\n",
"| StdEpRet | 1.53e+03 |\n",
"| MaxEpRet | -4.98e+03 |\n",
"| MinEpRet | -1.09e+04 |\n",
"| AverageTestEpRet | -5.01e+03 |\n",
"| StdTestEpRet | 1.18e+03 |\n",
"| MaxTestEpRet | -3.34e+03 |\n",
"| MinTestEpRet | -6.44e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 8.8e+03 |\n",
"| AverageQ1Vals | -501 |\n",
"| StdQ1Vals | 154 |\n",
"| MaxQ1Vals | 11.2 |\n",
"| MinQ1Vals | -1.07e+03 |\n",
"| AverageQ2Vals | -501 |\n",
"| StdQ2Vals | 154 |\n",
"| MaxQ2Vals | 16.9 |\n",
"| MinQ2Vals | -1.11e+03 |\n",
"| LossPi | 459 |\n",
"| LossQ | 3.94e+03 |\n",
"| Time | 92 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 5 |\n",
"| AverageEpRet | -6.3e+03 |\n",
"| StdEpRet | 1.14e+03 |\n",
"| MaxEpRet | -3.87e+03 |\n",
"| MinEpRet | -8.1e+03 |\n",
"| AverageTestEpRet | -4.27e+03 |\n",
"| StdTestEpRet | 1.52e+03 |\n",
"| MaxTestEpRet | -1.82e+03 |\n",
"| MinTestEpRet | -6.62e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.1e+04 |\n",
"| AverageQ1Vals | -552 |\n",
"| StdQ1Vals | 173 |\n",
"| MaxQ1Vals | -15.7 |\n",
"| MinQ1Vals | -1.15e+03 |\n",
"| AverageQ2Vals | -552 |\n",
"| StdQ2Vals | 172 |\n",
"| MaxQ2Vals | 17.8 |\n",
"| MinQ2Vals | -1.17e+03 |\n",
"| LossPi | 508 |\n",
"| LossQ | 4.63e+03 |\n",
"| Time | 116 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 6 |\n",
"| AverageEpRet | -6.76e+03 |\n",
"| StdEpRet | 1.35e+03 |\n",
"| MaxEpRet | -4.61e+03 |\n",
"| MinEpRet | -1.13e+04 |\n",
"| AverageTestEpRet | -3.67e+03 |\n",
"| StdTestEpRet | 994 |\n",
"| MaxTestEpRet | -2.24e+03 |\n",
"| MinTestEpRet | -5.28e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.32e+04 |\n",
"| AverageQ1Vals | -574 |\n",
"| StdQ1Vals | 186 |\n",
"| MaxQ1Vals | -39.4 |\n",
"| MinQ1Vals | -1.41e+03 |\n",
"| AverageQ2Vals | -574 |\n",
"| StdQ2Vals | 185 |\n",
"| MaxQ2Vals | -27.9 |\n",
"| MinQ2Vals | -1.29e+03 |\n",
"| LossPi | 527 |\n",
"| LossQ | 5.18e+03 |\n",
"| Time | 139 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 7 |\n",
"| AverageEpRet | -7.02e+03 |\n",
"| StdEpRet | 1.79e+03 |\n",
"| MaxEpRet | -3.34e+03 |\n",
"| MinEpRet | -9.5e+03 |\n",
"| AverageTestEpRet | -3.05e+03 |\n",
"| StdTestEpRet | 1.56e+03 |\n",
"| MaxTestEpRet | -1.34e+03 |\n",
"| MinTestEpRet | -6.7e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.54e+04 |\n",
"| AverageQ1Vals | -582 |\n",
"| StdQ1Vals | 196 |\n",
"| MaxQ1Vals | -68.9 |\n",
"| MinQ1Vals | -1.38e+03 |\n",
"| AverageQ2Vals | -582 |\n",
"| StdQ2Vals | 195 |\n",
"| MaxQ2Vals | -43.9 |\n",
"| MinQ2Vals | -1.31e+03 |\n",
"| LossPi | 534 |\n",
"| LossQ | 5.26e+03 |\n",
"| Time | 163 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 8 |\n",
"| AverageEpRet | -6.62e+03 |\n",
"| StdEpRet | 1.42e+03 |\n",
"| MaxEpRet | -4.04e+03 |\n",
"| MinEpRet | -9.02e+03 |\n",
"| AverageTestEpRet | -1.54e+03 |\n",
"| StdTestEpRet | 771 |\n",
"| MaxTestEpRet | -595 |\n",
"| MinTestEpRet | -3e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.76e+04 |\n",
"| AverageQ1Vals | -573 |\n",
"| StdQ1Vals | 209 |\n",
"| MaxQ1Vals | -4.68 |\n",
"| MinQ1Vals | -1.34e+03 |\n",
"| AverageQ2Vals | -573 |\n",
"| StdQ2Vals | 209 |\n",
"| MaxQ2Vals | 22.9 |\n",
"| MinQ2Vals | -1.35e+03 |\n",
"| LossPi | 522 |\n",
"| LossQ | 5.51e+03 |\n",
"| Time | 187 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 9 |\n",
"| AverageEpRet | -6.7e+03 |\n",
"| StdEpRet | 1.58e+03 |\n",
"| MaxEpRet | -4.21e+03 |\n",
"| MinEpRet | -9.46e+03 |\n",
"| AverageTestEpRet | -842 |\n",
"| StdTestEpRet | 304 |\n",
"| MaxTestEpRet | -411 |\n",
"| MinTestEpRet | -1.52e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.98e+04 |\n",
"| AverageQ1Vals | -546 |\n",
"| StdQ1Vals | 223 |\n",
"| MaxQ1Vals | 71.2 |\n",
"| MinQ1Vals | -1.4e+03 |\n",
"| AverageQ2Vals | -546 |\n",
"| StdQ2Vals | 222 |\n",
"| MaxQ2Vals | 60.5 |\n",
"| MinQ2Vals | -1.41e+03 |\n",
"| LossPi | 490 |\n",
"| LossQ | 5.83e+03 |\n",
"| Time | 211 |\n",
"---------------------------------------\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 10 |\n",
"| AverageEpRet | -1.66e+03 |\n",
"| StdEpRet | 1.99e+03 |\n",
"| MaxEpRet | -153 |\n",
"| MinEpRet | -8.64e+03 |\n",
"| AverageTestEpRet | -872 |\n",
"| StdTestEpRet | 378 |\n",
"| MaxTestEpRet | -487 |\n",
"| MinTestEpRet | -1.53e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.2e+04 |\n",
"| AverageQ1Vals | -488 |\n",
"| StdQ1Vals | 243 |\n",
"| MaxQ1Vals | 151 |\n",
"| MinQ1Vals | -1.43e+03 |\n",
"| AverageQ2Vals | -488 |\n",
"| StdQ2Vals | 243 |\n",
"| MaxQ2Vals | 127 |\n",
"| MinQ2Vals | -1.4e+03 |\n",
"| LossPi | 432 |\n",
"| LossQ | 5.85e+03 |\n",
"| Time | 239 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 11 |\n",
"| AverageEpRet | -947 |\n",
"| StdEpRet | 493 |\n",
"| MaxEpRet | -232 |\n",
"| MinEpRet | -1.89e+03 |\n",
"| AverageTestEpRet | -1.09e+03 |\n",
"| StdTestEpRet | 661 |\n",
"| MaxTestEpRet | -271 |\n",
"| MinTestEpRet | -2.78e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.42e+04 |\n",
"| AverageQ1Vals | -425 |\n",
"| StdQ1Vals | 258 |\n",
"| MaxQ1Vals | 141 |\n",
"| MinQ1Vals | -1.4e+03 |\n",
"| AverageQ2Vals | -425 |\n",
"| StdQ2Vals | 258 |\n",
"| MaxQ2Vals | 137 |\n",
"| MinQ2Vals | -1.39e+03 |\n",
"| LossPi | 376 |\n",
"| LossQ | 4.71e+03 |\n",
"| Time | 263 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 12 |\n",
"| AverageEpRet | -888 |\n",
"| StdEpRet | 472 |\n",
"| MaxEpRet | -325 |\n",
"| MinEpRet | -2.33e+03 |\n",
"| AverageTestEpRet | -602 |\n",
"| StdTestEpRet | 199 |\n",
"| MaxTestEpRet | -286 |\n",
"| MinTestEpRet | -910 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.64e+04 |\n",
"| AverageQ1Vals | -384 |\n",
"| StdQ1Vals | 264 |\n",
"| MaxQ1Vals | 161 |\n",
"| MinQ1Vals | -1.41e+03 |\n",
"| AverageQ2Vals | -384 |\n",
"| StdQ2Vals | 264 |\n",
"| MaxQ2Vals | 142 |\n",
"| MinQ2Vals | -1.39e+03 |\n",
"| LossPi | 341 |\n",
"| LossQ | 3.72e+03 |\n",
"| Time | 288 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 13 |\n",
"| AverageEpRet | -797 |\n",
"| StdEpRet | 536 |\n",
"| MaxEpRet | -48.6 |\n",
"| MinEpRet | -2.46e+03 |\n",
"| AverageTestEpRet | -857 |\n",
"| StdTestEpRet | 354 |\n",
"| MaxTestEpRet | -467 |\n",
"| MinTestEpRet | -1.77e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.86e+04 |\n",
"| AverageQ1Vals | -354 |\n",
"| StdQ1Vals | 270 |\n",
"| MaxQ1Vals | 169 |\n",
"| MinQ1Vals | -1.36e+03 |\n",
"| AverageQ2Vals | -354 |\n",
"| StdQ2Vals | 270 |\n",
"| MaxQ2Vals | 166 |\n",
"| MinQ2Vals | -1.35e+03 |\n",
"| LossPi | 314 |\n",
"| LossQ | 3.07e+03 |\n",
"| Time | 312 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 14 |\n",
"| AverageEpRet | -926 |\n",
"| StdEpRet | 418 |\n",
"| MaxEpRet | -333 |\n",
"| MinEpRet | -1.67e+03 |\n",
"| AverageTestEpRet | -902 |\n",
"| StdTestEpRet | 481 |\n",
"| MaxTestEpRet | -146 |\n",
"| MinTestEpRet | -2.01e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 3.08e+04 |\n",
"| AverageQ1Vals | -326 |\n",
"| StdQ1Vals | 274 |\n",
"| MaxQ1Vals | 192 |\n",
"| MinQ1Vals | -1.34e+03 |\n",
"| AverageQ2Vals | -326 |\n",
"| StdQ2Vals | 274 |\n",
"| MaxQ2Vals | 191 |\n",
"| MinQ2Vals | -1.34e+03 |\n",
"| LossPi | 288 |\n",
"| LossQ | 2.66e+03 |\n",
"| Time | 337 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 15 |\n",
"| AverageEpRet | -738 |\n",
"| StdEpRet | 339 |\n",
"| MaxEpRet | -267 |\n",
"| MinEpRet | -1.46e+03 |\n",
"| AverageTestEpRet | -1.45e+03 |\n",
"| StdTestEpRet | 1.42e+03 |\n",
"| MaxTestEpRet | -185 |\n",
"| MinTestEpRet | -4.34e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 3.3e+04 |\n",
"| AverageQ1Vals | -297 |\n",
"| StdQ1Vals | 279 |\n",
"| MaxQ1Vals | 220 |\n",
"| MinQ1Vals | -1.31e+03 |\n",
"| AverageQ2Vals | -297 |\n",
"| StdQ2Vals | 279 |\n",
"| MaxQ2Vals | 221 |\n",
"| MinQ2Vals | -1.31e+03 |\n",
"| LossPi | 261 |\n",
"| LossQ | 2.37e+03 |\n",
"| Time | 362 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 16 |\n",
"| AverageEpRet | -1.37e+03 |\n",
"| StdEpRet | 1.85e+03 |\n",
"| MaxEpRet | -223 |\n",
"| MinEpRet | -8.63e+03 |\n",
"| AverageTestEpRet | -595 |\n",
"| StdTestEpRet | 159 |\n",
"| MaxTestEpRet | -339 |\n",
"| MinTestEpRet | -913 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 3.52e+04 |\n",
"| AverageQ1Vals | -267 |\n",
"| StdQ1Vals | 277 |\n",
"| MaxQ1Vals | 279 |\n",
"| MinQ1Vals | -1.3e+03 |\n",
"| AverageQ2Vals | -267 |\n",
"| StdQ2Vals | 277 |\n",
"| MaxQ2Vals | 269 |\n",
"| MinQ2Vals | -1.27e+03 |\n",
"| LossPi | 231 |\n",
"| LossQ | 2.21e+03 |\n",
"| Time | 386 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 17 |\n",
"| AverageEpRet | -754 |\n",
"| StdEpRet | 595 |\n",
"| MaxEpRet | -202 |\n",
"| MinEpRet | -2.5e+03 |\n",
"| AverageTestEpRet | -636 |\n",
"| StdTestEpRet | 389 |\n",
"| MaxTestEpRet | -147 |\n",
"| MinTestEpRet | -1.49e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 3.74e+04 |\n",
"| AverageQ1Vals | -245 |\n",
"| StdQ1Vals | 273 |\n",
"| MaxQ1Vals | 278 |\n",
"| MinQ1Vals | -1.25e+03 |\n",
"| AverageQ2Vals | -245 |\n",
"| StdQ2Vals | 273 |\n",
"| MaxQ2Vals | 268 |\n",
"| MinQ2Vals | -1.24e+03 |\n",
"| LossPi | 211 |\n",
"| LossQ | 2.03e+03 |\n",
"| Time | 411 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 18 |\n",
"| AverageEpRet | -616 |\n",
"| StdEpRet | 339 |\n",
"| MaxEpRet | -241 |\n",
"| MinEpRet | -1.4e+03 |\n",
"| AverageTestEpRet | -713 |\n",
"| StdTestEpRet | 304 |\n",
"| MaxTestEpRet | -419 |\n",
"| MinTestEpRet | -1.53e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 3.96e+04 |\n",
"| AverageQ1Vals | -226 |\n",
"| StdQ1Vals | 268 |\n",
"| MaxQ1Vals | 275 |\n",
"| MinQ1Vals | -1.19e+03 |\n",
"| AverageQ2Vals | -226 |\n",
"| StdQ2Vals | 268 |\n",
"| MaxQ2Vals | 265 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 194 |\n",
"| LossQ | 1.83e+03 |\n",
"| Time | 434 |\n",
"---------------------------------------\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 19 |\n",
"| AverageEpRet | -745 |\n",
"| StdEpRet | 537 |\n",
"| MaxEpRet | -109 |\n",
"| MinEpRet | -2.14e+03 |\n",
"| AverageTestEpRet | -963 |\n",
"| StdTestEpRet | 641 |\n",
"| MaxTestEpRet | -159 |\n",
"| MinTestEpRet | -2.65e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 4.18e+04 |\n",
"| AverageQ1Vals | -214 |\n",
"| StdQ1Vals | 263 |\n",
"| MaxQ1Vals | 273 |\n",
"| MinQ1Vals | -1.18e+03 |\n",
"| AverageQ2Vals | -214 |\n",
"| StdQ2Vals | 263 |\n",
"| MaxQ2Vals | 266 |\n",
"| MinQ2Vals | -1.18e+03 |\n",
"| LossPi | 183 |\n",
"| LossQ | 1.67e+03 |\n",
"| Time | 458 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 20 |\n",
"| AverageEpRet | -711 |\n",
"| StdEpRet | 511 |\n",
"| MaxEpRet | -18.3 |\n",
"| MinEpRet | -1.83e+03 |\n",
"| AverageTestEpRet | -803 |\n",
"| StdTestEpRet | 372 |\n",
"| MaxTestEpRet | -126 |\n",
"| MinTestEpRet | -1.53e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 4.4e+04 |\n",
"| AverageQ1Vals | -198 |\n",
"| StdQ1Vals | 260 |\n",
"| MaxQ1Vals | 276 |\n",
"| MinQ1Vals | -1.19e+03 |\n",
"| AverageQ2Vals | -198 |\n",
"| StdQ2Vals | 260 |\n",
"| MaxQ2Vals | 268 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 169 |\n",
"| LossQ | 1.57e+03 |\n",
"| Time | 483 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 21 |\n",
"| AverageEpRet | -664 |\n",
"| StdEpRet | 403 |\n",
"| MaxEpRet | -176 |\n",
"| MinEpRet | -1.87e+03 |\n",
"| AverageTestEpRet | -577 |\n",
"| StdTestEpRet | 343 |\n",
"| MaxTestEpRet | -133 |\n",
"| MinTestEpRet | -1.16e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 4.62e+04 |\n",
"| AverageQ1Vals | -187 |\n",
"| StdQ1Vals | 254 |\n",
"| MaxQ1Vals | 269 |\n",
"| MinQ1Vals | -1.15e+03 |\n",
"| AverageQ2Vals | -187 |\n",
"| StdQ2Vals | 254 |\n",
"| MaxQ2Vals | 262 |\n",
"| MinQ2Vals | -1.13e+03 |\n",
"| LossPi | 159 |\n",
"| LossQ | 1.48e+03 |\n",
"| Time | 507 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 22 |\n",
"| AverageEpRet | -662 |\n",
"| StdEpRet | 341 |\n",
"| MaxEpRet | -261 |\n",
"| MinEpRet | -1.64e+03 |\n",
"| AverageTestEpRet | -780 |\n",
"| StdTestEpRet | 458 |\n",
"| MaxTestEpRet | -39.9 |\n",
"| MinTestEpRet | -1.77e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 4.84e+04 |\n",
"| AverageQ1Vals | -178 |\n",
"| StdQ1Vals | 249 |\n",
"| MaxQ1Vals | 260 |\n",
"| MinQ1Vals | -1.15e+03 |\n",
"| AverageQ2Vals | -178 |\n",
"| StdQ2Vals | 249 |\n",
"| MaxQ2Vals | 258 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 151 |\n",
"| LossQ | 1.35e+03 |\n",
"| Time | 531 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 23 |\n",
"| AverageEpRet | -524 |\n",
"| StdEpRet | 312 |\n",
"| MaxEpRet | -85.9 |\n",
"| MinEpRet | -1.22e+03 |\n",
"| AverageTestEpRet | -768 |\n",
"| StdTestEpRet | 268 |\n",
"| MaxTestEpRet | -329 |\n",
"| MinTestEpRet | -1.3e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 5.06e+04 |\n",
"| AverageQ1Vals | -171 |\n",
"| StdQ1Vals | 243 |\n",
"| MaxQ1Vals | 239 |\n",
"| MinQ1Vals | -1.15e+03 |\n",
"| AverageQ2Vals | -170 |\n",
"| StdQ2Vals | 243 |\n",
"| MaxQ2Vals | 246 |\n",
"| MinQ2Vals | -1.13e+03 |\n",
"| LossPi | 145 |\n",
"| LossQ | 1.29e+03 |\n",
"| Time | 555 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 24 |\n",
"| AverageEpRet | -714 |\n",
"| StdEpRet | 351 |\n",
"| MaxEpRet | -181 |\n",
"| MinEpRet | -1.29e+03 |\n",
"| AverageTestEpRet | -433 |\n",
"| StdTestEpRet | 184 |\n",
"| MaxTestEpRet | -178 |\n",
"| MinTestEpRet | -786 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 5.28e+04 |\n",
"| AverageQ1Vals | -164 |\n",
"| StdQ1Vals | 238 |\n",
"| MaxQ1Vals | 227 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -164 |\n",
"| StdQ2Vals | 238 |\n",
"| MaxQ2Vals | 229 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 139 |\n",
"| LossQ | 1.22e+03 |\n",
"| Time | 579 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 25 |\n",
"| AverageEpRet | -709 |\n",
"| StdEpRet | 425 |\n",
"| MaxEpRet | -88.8 |\n",
"| MinEpRet | -1.59e+03 |\n",
"| AverageTestEpRet | -808 |\n",
"| StdTestEpRet | 476 |\n",
"| MaxTestEpRet | -198 |\n",
"| MinTestEpRet | -1.81e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 5.5e+04 |\n",
"| AverageQ1Vals | -159 |\n",
"| StdQ1Vals | 233 |\n",
"| MaxQ1Vals | 209 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -159 |\n",
"| StdQ2Vals | 233 |\n",
"| MaxQ2Vals | 209 |\n",
"| MinQ2Vals | -1.13e+03 |\n",
"| LossPi | 136 |\n",
"| LossQ | 1.15e+03 |\n",
"| Time | 603 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 26 |\n",
"| AverageEpRet | -813 |\n",
"| StdEpRet | 433 |\n",
"| MaxEpRet | -247 |\n",
"| MinEpRet | -1.81e+03 |\n",
"| AverageTestEpRet | -702 |\n",
"| StdTestEpRet | 308 |\n",
"| MaxTestEpRet | -197 |\n",
"| MinTestEpRet | -1.43e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 5.72e+04 |\n",
"| AverageQ1Vals | -158 |\n",
"| StdQ1Vals | 231 |\n",
"| MaxQ1Vals | 194 |\n",
"| MinQ1Vals | -1.2e+03 |\n",
"| AverageQ2Vals | -158 |\n",
"| StdQ2Vals | 231 |\n",
"| MaxQ2Vals | 198 |\n",
"| MinQ2Vals | -1.17e+03 |\n",
"| LossPi | 136 |\n",
"| LossQ | 1.14e+03 |\n",
"| Time | 628 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 27 |\n",
"| AverageEpRet | -690 |\n",
"| StdEpRet | 282 |\n",
"| MaxEpRet | -336 |\n",
"| MinEpRet | -1.07e+03 |\n",
"| AverageTestEpRet | -934 |\n",
"| StdTestEpRet | 626 |\n",
"| MaxTestEpRet | -317 |\n",
"| MinTestEpRet | -2.24e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 5.94e+04 |\n",
"| AverageQ1Vals | -157 |\n",
"| StdQ1Vals | 229 |\n",
"| MaxQ1Vals | 190 |\n",
"| MinQ1Vals | -1.15e+03 |\n",
"| AverageQ2Vals | -157 |\n",
"| StdQ2Vals | 229 |\n",
"| MaxQ2Vals | 192 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 135 |\n",
"| LossQ | 1.03e+03 |\n",
"| Time | 653 |\n",
"---------------------------------------\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 28 |\n",
"| AverageEpRet | -965 |\n",
"| StdEpRet | 522 |\n",
"| MaxEpRet | -172 |\n",
"| MinEpRet | -2.3e+03 |\n",
"| AverageTestEpRet | -599 |\n",
"| StdTestEpRet | 398 |\n",
"| MaxTestEpRet | -163 |\n",
"| MinTestEpRet | -1.32e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 6.16e+04 |\n",
"| AverageQ1Vals | -154 |\n",
"| StdQ1Vals | 226 |\n",
"| MaxQ1Vals | 176 |\n",
"| MinQ1Vals | -1.12e+03 |\n",
"| AverageQ2Vals | -154 |\n",
"| StdQ2Vals | 226 |\n",
"| MaxQ2Vals | 188 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 133 |\n",
"| LossQ | 973 |\n",
"| Time | 677 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 29 |\n",
"| AverageEpRet | -766 |\n",
"| StdEpRet | 367 |\n",
"| MaxEpRet | -114 |\n",
"| MinEpRet | -1.69e+03 |\n",
"| AverageTestEpRet | -659 |\n",
"| StdTestEpRet | 229 |\n",
"| MaxTestEpRet | -303 |\n",
"| MinTestEpRet | -1.1e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 6.38e+04 |\n",
"| AverageQ1Vals | -153 |\n",
"| StdQ1Vals | 225 |\n",
"| MaxQ1Vals | 173 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -153 |\n",
"| StdQ2Vals | 225 |\n",
"| MaxQ2Vals | 176 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 133 |\n",
"| LossQ | 961 |\n",
"| Time | 702 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 30 |\n",
"| AverageEpRet | -682 |\n",
"| StdEpRet | 254 |\n",
"| MaxEpRet | -388 |\n",
"| MinEpRet | -1.46e+03 |\n",
"| AverageTestEpRet | -686 |\n",
"| StdTestEpRet | 188 |\n",
"| MaxTestEpRet | -312 |\n",
"| MinTestEpRet | -977 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 6.6e+04 |\n",
"| AverageQ1Vals | -151 |\n",
"| StdQ1Vals | 222 |\n",
"| MaxQ1Vals | 162 |\n",
"| MinQ1Vals | -1.2e+03 |\n",
"| AverageQ2Vals | -151 |\n",
"| StdQ2Vals | 222 |\n",
"| MaxQ2Vals | 159 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 131 |\n",
"| LossQ | 913 |\n",
"| Time | 727 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 31 |\n",
"| AverageEpRet | -676 |\n",
"| StdEpRet | 442 |\n",
"| MaxEpRet | -163 |\n",
"| MinEpRet | -1.84e+03 |\n",
"| AverageTestEpRet | -678 |\n",
"| StdTestEpRet | 371 |\n",
"| MaxTestEpRet | -156 |\n",
"| MinTestEpRet | -1.41e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 6.82e+04 |\n",
"| AverageQ1Vals | -149 |\n",
"| StdQ1Vals | 219 |\n",
"| MaxQ1Vals | 149 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -149 |\n",
"| StdQ2Vals | 219 |\n",
"| MaxQ2Vals | 153 |\n",
"| MinQ2Vals | -1.09e+03 |\n",
"| LossPi | 130 |\n",
"| LossQ | 855 |\n",
"| Time | 753 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 32 |\n",
"| AverageEpRet | -760 |\n",
"| StdEpRet | 313 |\n",
"| MaxEpRet | -216 |\n",
"| MinEpRet | -1.49e+03 |\n",
"| AverageTestEpRet | -759 |\n",
"| StdTestEpRet | 430 |\n",
"| MaxTestEpRet | -256 |\n",
"| MinTestEpRet | -1.64e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 7.04e+04 |\n",
"| AverageQ1Vals | -150 |\n",
"| StdQ1Vals | 217 |\n",
"| MaxQ1Vals | 146 |\n",
"| MinQ1Vals | -1.1e+03 |\n",
"| AverageQ2Vals | -150 |\n",
"| StdQ2Vals | 217 |\n",
"| MaxQ2Vals | 145 |\n",
"| MinQ2Vals | -1.11e+03 |\n",
"| LossPi | 130 |\n",
"| LossQ | 835 |\n",
"| Time | 775 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 33 |\n",
"| AverageEpRet | -527 |\n",
"| StdEpRet | 395 |\n",
"| MaxEpRet | -57.1 |\n",
"| MinEpRet | -1.4e+03 |\n",
"| AverageTestEpRet | -583 |\n",
"| StdTestEpRet | 368 |\n",
"| MaxTestEpRet | -120 |\n",
"| MinTestEpRet | -1.52e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 7.26e+04 |\n",
"| AverageQ1Vals | -147 |\n",
"| StdQ1Vals | 213 |\n",
"| MaxQ1Vals | 130 |\n",
"| MinQ1Vals | -1.11e+03 |\n",
"| AverageQ2Vals | -147 |\n",
"| StdQ2Vals | 213 |\n",
"| MaxQ2Vals | 125 |\n",
"| MinQ2Vals | -1.11e+03 |\n",
"| LossPi | 129 |\n",
"| LossQ | 800 |\n",
"| Time | 796 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 34 |\n",
"| AverageEpRet | -732 |\n",
"| StdEpRet | 361 |\n",
"| MaxEpRet | -114 |\n",
"| MinEpRet | -1.6e+03 |\n",
"| AverageTestEpRet | -737 |\n",
"| StdTestEpRet | 290 |\n",
"| MaxTestEpRet | -278 |\n",
"| MinTestEpRet | -1.25e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 7.48e+04 |\n",
"| AverageQ1Vals | -144 |\n",
"| StdQ1Vals | 211 |\n",
"| MaxQ1Vals | 133 |\n",
"| MinQ1Vals | -1.09e+03 |\n",
"| AverageQ2Vals | -144 |\n",
"| StdQ2Vals | 211 |\n",
"| MaxQ2Vals | 121 |\n",
"| MinQ2Vals | -1.1e+03 |\n",
"| LossPi | 126 |\n",
"| LossQ | 784 |\n",
"| Time | 820 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 35 |\n",
"| AverageEpRet | -682 |\n",
"| StdEpRet | 348 |\n",
"| MaxEpRet | -159 |\n",
"| MinEpRet | -1.58e+03 |\n",
"| AverageTestEpRet | -766 |\n",
"| StdTestEpRet | 358 |\n",
"| MaxTestEpRet | -85.9 |\n",
"| MinTestEpRet | -1.35e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 7.7e+04 |\n",
"| AverageQ1Vals | -143 |\n",
"| StdQ1Vals | 209 |\n",
"| MaxQ1Vals | 123 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -143 |\n",
"| StdQ2Vals | 209 |\n",
"| MaxQ2Vals | 107 |\n",
"| MinQ2Vals | -1.17e+03 |\n",
"| LossPi | 125 |\n",
"| LossQ | 730 |\n",
"| Time | 846 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 36 |\n",
"| AverageEpRet | -848 |\n",
"| StdEpRet | 733 |\n",
"| MaxEpRet | -216 |\n",
"| MinEpRet | -3.32e+03 |\n",
"| AverageTestEpRet | -765 |\n",
"| StdTestEpRet | 340 |\n",
"| MaxTestEpRet | -191 |\n",
"| MinTestEpRet | -1.48e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 7.92e+04 |\n",
"| AverageQ1Vals | -141 |\n",
"| StdQ1Vals | 207 |\n",
"| MaxQ1Vals | 115 |\n",
"| MinQ1Vals | -1.1e+03 |\n",
"| AverageQ2Vals | -141 |\n",
"| StdQ2Vals | 207 |\n",
"| MaxQ2Vals | 108 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 125 |\n",
"| LossQ | 703 |\n",
"| Time | 873 |\n",
"---------------------------------------\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 37 |\n",
"| AverageEpRet | -625 |\n",
"| StdEpRet | 379 |\n",
"| MaxEpRet | -11.3 |\n",
"| MinEpRet | -1.43e+03 |\n",
"| AverageTestEpRet | -646 |\n",
"| StdTestEpRet | 399 |\n",
"| MaxTestEpRet | -102 |\n",
"| MinTestEpRet | -1.15e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 8.14e+04 |\n",
"| AverageQ1Vals | -140 |\n",
"| StdQ1Vals | 204 |\n",
"| MaxQ1Vals | 103 |\n",
"| MinQ1Vals | -1.15e+03 |\n",
"| AverageQ2Vals | -140 |\n",
"| StdQ2Vals | 204 |\n",
"| MaxQ2Vals | 96.8 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 124 |\n",
"| LossQ | 667 |\n",
"| Time | 900 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 38 |\n",
"| AverageEpRet | -634 |\n",
"| StdEpRet | 304 |\n",
"| MaxEpRet | -44.1 |\n",
"| MinEpRet | -1.19e+03 |\n",
"| AverageTestEpRet | -716 |\n",
"| StdTestEpRet | 356 |\n",
"| MaxTestEpRet | -263 |\n",
"| MinTestEpRet | -1.49e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 8.36e+04 |\n",
"| AverageQ1Vals | -140 |\n",
"| StdQ1Vals | 203 |\n",
"| MaxQ1Vals | 91.8 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -140 |\n",
"| StdQ2Vals | 203 |\n",
"| MaxQ2Vals | 86 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 124 |\n",
"| LossQ | 664 |\n",
"| Time | 929 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 39 |\n",
"| AverageEpRet | -630 |\n",
"| StdEpRet | 375 |\n",
"| MaxEpRet | -127 |\n",
"| MinEpRet | -1.59e+03 |\n",
"| AverageTestEpRet | -591 |\n",
"| StdTestEpRet | 239 |\n",
"| MaxTestEpRet | -204 |\n",
"| MinTestEpRet | -946 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 8.58e+04 |\n",
"| AverageQ1Vals | -139 |\n",
"| StdQ1Vals | 201 |\n",
"| MaxQ1Vals | 86.8 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -139 |\n",
"| StdQ2Vals | 201 |\n",
"| MaxQ2Vals | 77.3 |\n",
"| MinQ2Vals | -1.11e+03 |\n",
"| LossPi | 124 |\n",
"| LossQ | 649 |\n",
"| Time | 960 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 40 |\n",
"| AverageEpRet | -506 |\n",
"| StdEpRet | 280 |\n",
"| MaxEpRet | -67.2 |\n",
"| MinEpRet | -1.18e+03 |\n",
"| AverageTestEpRet | -621 |\n",
"| StdTestEpRet | 351 |\n",
"| MaxTestEpRet | -171 |\n",
"| MinTestEpRet | -1.07e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 8.8e+04 |\n",
"| AverageQ1Vals | -137 |\n",
"| StdQ1Vals | 199 |\n",
"| MaxQ1Vals | 77.5 |\n",
"| MinQ1Vals | -1.21e+03 |\n",
"| AverageQ2Vals | -137 |\n",
"| StdQ2Vals | 199 |\n",
"| MaxQ2Vals | 66.2 |\n",
"| MinQ2Vals | -1.21e+03 |\n",
"| LossPi | 122 |\n",
"| LossQ | 629 |\n",
"| Time | 991 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 41 |\n",
"| AverageEpRet | -676 |\n",
"| StdEpRet | 301 |\n",
"| MaxEpRet | -182 |\n",
"| MinEpRet | -1.31e+03 |\n",
"| AverageTestEpRet | -784 |\n",
"| StdTestEpRet | 309 |\n",
"| MaxTestEpRet | -408 |\n",
"| MinTestEpRet | -1.4e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 9.02e+04 |\n",
"| AverageQ1Vals | -136 |\n",
"| StdQ1Vals | 197 |\n",
"| MaxQ1Vals | 74.4 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -136 |\n",
"| StdQ2Vals | 197 |\n",
"| MaxQ2Vals | 74.3 |\n",
"| MinQ2Vals | -1.12e+03 |\n",
"| LossPi | 121 |\n",
"| LossQ | 587 |\n",
"| Time | 1.02e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 42 |\n",
"| AverageEpRet | -623 |\n",
"| StdEpRet | 295 |\n",
"| MaxEpRet | -69.3 |\n",
"| MinEpRet | -1.19e+03 |\n",
"| AverageTestEpRet | -806 |\n",
"| StdTestEpRet | 386 |\n",
"| MaxTestEpRet | -285 |\n",
"| MinTestEpRet | -1.63e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 9.24e+04 |\n",
"| AverageQ1Vals | -134 |\n",
"| StdQ1Vals | 196 |\n",
"| MaxQ1Vals | 59.5 |\n",
"| MinQ1Vals | -1.13e+03 |\n",
"| AverageQ2Vals | -134 |\n",
"| StdQ2Vals | 196 |\n",
"| MaxQ2Vals | 67.8 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 120 |\n",
"| LossQ | 584 |\n",
"| Time | 1.05e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 43 |\n",
"| AverageEpRet | -565 |\n",
"| StdEpRet | 255 |\n",
"| MaxEpRet | -79.6 |\n",
"| MinEpRet | -1.08e+03 |\n",
"| AverageTestEpRet | -620 |\n",
"| StdTestEpRet | 300 |\n",
"| MaxTestEpRet | -160 |\n",
"| MinTestEpRet | -971 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 9.46e+04 |\n",
"| AverageQ1Vals | -133 |\n",
"| StdQ1Vals | 194 |\n",
"| MaxQ1Vals | 63.5 |\n",
"| MinQ1Vals | -1.17e+03 |\n",
"| AverageQ2Vals | -133 |\n",
"| StdQ2Vals | 194 |\n",
"| MaxQ2Vals | 68.2 |\n",
"| MinQ2Vals | -1.12e+03 |\n",
"| LossPi | 118 |\n",
"| LossQ | 561 |\n",
"| Time | 1.08e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 44 |\n",
"| AverageEpRet | -583 |\n",
"| StdEpRet | 247 |\n",
"| MaxEpRet | -63.3 |\n",
"| MinEpRet | -1.08e+03 |\n",
"| AverageTestEpRet | -507 |\n",
"| StdTestEpRet | 296 |\n",
"| MaxTestEpRet | -107 |\n",
"| MinTestEpRet | -996 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 9.68e+04 |\n",
"| AverageQ1Vals | -132 |\n",
"| StdQ1Vals | 191 |\n",
"| MaxQ1Vals | 49.2 |\n",
"| MinQ1Vals | -1.18e+03 |\n",
"| AverageQ2Vals | -132 |\n",
"| StdQ2Vals | 191 |\n",
"| MaxQ2Vals | 49.2 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 118 |\n",
"| LossQ | 532 |\n",
"| Time | 1.11e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 45 |\n",
"| AverageEpRet | -608 |\n",
"| StdEpRet | 309 |\n",
"| MaxEpRet | -147 |\n",
"| MinEpRet | -1.23e+03 |\n",
"| AverageTestEpRet | -727 |\n",
"| StdTestEpRet | 348 |\n",
"| MaxTestEpRet | -203 |\n",
"| MinTestEpRet | -1.43e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 9.9e+04 |\n",
"| AverageQ1Vals | -129 |\n",
"| StdQ1Vals | 187 |\n",
"| MaxQ1Vals | 50.6 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -129 |\n",
"| StdQ2Vals | 187 |\n",
"| MaxQ2Vals | 47.9 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 116 |\n",
"| LossQ | 517 |\n",
"| Time | 1.14e+03 |\n",
"---------------------------------------\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 46 |\n",
"| AverageEpRet | -649 |\n",
"| StdEpRet | 325 |\n",
"| MaxEpRet | -151 |\n",
"| MinEpRet | -1.5e+03 |\n",
"| AverageTestEpRet | -647 |\n",
"| StdTestEpRet | 317 |\n",
"| MaxTestEpRet | -219 |\n",
"| MinTestEpRet | -1.25e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.01e+05 |\n",
"| AverageQ1Vals | -129 |\n",
"| StdQ1Vals | 187 |\n",
"| MaxQ1Vals | 49.8 |\n",
"| MinQ1Vals | -1.1e+03 |\n",
"| AverageQ2Vals | -129 |\n",
"| StdQ2Vals | 187 |\n",
"| MaxQ2Vals | 90.9 |\n",
"| MinQ2Vals | -1.11e+03 |\n",
"| LossPi | 115 |\n",
"| LossQ | 514 |\n",
"| Time | 1.18e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 47 |\n",
"| AverageEpRet | -444 |\n",
"| StdEpRet | 183 |\n",
"| MaxEpRet | -183 |\n",
"| MinEpRet | -968 |\n",
"| AverageTestEpRet | -669 |\n",
"| StdTestEpRet | 245 |\n",
"| MaxTestEpRet | -261 |\n",
"| MinTestEpRet | -1.12e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.03e+05 |\n",
"| AverageQ1Vals | -127 |\n",
"| StdQ1Vals | 185 |\n",
"| MaxQ1Vals | 58.8 |\n",
"| MinQ1Vals | -1.15e+03 |\n",
"| AverageQ2Vals | -127 |\n",
"| StdQ2Vals | 185 |\n",
"| MaxQ2Vals | 55.1 |\n",
"| MinQ2Vals | -1.15e+03 |\n",
"| LossPi | 113 |\n",
"| LossQ | 489 |\n",
"| Time | 1.21e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 48 |\n",
"| AverageEpRet | -673 |\n",
"| StdEpRet | 332 |\n",
"| MaxEpRet | -125 |\n",
"| MinEpRet | -1.41e+03 |\n",
"| AverageTestEpRet | -534 |\n",
"| StdTestEpRet | 252 |\n",
"| MaxTestEpRet | -167 |\n",
"| MinTestEpRet | -1.04e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.06e+05 |\n",
"| AverageQ1Vals | -125 |\n",
"| StdQ1Vals | 182 |\n",
"| MaxQ1Vals | 96.2 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -125 |\n",
"| StdQ2Vals | 182 |\n",
"| MaxQ2Vals | 93.5 |\n",
"| MinQ2Vals | -1.18e+03 |\n",
"| LossPi | 112 |\n",
"| LossQ | 473 |\n",
"| Time | 1.24e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 49 |\n",
"| AverageEpRet | -475 |\n",
"| StdEpRet | 243 |\n",
"| MaxEpRet | -125 |\n",
"| MinEpRet | -1.11e+03 |\n",
"| AverageTestEpRet | -572 |\n",
"| StdTestEpRet | 339 |\n",
"| MaxTestEpRet | -155 |\n",
"| MinTestEpRet | -1.25e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.08e+05 |\n",
"| AverageQ1Vals | -124 |\n",
"| StdQ1Vals | 181 |\n",
"| MaxQ1Vals | 66.2 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -124 |\n",
"| StdQ2Vals | 181 |\n",
"| MaxQ2Vals | 60.6 |\n",
"| MinQ2Vals | -1.11e+03 |\n",
"| LossPi | 112 |\n",
"| LossQ | 466 |\n",
"| Time | 1.27e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 50 |\n",
"| AverageEpRet | -581 |\n",
"| StdEpRet | 358 |\n",
"| MaxEpRet | -121 |\n",
"| MinEpRet | -1.34e+03 |\n",
"| AverageTestEpRet | -687 |\n",
"| StdTestEpRet | 246 |\n",
"| MaxTestEpRet | -246 |\n",
"| MinTestEpRet | -1.07e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.1e+05 |\n",
"| AverageQ1Vals | -122 |\n",
"| StdQ1Vals | 179 |\n",
"| MaxQ1Vals | 40.6 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -122 |\n",
"| StdQ2Vals | 179 |\n",
"| MaxQ2Vals | 50.9 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 109 |\n",
"| LossQ | 439 |\n",
"| Time | 1.31e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 51 |\n",
"| AverageEpRet | -599 |\n",
"| StdEpRet | 287 |\n",
"| MaxEpRet | -232 |\n",
"| MinEpRet | -1.44e+03 |\n",
"| AverageTestEpRet | -561 |\n",
"| StdTestEpRet | 204 |\n",
"| MaxTestEpRet | -216 |\n",
"| MinTestEpRet | -856 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.12e+05 |\n",
"| AverageQ1Vals | -122 |\n",
"| StdQ1Vals | 179 |\n",
"| MaxQ1Vals | 78.3 |\n",
"| MinQ1Vals | -1.12e+03 |\n",
"| AverageQ2Vals | -122 |\n",
"| StdQ2Vals | 179 |\n",
"| MaxQ2Vals | 76.5 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 110 |\n",
"| LossQ | 437 |\n",
"| Time | 1.34e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 52 |\n",
"| AverageEpRet | -636 |\n",
"| StdEpRet | 283 |\n",
"| MaxEpRet | -220 |\n",
"| MinEpRet | -1.12e+03 |\n",
"| AverageTestEpRet | -712 |\n",
"| StdTestEpRet | 185 |\n",
"| MaxTestEpRet | -457 |\n",
"| MinTestEpRet | -1.09e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.14e+05 |\n",
"| AverageQ1Vals | -121 |\n",
"| StdQ1Vals | 178 |\n",
"| MaxQ1Vals | 58.8 |\n",
"| MinQ1Vals | -1.17e+03 |\n",
"| AverageQ2Vals | -121 |\n",
"| StdQ2Vals | 178 |\n",
"| MaxQ2Vals | 54.7 |\n",
"| MinQ2Vals | -1.17e+03 |\n",
"| LossPi | 109 |\n",
"| LossQ | 431 |\n",
"| Time | 1.37e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 53 |\n",
"| AverageEpRet | -591 |\n",
"| StdEpRet | 351 |\n",
"| MaxEpRet | -132 |\n",
"| MinEpRet | -1.43e+03 |\n",
"| AverageTestEpRet | -551 |\n",
"| StdTestEpRet | 206 |\n",
"| MaxTestEpRet | -333 |\n",
"| MinTestEpRet | -975 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.17e+05 |\n",
"| AverageQ1Vals | -119 |\n",
"| StdQ1Vals | 176 |\n",
"| MaxQ1Vals | 54.4 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -119 |\n",
"| StdQ2Vals | 176 |\n",
"| MaxQ2Vals | 89.1 |\n",
"| MinQ2Vals | -1.18e+03 |\n",
"| LossPi | 108 |\n",
"| LossQ | 418 |\n",
"| Time | 1.4e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 54 |\n",
"| AverageEpRet | -426 |\n",
"| StdEpRet | 230 |\n",
"| MaxEpRet | -90.2 |\n",
"| MinEpRet | -906 |\n",
"| AverageTestEpRet | -447 |\n",
"| StdTestEpRet | 197 |\n",
"| MaxTestEpRet | -124 |\n",
"| MinTestEpRet | -708 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.19e+05 |\n",
"| AverageQ1Vals | -118 |\n",
"| StdQ1Vals | 175 |\n",
"| MaxQ1Vals | 47.2 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -118 |\n",
"| StdQ2Vals | 175 |\n",
"| MaxQ2Vals | 80 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 106 |\n",
"| LossQ | 401 |\n",
"| Time | 1.43e+03 |\n",
"---------------------------------------\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 55 |\n",
"| AverageEpRet | -503 |\n",
"| StdEpRet | 235 |\n",
"| MaxEpRet | -110 |\n",
"| MinEpRet | -939 |\n",
"| AverageTestEpRet | -615 |\n",
"| StdTestEpRet | 194 |\n",
"| MaxTestEpRet | -400 |\n",
"| MinTestEpRet | -952 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.21e+05 |\n",
"| AverageQ1Vals | -118 |\n",
"| StdQ1Vals | 174 |\n",
"| MaxQ1Vals | 54.2 |\n",
"| MinQ1Vals | -1.19e+03 |\n",
"| AverageQ2Vals | -118 |\n",
"| StdQ2Vals | 174 |\n",
"| MaxQ2Vals | 68.6 |\n",
"| MinQ2Vals | -1.15e+03 |\n",
"| LossPi | 106 |\n",
"| LossQ | 392 |\n",
"| Time | 1.47e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 56 |\n",
"| AverageEpRet | -552 |\n",
"| StdEpRet | 234 |\n",
"| MaxEpRet | -228 |\n",
"| MinEpRet | -969 |\n",
"| AverageTestEpRet | -400 |\n",
"| StdTestEpRet | 293 |\n",
"| MaxTestEpRet | -66.3 |\n",
"| MinTestEpRet | -1.1e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.23e+05 |\n",
"| AverageQ1Vals | -117 |\n",
"| StdQ1Vals | 173 |\n",
"| MaxQ1Vals | 66.1 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -117 |\n",
"| StdQ2Vals | 173 |\n",
"| MaxQ2Vals | 69.5 |\n",
"| MinQ2Vals | -1.13e+03 |\n",
"| LossPi | 105 |\n",
"| LossQ | 400 |\n",
"| Time | 1.5e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 57 |\n",
"| AverageEpRet | -476 |\n",
"| StdEpRet | 318 |\n",
"| MaxEpRet | -33.7 |\n",
"| MinEpRet | -1.13e+03 |\n",
"| AverageTestEpRet | -480 |\n",
"| StdTestEpRet | 210 |\n",
"| MaxTestEpRet | -197 |\n",
"| MinTestEpRet | -802 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.25e+05 |\n",
"| AverageQ1Vals | -114 |\n",
"| StdQ1Vals | 171 |\n",
"| MaxQ1Vals | 68.5 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -114 |\n",
"| StdQ2Vals | 171 |\n",
"| MaxQ2Vals | 68.8 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 103 |\n",
"| LossQ | 380 |\n",
"| Time | 1.53e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 58 |\n",
"| AverageEpRet | -590 |\n",
"| StdEpRet | 261 |\n",
"| MaxEpRet | -113 |\n",
"| MinEpRet | -1.32e+03 |\n",
"| AverageTestEpRet | -519 |\n",
"| StdTestEpRet | 234 |\n",
"| MaxTestEpRet | -206 |\n",
"| MinTestEpRet | -935 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.28e+05 |\n",
"| AverageQ1Vals | -113 |\n",
"| StdQ1Vals | 170 |\n",
"| MaxQ1Vals | 72.9 |\n",
"| MinQ1Vals | -1.12e+03 |\n",
"| AverageQ2Vals | -113 |\n",
"| StdQ2Vals | 170 |\n",
"| MaxQ2Vals | 51.6 |\n",
"| MinQ2Vals | -1.09e+03 |\n",
"| LossPi | 102 |\n",
"| LossQ | 368 |\n",
"| Time | 1.56e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 59 |\n",
"| AverageEpRet | -588 |\n",
"| StdEpRet | 220 |\n",
"| MaxEpRet | -170 |\n",
"| MinEpRet | -1.05e+03 |\n",
"| AverageTestEpRet | -467 |\n",
"| StdTestEpRet | 182 |\n",
"| MaxTestEpRet | -212 |\n",
"| MinTestEpRet | -763 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.3e+05 |\n",
"| AverageQ1Vals | -112 |\n",
"| StdQ1Vals | 169 |\n",
"| MaxQ1Vals | 64.5 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -112 |\n",
"| StdQ2Vals | 169 |\n",
"| MaxQ2Vals | 93.3 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 102 |\n",
"| LossQ | 367 |\n",
"| Time | 1.6e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 60 |\n",
"| AverageEpRet | -495 |\n",
"| StdEpRet | 358 |\n",
"| MaxEpRet | -44.8 |\n",
"| MinEpRet | -1.71e+03 |\n",
"| AverageTestEpRet | -654 |\n",
"| StdTestEpRet | 261 |\n",
"| MaxTestEpRet | -227 |\n",
"| MinTestEpRet | -1.05e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.32e+05 |\n",
"| AverageQ1Vals | -112 |\n",
"| StdQ1Vals | 168 |\n",
"| MaxQ1Vals | 68.9 |\n",
"| MinQ1Vals | -1.18e+03 |\n",
"| AverageQ2Vals | -112 |\n",
"| StdQ2Vals | 168 |\n",
"| MaxQ2Vals | 73.7 |\n",
"| MinQ2Vals | -1.15e+03 |\n",
"| LossPi | 101 |\n",
"| LossQ | 363 |\n",
"| Time | 1.63e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 61 |\n",
"| AverageEpRet | -690 |\n",
"| StdEpRet | 376 |\n",
"| MaxEpRet | -74.9 |\n",
"| MinEpRet | -1.45e+03 |\n",
"| AverageTestEpRet | -574 |\n",
"| StdTestEpRet | 410 |\n",
"| MaxTestEpRet | -144 |\n",
"| MinTestEpRet | -1.57e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.34e+05 |\n",
"| AverageQ1Vals | -110 |\n",
"| StdQ1Vals | 166 |\n",
"| MaxQ1Vals | 49.8 |\n",
"| MinQ1Vals | -1.18e+03 |\n",
"| AverageQ2Vals | -110 |\n",
"| StdQ2Vals | 166 |\n",
"| MaxQ2Vals | 52.8 |\n",
"| MinQ2Vals | -1.17e+03 |\n",
"| LossPi | 100 |\n",
"| LossQ | 349 |\n",
"| Time | 1.66e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 62 |\n",
"| AverageEpRet | -487 |\n",
"| StdEpRet | 280 |\n",
"| MaxEpRet | -116 |\n",
"| MinEpRet | -1.24e+03 |\n",
"| AverageTestEpRet | -485 |\n",
"| StdTestEpRet | 247 |\n",
"| MaxTestEpRet | -146 |\n",
"| MinTestEpRet | -886 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.36e+05 |\n",
"| AverageQ1Vals | -109 |\n",
"| StdQ1Vals | 165 |\n",
"| MaxQ1Vals | 67.9 |\n",
"| MinQ1Vals | -1.17e+03 |\n",
"| AverageQ2Vals | -109 |\n",
"| StdQ2Vals | 165 |\n",
"| MaxQ2Vals | 44.4 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 98.7 |\n",
"| LossQ | 358 |\n",
"| Time | 1.7e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 63 |\n",
"| AverageEpRet | -448 |\n",
"| StdEpRet | 251 |\n",
"| MaxEpRet | -56.4 |\n",
"| MinEpRet | -1.16e+03 |\n",
"| AverageTestEpRet | -341 |\n",
"| StdTestEpRet | 181 |\n",
"| MaxTestEpRet | -63.6 |\n",
"| MinTestEpRet | -608 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.39e+05 |\n",
"| AverageQ1Vals | -108 |\n",
"| StdQ1Vals | 165 |\n",
"| MaxQ1Vals | 55.3 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -108 |\n",
"| StdQ2Vals | 165 |\n",
"| MaxQ2Vals | 52.7 |\n",
"| MinQ2Vals | -1.13e+03 |\n",
"| LossPi | 97.8 |\n",
"| LossQ | 344 |\n",
"| Time | 1.73e+03 |\n",
"---------------------------------------\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 64 |\n",
"| AverageEpRet | -525 |\n",
"| StdEpRet | 226 |\n",
"| MaxEpRet | -189 |\n",
"| MinEpRet | -1.16e+03 |\n",
"| AverageTestEpRet | -532 |\n",
"| StdTestEpRet | 182 |\n",
"| MaxTestEpRet | -302 |\n",
"| MinTestEpRet | -824 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.41e+05 |\n",
"| AverageQ1Vals | -106 |\n",
"| StdQ1Vals | 164 |\n",
"| MaxQ1Vals | 50.1 |\n",
"| MinQ1Vals | -1.13e+03 |\n",
"| AverageQ2Vals | -106 |\n",
"| StdQ2Vals | 164 |\n",
"| MaxQ2Vals | 37.7 |\n",
"| MinQ2Vals | -1.13e+03 |\n",
"| LossPi | 95.7 |\n",
"| LossQ | 340 |\n",
"| Time | 1.76e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 65 |\n",
"| AverageEpRet | -470 |\n",
"| StdEpRet | 277 |\n",
"| MaxEpRet | -31.2 |\n",
"| MinEpRet | -1.01e+03 |\n",
"| AverageTestEpRet | -520 |\n",
"| StdTestEpRet | 359 |\n",
"| MaxTestEpRet | -127 |\n",
"| MinTestEpRet | -1.51e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.43e+05 |\n",
"| AverageQ1Vals | -105 |\n",
"| StdQ1Vals | 162 |\n",
"| MaxQ1Vals | 58.3 |\n",
"| MinQ1Vals | -1.22e+03 |\n",
"| AverageQ2Vals | -105 |\n",
"| StdQ2Vals | 162 |\n",
"| MaxQ2Vals | 51.6 |\n",
"| MinQ2Vals | -1.2e+03 |\n",
"| LossPi | 95.2 |\n",
"| LossQ | 329 |\n",
"| Time | 1.79e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 66 |\n",
"| AverageEpRet | -622 |\n",
"| StdEpRet | 284 |\n",
"| MaxEpRet | -126 |\n",
"| MinEpRet | -1.33e+03 |\n",
"| AverageTestEpRet | -525 |\n",
"| StdTestEpRet | 239 |\n",
"| MaxTestEpRet | -224 |\n",
"| MinTestEpRet | -1.01e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.45e+05 |\n",
"| AverageQ1Vals | -104 |\n",
"| StdQ1Vals | 163 |\n",
"| MaxQ1Vals | 46.5 |\n",
"| MinQ1Vals | -1.17e+03 |\n",
"| AverageQ2Vals | -104 |\n",
"| StdQ2Vals | 163 |\n",
"| MaxQ2Vals | 73.2 |\n",
"| MinQ2Vals | -1.19e+03 |\n",
"| LossPi | 94.4 |\n",
"| LossQ | 329 |\n",
"| Time | 1.83e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 67 |\n",
"| AverageEpRet | -483 |\n",
"| StdEpRet | 204 |\n",
"| MaxEpRet | -118 |\n",
"| MinEpRet | -836 |\n",
"| AverageTestEpRet | -530 |\n",
"| StdTestEpRet | 231 |\n",
"| MaxTestEpRet | -156 |\n",
"| MinTestEpRet | -994 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.47e+05 |\n",
"| AverageQ1Vals | -103 |\n",
"| StdQ1Vals | 161 |\n",
"| MaxQ1Vals | 56 |\n",
"| MinQ1Vals | -1.22e+03 |\n",
"| AverageQ2Vals | -103 |\n",
"| StdQ2Vals | 161 |\n",
"| MaxQ2Vals | 80 |\n",
"| MinQ2Vals | -1.24e+03 |\n",
"| LossPi | 93.2 |\n",
"| LossQ | 325 |\n",
"| Time | 1.86e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 68 |\n",
"| AverageEpRet | -443 |\n",
"| StdEpRet | 266 |\n",
"| MaxEpRet | -17.7 |\n",
"| MinEpRet | -926 |\n",
"| AverageTestEpRet | -498 |\n",
"| StdTestEpRet | 213 |\n",
"| MaxTestEpRet | -224 |\n",
"| MinTestEpRet | -779 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.5e+05 |\n",
"| AverageQ1Vals | -101 |\n",
"| StdQ1Vals | 160 |\n",
"| MaxQ1Vals | 71.7 |\n",
"| MinQ1Vals | -1.13e+03 |\n",
"| AverageQ2Vals | -101 |\n",
"| StdQ2Vals | 160 |\n",
"| MaxQ2Vals | 76.3 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 91.3 |\n",
"| LossQ | 311 |\n",
"| Time | 1.89e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 69 |\n",
"| AverageEpRet | -542 |\n",
"| StdEpRet | 422 |\n",
"| MaxEpRet | -74.6 |\n",
"| MinEpRet | -1.84e+03 |\n",
"| AverageTestEpRet | -466 |\n",
"| StdTestEpRet | 205 |\n",
"| MaxTestEpRet | -134 |\n",
"| MinTestEpRet | -905 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.52e+05 |\n",
"| AverageQ1Vals | -101 |\n",
"| StdQ1Vals | 160 |\n",
"| MaxQ1Vals | 57.9 |\n",
"| MinQ1Vals | -1.19e+03 |\n",
"| AverageQ2Vals | -101 |\n",
"| StdQ2Vals | 160 |\n",
"| MaxQ2Vals | 106 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 91.1 |\n",
"| LossQ | 315 |\n",
"| Time | 1.92e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 70 |\n",
"| AverageEpRet | -556 |\n",
"| StdEpRet | 188 |\n",
"| MaxEpRet | -166 |\n",
"| MinEpRet | -827 |\n",
"| AverageTestEpRet | -466 |\n",
"| StdTestEpRet | 163 |\n",
"| MaxTestEpRet | -247 |\n",
"| MinTestEpRet | -782 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.54e+05 |\n",
"| AverageQ1Vals | -98.9 |\n",
"| StdQ1Vals | 158 |\n",
"| MaxQ1Vals | 55.3 |\n",
"| MinQ1Vals | -1.2e+03 |\n",
"| AverageQ2Vals | -98.9 |\n",
"| StdQ2Vals | 158 |\n",
"| MaxQ2Vals | 104 |\n",
"| MinQ2Vals | -1.19e+03 |\n",
"| LossPi | 89.6 |\n",
"| LossQ | 298 |\n",
"| Time | 1.96e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 71 |\n",
"| AverageEpRet | -508 |\n",
"| StdEpRet | 360 |\n",
"| MaxEpRet | -116 |\n",
"| MinEpRet | -1.65e+03 |\n",
"| AverageTestEpRet | -503 |\n",
"| StdTestEpRet | 290 |\n",
"| MaxTestEpRet | -98.4 |\n",
"| MinTestEpRet | -933 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.56e+05 |\n",
"| AverageQ1Vals | -98.9 |\n",
"| StdQ1Vals | 158 |\n",
"| MaxQ1Vals | 68.3 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -98.9 |\n",
"| StdQ2Vals | 158 |\n",
"| MaxQ2Vals | 62.4 |\n",
"| MinQ2Vals | -1.17e+03 |\n",
"| LossPi | 89.9 |\n",
"| LossQ | 310 |\n",
"| Time | 1.98e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 72 |\n",
"| AverageEpRet | -565 |\n",
"| StdEpRet | 254 |\n",
"| MaxEpRet | -154 |\n",
"| MinEpRet | -1.08e+03 |\n",
"| AverageTestEpRet | -595 |\n",
"| StdTestEpRet | 299 |\n",
"| MaxTestEpRet | -224 |\n",
"| MinTestEpRet | -1.16e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.58e+05 |\n",
"| AverageQ1Vals | -98.4 |\n",
"| StdQ1Vals | 157 |\n",
"| MaxQ1Vals | 40.1 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -98.4 |\n",
"| StdQ2Vals | 157 |\n",
"| MaxQ2Vals | 65.8 |\n",
"| MinQ2Vals | -1.17e+03 |\n",
"| LossPi | 89.2 |\n",
"| LossQ | 307 |\n",
"| Time | 2.01e+03 |\n",
"---------------------------------------\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 73 |\n",
"| AverageEpRet | -531 |\n",
"| StdEpRet | 253 |\n",
"| MaxEpRet | -152 |\n",
"| MinEpRet | -1.18e+03 |\n",
"| AverageTestEpRet | -403 |\n",
"| StdTestEpRet | 239 |\n",
"| MaxTestEpRet | -66.2 |\n",
"| MinTestEpRet | -865 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.61e+05 |\n",
"| AverageQ1Vals | -98 |\n",
"| StdQ1Vals | 156 |\n",
"| MaxQ1Vals | 123 |\n",
"| MinQ1Vals | -1.18e+03 |\n",
"| AverageQ2Vals | -98 |\n",
"| StdQ2Vals | 156 |\n",
"| MaxQ2Vals | 61.2 |\n",
"| MinQ2Vals | -1.17e+03 |\n",
"| LossPi | 89.2 |\n",
"| LossQ | 290 |\n",
"| Time | 2.05e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 74 |\n",
"| AverageEpRet | -608 |\n",
"| StdEpRet | 225 |\n",
"| MaxEpRet | -242 |\n",
"| MinEpRet | -1.07e+03 |\n",
"| AverageTestEpRet | -421 |\n",
"| StdTestEpRet | 224 |\n",
"| MaxTestEpRet | -127 |\n",
"| MinTestEpRet | -972 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.63e+05 |\n",
"| AverageQ1Vals | -96.8 |\n",
"| StdQ1Vals | 154 |\n",
"| MaxQ1Vals | 84.5 |\n",
"| MinQ1Vals | -1.11e+03 |\n",
"| AverageQ2Vals | -96.8 |\n",
"| StdQ2Vals | 154 |\n",
"| MaxQ2Vals | 44 |\n",
"| MinQ2Vals | -1.13e+03 |\n",
"| LossPi | 87.6 |\n",
"| LossQ | 280 |\n",
"| Time | 2.08e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 75 |\n",
"| AverageEpRet | -438 |\n",
"| StdEpRet | 207 |\n",
"| MaxEpRet | -103 |\n",
"| MinEpRet | -930 |\n",
"| AverageTestEpRet | -416 |\n",
"| StdTestEpRet | 241 |\n",
"| MaxTestEpRet | -135 |\n",
"| MinTestEpRet | -887 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.65e+05 |\n",
"| AverageQ1Vals | -96.7 |\n",
"| StdQ1Vals | 155 |\n",
"| MaxQ1Vals | 72.5 |\n",
"| MinQ1Vals | -1.13e+03 |\n",
"| AverageQ2Vals | -96.7 |\n",
"| StdQ2Vals | 155 |\n",
"| MaxQ2Vals | 75.7 |\n",
"| MinQ2Vals | -1.2e+03 |\n",
"| LossPi | 88.1 |\n",
"| LossQ | 285 |\n",
"| Time | 2.11e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 76 |\n",
"| AverageEpRet | -639 |\n",
"| StdEpRet | 315 |\n",
"| MaxEpRet | -214 |\n",
"| MinEpRet | -1.51e+03 |\n",
"| AverageTestEpRet | -437 |\n",
"| StdTestEpRet | 268 |\n",
"| MaxTestEpRet | -19.2 |\n",
"| MinTestEpRet | -1.04e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.67e+05 |\n",
"| AverageQ1Vals | -95.7 |\n",
"| StdQ1Vals | 153 |\n",
"| MaxQ1Vals | 48.5 |\n",
"| MinQ1Vals | -1.18e+03 |\n",
"| AverageQ2Vals | -95.7 |\n",
"| StdQ2Vals | 153 |\n",
"| MaxQ2Vals | 46.2 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 86.8 |\n",
"| LossQ | 285 |\n",
"| Time | 2.14e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 77 |\n",
"| AverageEpRet | -468 |\n",
"| StdEpRet | 228 |\n",
"| MaxEpRet | -125 |\n",
"| MinEpRet | -901 |\n",
"| AverageTestEpRet | -556 |\n",
"| StdTestEpRet | 262 |\n",
"| MaxTestEpRet | -148 |\n",
"| MinTestEpRet | -812 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.69e+05 |\n",
"| AverageQ1Vals | -95.7 |\n",
"| StdQ1Vals | 153 |\n",
"| MaxQ1Vals | 37.2 |\n",
"| MinQ1Vals | -1.17e+03 |\n",
"| AverageQ2Vals | -95.7 |\n",
"| StdQ2Vals | 153 |\n",
"| MaxQ2Vals | 49.4 |\n",
"| MinQ2Vals | -1.13e+03 |\n",
"| LossPi | 86.9 |\n",
"| LossQ | 283 |\n",
"| Time | 2.18e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 78 |\n",
"| AverageEpRet | -568 |\n",
"| StdEpRet | 284 |\n",
"| MaxEpRet | -123 |\n",
"| MinEpRet | -1.27e+03 |\n",
"| AverageTestEpRet | -550 |\n",
"| StdTestEpRet | 360 |\n",
"| MaxTestEpRet | -164 |\n",
"| MinTestEpRet | -1.26e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.72e+05 |\n",
"| AverageQ1Vals | -94.5 |\n",
"| StdQ1Vals | 151 |\n",
"| MaxQ1Vals | 47.8 |\n",
"| MinQ1Vals | -1.2e+03 |\n",
"| AverageQ2Vals | -94.5 |\n",
"| StdQ2Vals | 151 |\n",
"| MaxQ2Vals | 92 |\n",
"| MinQ2Vals | -1.18e+03 |\n",
"| LossPi | 85.9 |\n",
"| LossQ | 265 |\n",
"| Time | 2.21e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 79 |\n",
"| AverageEpRet | -566 |\n",
"| StdEpRet | 337 |\n",
"| MaxEpRet | -96.5 |\n",
"| MinEpRet | -1.45e+03 |\n",
"| AverageTestEpRet | -543 |\n",
"| StdTestEpRet | 365 |\n",
"| MaxTestEpRet | -134 |\n",
"| MinTestEpRet | -1.41e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.74e+05 |\n",
"| AverageQ1Vals | -94.8 |\n",
"| StdQ1Vals | 151 |\n",
"| MaxQ1Vals | 69.7 |\n",
"| MinQ1Vals | -1.21e+03 |\n",
"| AverageQ2Vals | -94.8 |\n",
"| StdQ2Vals | 151 |\n",
"| MaxQ2Vals | 75.6 |\n",
"| MinQ2Vals | -1.21e+03 |\n",
"| LossPi | 86.4 |\n",
"| LossQ | 278 |\n",
"| Time | 2.24e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 80 |\n",
"| AverageEpRet | -616 |\n",
"| StdEpRet | 290 |\n",
"| MaxEpRet | -114 |\n",
"| MinEpRet | -1.16e+03 |\n",
"| AverageTestEpRet | -447 |\n",
"| StdTestEpRet | 196 |\n",
"| MaxTestEpRet | -182 |\n",
"| MinTestEpRet | -783 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.76e+05 |\n",
"| AverageQ1Vals | -94.6 |\n",
"| StdQ1Vals | 151 |\n",
"| MaxQ1Vals | 59.6 |\n",
"| MinQ1Vals | -1.13e+03 |\n",
"| AverageQ2Vals | -94.6 |\n",
"| StdQ2Vals | 151 |\n",
"| MaxQ2Vals | 74.6 |\n",
"| MinQ2Vals | -1.13e+03 |\n",
"| LossPi | 86.4 |\n",
"| LossQ | 271 |\n",
"| Time | 2.28e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 81 |\n",
"| AverageEpRet | -535 |\n",
"| StdEpRet | 217 |\n",
"| MaxEpRet | -131 |\n",
"| MinEpRet | -999 |\n",
"| AverageTestEpRet | -422 |\n",
"| StdTestEpRet | 270 |\n",
"| MaxTestEpRet | -67.3 |\n",
"| MinTestEpRet | -1.09e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.78e+05 |\n",
"| AverageQ1Vals | -94.2 |\n",
"| StdQ1Vals | 150 |\n",
"| MaxQ1Vals | 47.4 |\n",
"| MinQ1Vals | -1.15e+03 |\n",
"| AverageQ2Vals | -94.2 |\n",
"| StdQ2Vals | 150 |\n",
"| MaxQ2Vals | 71 |\n",
"| MinQ2Vals | -1.15e+03 |\n",
"| LossPi | 85.8 |\n",
"| LossQ | 263 |\n",
"| Time | 2.31e+03 |\n",
"---------------------------------------\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 82 |\n",
"| AverageEpRet | -505 |\n",
"| StdEpRet | 251 |\n",
"| MaxEpRet | -79.9 |\n",
"| MinEpRet | -1.01e+03 |\n",
"| AverageTestEpRet | -734 |\n",
"| StdTestEpRet | 289 |\n",
"| MaxTestEpRet | -227 |\n",
"| MinTestEpRet | -1.22e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.8e+05 |\n",
"| AverageQ1Vals | -94.2 |\n",
"| StdQ1Vals | 149 |\n",
"| MaxQ1Vals | 53 |\n",
"| MinQ1Vals | -1.09e+03 |\n",
"| AverageQ2Vals | -94.2 |\n",
"| StdQ2Vals | 149 |\n",
"| MaxQ2Vals | 67.3 |\n",
"| MinQ2Vals | -1.08e+03 |\n",
"| LossPi | 86.6 |\n",
"| LossQ | 267 |\n",
"| Time | 2.35e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 83 |\n",
"| AverageEpRet | -585 |\n",
"| StdEpRet | 348 |\n",
"| MaxEpRet | -96.7 |\n",
"| MinEpRet | -1.3e+03 |\n",
"| AverageTestEpRet | -436 |\n",
"| StdTestEpRet | 169 |\n",
"| MaxTestEpRet | -212 |\n",
"| MinTestEpRet | -748 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.83e+05 |\n",
"| AverageQ1Vals | -92.9 |\n",
"| StdQ1Vals | 147 |\n",
"| MaxQ1Vals | 44.3 |\n",
"| MinQ1Vals | -1.18e+03 |\n",
"| AverageQ2Vals | -92.9 |\n",
"| StdQ2Vals | 147 |\n",
"| MaxQ2Vals | 75.2 |\n",
"| MinQ2Vals | -1.15e+03 |\n",
"| LossPi | 84.8 |\n",
"| LossQ | 263 |\n",
"| Time | 2.38e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 84 |\n",
"| AverageEpRet | -406 |\n",
"| StdEpRet | 232 |\n",
"| MaxEpRet | -128 |\n",
"| MinEpRet | -924 |\n",
"| AverageTestEpRet | -650 |\n",
"| StdTestEpRet | 236 |\n",
"| MaxTestEpRet | -198 |\n",
"| MinTestEpRet | -1.01e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.85e+05 |\n",
"| AverageQ1Vals | -92.5 |\n",
"| StdQ1Vals | 146 |\n",
"| MaxQ1Vals | 46.3 |\n",
"| MinQ1Vals | -1.12e+03 |\n",
"| AverageQ2Vals | -92.5 |\n",
"| StdQ2Vals | 146 |\n",
"| MaxQ2Vals | 80.6 |\n",
"| MinQ2Vals | -1.11e+03 |\n",
"| LossPi | 84.4 |\n",
"| LossQ | 258 |\n",
"| Time | 2.41e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 85 |\n",
"| AverageEpRet | -474 |\n",
"| StdEpRet | 247 |\n",
"| MaxEpRet | -180 |\n",
"| MinEpRet | -1.22e+03 |\n",
"| AverageTestEpRet | -527 |\n",
"| StdTestEpRet | 163 |\n",
"| MaxTestEpRet | -166 |\n",
"| MinTestEpRet | -737 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.87e+05 |\n",
"| AverageQ1Vals | -91.8 |\n",
"| StdQ1Vals | 145 |\n",
"| MaxQ1Vals | 51.6 |\n",
"| MinQ1Vals | -1.09e+03 |\n",
"| AverageQ2Vals | -91.8 |\n",
"| StdQ2Vals | 145 |\n",
"| MaxQ2Vals | 33.2 |\n",
"| MinQ2Vals | -1.06e+03 |\n",
"| LossPi | 84.1 |\n",
"| LossQ | 249 |\n",
"| Time | 2.44e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 86 |\n",
"| AverageEpRet | -431 |\n",
"| StdEpRet | 264 |\n",
"| MaxEpRet | -112 |\n",
"| MinEpRet | -1.26e+03 |\n",
"| AverageTestEpRet | -665 |\n",
"| StdTestEpRet | 378 |\n",
"| MaxTestEpRet | -261 |\n",
"| MinTestEpRet | -1.55e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.89e+05 |\n",
"| AverageQ1Vals | -91.6 |\n",
"| StdQ1Vals | 146 |\n",
"| MaxQ1Vals | 65.2 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -91.7 |\n",
"| StdQ2Vals | 146 |\n",
"| MaxQ2Vals | 67.6 |\n",
"| MinQ2Vals | -1.12e+03 |\n",
"| LossPi | 83.5 |\n",
"| LossQ | 238 |\n",
"| Time | 2.47e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 87 |\n",
"| AverageEpRet | -515 |\n",
"| StdEpRet | 228 |\n",
"| MaxEpRet | -122 |\n",
"| MinEpRet | -976 |\n",
"| AverageTestEpRet | -420 |\n",
"| StdTestEpRet | 202 |\n",
"| MaxTestEpRet | -180 |\n",
"| MinTestEpRet | -829 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.91e+05 |\n",
"| AverageQ1Vals | -92.1 |\n",
"| StdQ1Vals | 146 |\n",
"| MaxQ1Vals | 48.9 |\n",
"| MinQ1Vals | -1.17e+03 |\n",
"| AverageQ2Vals | -92.1 |\n",
"| StdQ2Vals | 146 |\n",
"| MaxQ2Vals | 54.4 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 83.6 |\n",
"| LossQ | 256 |\n",
"| Time | 2.51e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 88 |\n",
"| AverageEpRet | -572 |\n",
"| StdEpRet | 258 |\n",
"| MaxEpRet | -57 |\n",
"| MinEpRet | -1.07e+03 |\n",
"| AverageTestEpRet | -508 |\n",
"| StdTestEpRet | 163 |\n",
"| MaxTestEpRet | -217 |\n",
"| MinTestEpRet | -794 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.94e+05 |\n",
"| AverageQ1Vals | -91.3 |\n",
"| StdQ1Vals | 145 |\n",
"| MaxQ1Vals | 42.6 |\n",
"| MinQ1Vals | -1.12e+03 |\n",
"| AverageQ2Vals | -91.3 |\n",
"| StdQ2Vals | 145 |\n",
"| MaxQ2Vals | 58 |\n",
"| MinQ2Vals | -1.09e+03 |\n",
"| LossPi | 83.7 |\n",
"| LossQ | 246 |\n",
"| Time | 2.54e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 89 |\n",
"| AverageEpRet | -503 |\n",
"| StdEpRet | 241 |\n",
"| MaxEpRet | -49.9 |\n",
"| MinEpRet | -1.15e+03 |\n",
"| AverageTestEpRet | -562 |\n",
"| StdTestEpRet | 306 |\n",
"| MaxTestEpRet | -68.2 |\n",
"| MinTestEpRet | -1.15e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.96e+05 |\n",
"| AverageQ1Vals | -90.3 |\n",
"| StdQ1Vals | 144 |\n",
"| MaxQ1Vals | 49.8 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -90.3 |\n",
"| StdQ2Vals | 144 |\n",
"| MaxQ2Vals | 54.1 |\n",
"| MinQ2Vals | -1.15e+03 |\n",
"| LossPi | 83 |\n",
"| LossQ | 243 |\n",
"| Time | 2.57e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 90 |\n",
"| AverageEpRet | -478 |\n",
"| StdEpRet | 286 |\n",
"| MaxEpRet | -68 |\n",
"| MinEpRet | -1.15e+03 |\n",
"| AverageTestEpRet | -603 |\n",
"| StdTestEpRet | 390 |\n",
"| MaxTestEpRet | -123 |\n",
"| MinTestEpRet | -1.55e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 1.98e+05 |\n",
"| AverageQ1Vals | -89.9 |\n",
"| StdQ1Vals | 143 |\n",
"| MaxQ1Vals | 36.5 |\n",
"| MinQ1Vals | -1.17e+03 |\n",
"| AverageQ2Vals | -89.9 |\n",
"| StdQ2Vals | 143 |\n",
"| MaxQ2Vals | 65.2 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 82.6 |\n",
"| LossQ | 237 |\n",
"| Time | 2.6e+03 |\n",
"---------------------------------------\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 91 |\n",
"| AverageEpRet | -509 |\n",
"| StdEpRet | 252 |\n",
"| MaxEpRet | -101 |\n",
"| MinEpRet | -1.12e+03 |\n",
"| AverageTestEpRet | -566 |\n",
"| StdTestEpRet | 308 |\n",
"| MaxTestEpRet | -62.9 |\n",
"| MinTestEpRet | -1.02e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2e+05 |\n",
"| AverageQ1Vals | -89.9 |\n",
"| StdQ1Vals | 143 |\n",
"| MaxQ1Vals | 36.4 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -89.9 |\n",
"| StdQ2Vals | 143 |\n",
"| MaxQ2Vals | 25.5 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 82.7 |\n",
"| LossQ | 241 |\n",
"| Time | 2.63e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 92 |\n",
"| AverageEpRet | -425 |\n",
"| StdEpRet | 205 |\n",
"| MaxEpRet | -170 |\n",
"| MinEpRet | -998 |\n",
"| AverageTestEpRet | -536 |\n",
"| StdTestEpRet | 271 |\n",
"| MaxTestEpRet | -209 |\n",
"| MinTestEpRet | -1.04e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.02e+05 |\n",
"| AverageQ1Vals | -88.7 |\n",
"| StdQ1Vals | 143 |\n",
"| MaxQ1Vals | 36 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -88.7 |\n",
"| StdQ2Vals | 143 |\n",
"| MaxQ2Vals | 32.9 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 81.3 |\n",
"| LossQ | 237 |\n",
"| Time | 2.67e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 93 |\n",
"| AverageEpRet | -498 |\n",
"| StdEpRet | 277 |\n",
"| MaxEpRet | -83.8 |\n",
"| MinEpRet | -1.11e+03 |\n",
"| AverageTestEpRet | -523 |\n",
"| StdTestEpRet | 286 |\n",
"| MaxTestEpRet | -83.5 |\n",
"| MinTestEpRet | -967 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.05e+05 |\n",
"| AverageQ1Vals | -88.2 |\n",
"| StdQ1Vals | 144 |\n",
"| MaxQ1Vals | 97.3 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -88.2 |\n",
"| StdQ2Vals | 144 |\n",
"| MaxQ2Vals | 36.8 |\n",
"| MinQ2Vals | -1.18e+03 |\n",
"| LossPi | 80.8 |\n",
"| LossQ | 244 |\n",
"| Time | 2.7e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 94 |\n",
"| AverageEpRet | -470 |\n",
"| StdEpRet | 231 |\n",
"| MaxEpRet | -88.9 |\n",
"| MinEpRet | -946 |\n",
"| AverageTestEpRet | -407 |\n",
"| StdTestEpRet | 194 |\n",
"| MaxTestEpRet | -167 |\n",
"| MinTestEpRet | -793 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.07e+05 |\n",
"| AverageQ1Vals | -87.9 |\n",
"| StdQ1Vals | 143 |\n",
"| MaxQ1Vals | 48.9 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -87.9 |\n",
"| StdQ2Vals | 143 |\n",
"| MaxQ2Vals | 65.6 |\n",
"| MinQ2Vals | -1.1e+03 |\n",
"| LossPi | 80.4 |\n",
"| LossQ | 244 |\n",
"| Time | 2.73e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 95 |\n",
"| AverageEpRet | -471 |\n",
"| StdEpRet | 257 |\n",
"| MaxEpRet | -113 |\n",
"| MinEpRet | -994 |\n",
"| AverageTestEpRet | -563 |\n",
"| StdTestEpRet | 152 |\n",
"| MaxTestEpRet | -261 |\n",
"| MinTestEpRet | -827 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.09e+05 |\n",
"| AverageQ1Vals | -87.2 |\n",
"| StdQ1Vals | 141 |\n",
"| MaxQ1Vals | 30.3 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -87.2 |\n",
"| StdQ2Vals | 141 |\n",
"| MaxQ2Vals | 45.3 |\n",
"| MinQ2Vals | -1.11e+03 |\n",
"| LossPi | 80.3 |\n",
"| LossQ | 243 |\n",
"| Time | 2.76e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 96 |\n",
"| AverageEpRet | -473 |\n",
"| StdEpRet | 268 |\n",
"| MaxEpRet | -76.1 |\n",
"| MinEpRet | -1.03e+03 |\n",
"| AverageTestEpRet | -392 |\n",
"| StdTestEpRet | 191 |\n",
"| MaxTestEpRet | -90.2 |\n",
"| MinTestEpRet | -713 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.11e+05 |\n",
"| AverageQ1Vals | -86.8 |\n",
"| StdQ1Vals | 139 |\n",
"| MaxQ1Vals | 32.9 |\n",
"| MinQ1Vals | -1.09e+03 |\n",
"| AverageQ2Vals | -86.8 |\n",
"| StdQ2Vals | 139 |\n",
"| MaxQ2Vals | 40.5 |\n",
"| MinQ2Vals | -1.1e+03 |\n",
"| LossPi | 79.5 |\n",
"| LossQ | 233 |\n",
"| Time | 2.79e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 97 |\n",
"| AverageEpRet | -497 |\n",
"| StdEpRet | 345 |\n",
"| MaxEpRet | -37.1 |\n",
"| MinEpRet | -1.17e+03 |\n",
"| AverageTestEpRet | -420 |\n",
"| StdTestEpRet | 227 |\n",
"| MaxTestEpRet | -72.6 |\n",
"| MinTestEpRet | -742 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.13e+05 |\n",
"| AverageQ1Vals | -86.5 |\n",
"| StdQ1Vals | 140 |\n",
"| MaxQ1Vals | 43 |\n",
"| MinQ1Vals | -1.17e+03 |\n",
"| AverageQ2Vals | -86.5 |\n",
"| StdQ2Vals | 140 |\n",
"| MaxQ2Vals | 38.9 |\n",
"| MinQ2Vals | -1.18e+03 |\n",
"| LossPi | 79.6 |\n",
"| LossQ | 234 |\n",
"| Time | 2.82e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 98 |\n",
"| AverageEpRet | -429 |\n",
"| StdEpRet | 215 |\n",
"| MaxEpRet | -135 |\n",
"| MinEpRet | -848 |\n",
"| AverageTestEpRet | -511 |\n",
"| StdTestEpRet | 337 |\n",
"| MaxTestEpRet | -92.5 |\n",
"| MinTestEpRet | -1.37e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.16e+05 |\n",
"| AverageQ1Vals | -86.1 |\n",
"| StdQ1Vals | 139 |\n",
"| MaxQ1Vals | 30.3 |\n",
"| MinQ1Vals | -1.25e+03 |\n",
"| AverageQ2Vals | -86.1 |\n",
"| StdQ2Vals | 139 |\n",
"| MaxQ2Vals | 43.7 |\n",
"| MinQ2Vals | -1.21e+03 |\n",
"| LossPi | 79.1 |\n",
"| LossQ | 226 |\n",
"| Time | 2.85e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 99 |\n",
"| AverageEpRet | -514 |\n",
"| StdEpRet | 278 |\n",
"| MaxEpRet | -141 |\n",
"| MinEpRet | -1.21e+03 |\n",
"| AverageTestEpRet | -633 |\n",
"| StdTestEpRet | 489 |\n",
"| MaxTestEpRet | -181 |\n",
"| MinTestEpRet | -1.66e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.18e+05 |\n",
"| AverageQ1Vals | -84.8 |\n",
"| StdQ1Vals | 139 |\n",
"| MaxQ1Vals | 30.2 |\n",
"| MinQ1Vals | -1.19e+03 |\n",
"| AverageQ2Vals | -84.8 |\n",
"| StdQ2Vals | 139 |\n",
"| MaxQ2Vals | 27.5 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 77.7 |\n",
"| LossQ | 225 |\n",
"| Time | 2.88e+03 |\n",
"---------------------------------------\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 100 |\n",
"| AverageEpRet | -557 |\n",
"| StdEpRet | 280 |\n",
"| MaxEpRet | -26 |\n",
"| MinEpRet | -1.17e+03 |\n",
"| AverageTestEpRet | -544 |\n",
"| StdTestEpRet | 372 |\n",
"| MaxTestEpRet | -148 |\n",
"| MinTestEpRet | -1.24e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.2e+05 |\n",
"| AverageQ1Vals | -84 |\n",
"| StdQ1Vals | 139 |\n",
"| MaxQ1Vals | 51.4 |\n",
"| MinQ1Vals | -1.18e+03 |\n",
"| AverageQ2Vals | -84 |\n",
"| StdQ2Vals | 139 |\n",
"| MaxQ2Vals | 43 |\n",
"| MinQ2Vals | -1.22e+03 |\n",
"| LossPi | 76.6 |\n",
"| LossQ | 220 |\n",
"| Time | 2.92e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 101 |\n",
"| AverageEpRet | -434 |\n",
"| StdEpRet | 192 |\n",
"| MaxEpRet | -155 |\n",
"| MinEpRet | -806 |\n",
"| AverageTestEpRet | -418 |\n",
"| StdTestEpRet | 152 |\n",
"| MaxTestEpRet | -244 |\n",
"| MinTestEpRet | -730 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.22e+05 |\n",
"| AverageQ1Vals | -82.7 |\n",
"| StdQ1Vals | 138 |\n",
"| MaxQ1Vals | 35.3 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -82.7 |\n",
"| StdQ2Vals | 138 |\n",
"| MaxQ2Vals | 54.9 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 76.3 |\n",
"| LossQ | 219 |\n",
"| Time | 2.95e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 102 |\n",
"| AverageEpRet | -625 |\n",
"| StdEpRet | 341 |\n",
"| MaxEpRet | -120 |\n",
"| MinEpRet | -1.24e+03 |\n",
"| AverageTestEpRet | -490 |\n",
"| StdTestEpRet | 223 |\n",
"| MaxTestEpRet | -73.4 |\n",
"| MinTestEpRet | -824 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.24e+05 |\n",
"| AverageQ1Vals | -81.2 |\n",
"| StdQ1Vals | 137 |\n",
"| MaxQ1Vals | 96.8 |\n",
"| MinQ1Vals | -1.19e+03 |\n",
"| AverageQ2Vals | -81.2 |\n",
"| StdQ2Vals | 137 |\n",
"| MaxQ2Vals | 71.4 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 74.2 |\n",
"| LossQ | 213 |\n",
"| Time | 2.99e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 103 |\n",
"| AverageEpRet | -617 |\n",
"| StdEpRet | 327 |\n",
"| MaxEpRet | -104 |\n",
"| MinEpRet | -1.32e+03 |\n",
"| AverageTestEpRet | -561 |\n",
"| StdTestEpRet | 214 |\n",
"| MaxTestEpRet | -248 |\n",
"| MinTestEpRet | -906 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.27e+05 |\n",
"| AverageQ1Vals | -80.7 |\n",
"| StdQ1Vals | 138 |\n",
"| MaxQ1Vals | 70.5 |\n",
"| MinQ1Vals | -1.15e+03 |\n",
"| AverageQ2Vals | -80.7 |\n",
"| StdQ2Vals | 138 |\n",
"| MaxQ2Vals | 41 |\n",
"| MinQ2Vals | -1.13e+03 |\n",
"| LossPi | 74.1 |\n",
"| LossQ | 204 |\n",
"| Time | 3.02e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 104 |\n",
"| AverageEpRet | -527 |\n",
"| StdEpRet | 254 |\n",
"| MaxEpRet | -65.7 |\n",
"| MinEpRet | -1.01e+03 |\n",
"| AverageTestEpRet | -425 |\n",
"| StdTestEpRet | 224 |\n",
"| MaxTestEpRet | -92.5 |\n",
"| MinTestEpRet | -774 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.29e+05 |\n",
"| AverageQ1Vals | -79.9 |\n",
"| StdQ1Vals | 137 |\n",
"| MaxQ1Vals | 41.1 |\n",
"| MinQ1Vals | -1.13e+03 |\n",
"| AverageQ2Vals | -79.9 |\n",
"| StdQ2Vals | 137 |\n",
"| MaxQ2Vals | 44.5 |\n",
"| MinQ2Vals | -1.11e+03 |\n",
"| LossPi | 73.2 |\n",
"| LossQ | 217 |\n",
"| Time | 3.05e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 105 |\n",
"| AverageEpRet | -469 |\n",
"| StdEpRet | 235 |\n",
"| MaxEpRet | -144 |\n",
"| MinEpRet | -1.12e+03 |\n",
"| AverageTestEpRet | -317 |\n",
"| StdTestEpRet | 137 |\n",
"| MaxTestEpRet | -134 |\n",
"| MinTestEpRet | -541 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.31e+05 |\n",
"| AverageQ1Vals | -78.8 |\n",
"| StdQ1Vals | 135 |\n",
"| MaxQ1Vals | 24.5 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -78.8 |\n",
"| StdQ2Vals | 135 |\n",
"| MaxQ2Vals | 38.7 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 72.6 |\n",
"| LossQ | 200 |\n",
"| Time | 3.08e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 106 |\n",
"| AverageEpRet | -509 |\n",
"| StdEpRet | 244 |\n",
"| MaxEpRet | -114 |\n",
"| MinEpRet | -989 |\n",
"| AverageTestEpRet | -542 |\n",
"| StdTestEpRet | 277 |\n",
"| MaxTestEpRet | -129 |\n",
"| MinTestEpRet | -965 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.33e+05 |\n",
"| AverageQ1Vals | -79.1 |\n",
"| StdQ1Vals | 136 |\n",
"| MaxQ1Vals | 40.6 |\n",
"| MinQ1Vals | -1.09e+03 |\n",
"| AverageQ2Vals | -79.1 |\n",
"| StdQ2Vals | 136 |\n",
"| MaxQ2Vals | 54 |\n",
"| MinQ2Vals | -1.11e+03 |\n",
"| LossPi | 72.7 |\n",
"| LossQ | 207 |\n",
"| Time | 3.11e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 107 |\n",
"| AverageEpRet | -571 |\n",
"| StdEpRet | 245 |\n",
"| MaxEpRet | -189 |\n",
"| MinEpRet | -969 |\n",
"| AverageTestEpRet | -538 |\n",
"| StdTestEpRet | 189 |\n",
"| MaxTestEpRet | -255 |\n",
"| MinTestEpRet | -880 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.35e+05 |\n",
"| AverageQ1Vals | -78.4 |\n",
"| StdQ1Vals | 135 |\n",
"| MaxQ1Vals | 33.8 |\n",
"| MinQ1Vals | -1.11e+03 |\n",
"| AverageQ2Vals | -78.4 |\n",
"| StdQ2Vals | 135 |\n",
"| MaxQ2Vals | 45.3 |\n",
"| MinQ2Vals | -1.16e+03 |\n",
"| LossPi | 71.6 |\n",
"| LossQ | 202 |\n",
"| Time | 3.15e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 108 |\n",
"| AverageEpRet | -481 |\n",
"| StdEpRet | 187 |\n",
"| MaxEpRet | -110 |\n",
"| MinEpRet | -837 |\n",
"| AverageTestEpRet | -399 |\n",
"| StdTestEpRet | 162 |\n",
"| MaxTestEpRet | -149 |\n",
"| MinTestEpRet | -668 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.38e+05 |\n",
"| AverageQ1Vals | -78 |\n",
"| StdQ1Vals | 135 |\n",
"| MaxQ1Vals | 34 |\n",
"| MinQ1Vals | -1.15e+03 |\n",
"| AverageQ2Vals | -78 |\n",
"| StdQ2Vals | 135 |\n",
"| MaxQ2Vals | 41.9 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 72.1 |\n",
"| LossQ | 217 |\n",
"| Time | 3.18e+03 |\n",
"---------------------------------------\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 109 |\n",
"| AverageEpRet | -476 |\n",
"| StdEpRet | 272 |\n",
"| MaxEpRet | -63.6 |\n",
"| MinEpRet | -1.04e+03 |\n",
"| AverageTestEpRet | -531 |\n",
"| StdTestEpRet | 326 |\n",
"| MaxTestEpRet | -90.1 |\n",
"| MinTestEpRet | -1.19e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.4e+05 |\n",
"| AverageQ1Vals | -76.9 |\n",
"| StdQ1Vals | 134 |\n",
"| MaxQ1Vals | 59 |\n",
"| MinQ1Vals | -1.19e+03 |\n",
"| AverageQ2Vals | -76.9 |\n",
"| StdQ2Vals | 134 |\n",
"| MaxQ2Vals | 42.2 |\n",
"| MinQ2Vals | -1.18e+03 |\n",
"| LossPi | 70.7 |\n",
"| LossQ | 212 |\n",
"| Time | 3.21e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 110 |\n",
"| AverageEpRet | -523 |\n",
"| StdEpRet | 321 |\n",
"| MaxEpRet | -29.2 |\n",
"| MinEpRet | -1.39e+03 |\n",
"| AverageTestEpRet | -583 |\n",
"| StdTestEpRet | 282 |\n",
"| MaxTestEpRet | -187 |\n",
"| MinTestEpRet | -1.03e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.42e+05 |\n",
"| AverageQ1Vals | -76.8 |\n",
"| StdQ1Vals | 135 |\n",
"| MaxQ1Vals | 43.9 |\n",
"| MinQ1Vals | -1.19e+03 |\n",
"| AverageQ2Vals | -76.8 |\n",
"| StdQ2Vals | 135 |\n",
"| MaxQ2Vals | 53.2 |\n",
"| MinQ2Vals | -1.19e+03 |\n",
"| LossPi | 70.9 |\n",
"| LossQ | 202 |\n",
"| Time | 3.24e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 111 |\n",
"| AverageEpRet | -453 |\n",
"| StdEpRet | 254 |\n",
"| MaxEpRet | -81.5 |\n",
"| MinEpRet | -1.13e+03 |\n",
"| AverageTestEpRet | -524 |\n",
"| StdTestEpRet | 105 |\n",
"| MaxTestEpRet | -339 |\n",
"| MinTestEpRet | -689 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.44e+05 |\n",
"| AverageQ1Vals | -76.5 |\n",
"| StdQ1Vals | 135 |\n",
"| MaxQ1Vals | 30.1 |\n",
"| MinQ1Vals | -1.19e+03 |\n",
"| AverageQ2Vals | -76.5 |\n",
"| StdQ2Vals | 135 |\n",
"| MaxQ2Vals | 41.8 |\n",
"| MinQ2Vals | -1.23e+03 |\n",
"| LossPi | 70.4 |\n",
"| LossQ | 207 |\n",
"| Time | 3.27e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 112 |\n",
"| AverageEpRet | -596 |\n",
"| StdEpRet | 262 |\n",
"| MaxEpRet | -173 |\n",
"| MinEpRet | -1.26e+03 |\n",
"| AverageTestEpRet | -415 |\n",
"| StdTestEpRet | 161 |\n",
"| MaxTestEpRet | -137 |\n",
"| MinTestEpRet | -652 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.46e+05 |\n",
"| AverageQ1Vals | -76.3 |\n",
"| StdQ1Vals | 134 |\n",
"| MaxQ1Vals | 34.9 |\n",
"| MinQ1Vals | -1.19e+03 |\n",
"| AverageQ2Vals | -76.3 |\n",
"| StdQ2Vals | 134 |\n",
"| MaxQ2Vals | 46.7 |\n",
"| MinQ2Vals | -1.18e+03 |\n",
"| LossPi | 70.3 |\n",
"| LossQ | 198 |\n",
"| Time | 3.3e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 113 |\n",
"| AverageEpRet | -482 |\n",
"| StdEpRet | 333 |\n",
"| MaxEpRet | -62.8 |\n",
"| MinEpRet | -1.44e+03 |\n",
"| AverageTestEpRet | -559 |\n",
"| StdTestEpRet | 304 |\n",
"| MaxTestEpRet | -142 |\n",
"| MinTestEpRet | -1.28e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.49e+05 |\n",
"| AverageQ1Vals | -76.2 |\n",
"| StdQ1Vals | 134 |\n",
"| MaxQ1Vals | 38.3 |\n",
"| MinQ1Vals | -1.18e+03 |\n",
"| AverageQ2Vals | -76.2 |\n",
"| StdQ2Vals | 134 |\n",
"| MaxQ2Vals | 50.3 |\n",
"| MinQ2Vals | -1.2e+03 |\n",
"| LossPi | 69.7 |\n",
"| LossQ | 200 |\n",
"| Time | 3.33e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 114 |\n",
"| AverageEpRet | -450 |\n",
"| StdEpRet | 216 |\n",
"| MaxEpRet | -94.9 |\n",
"| MinEpRet | -872 |\n",
"| AverageTestEpRet | -432 |\n",
"| StdTestEpRet | 132 |\n",
"| MaxTestEpRet | -232 |\n",
"| MinTestEpRet | -645 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.51e+05 |\n",
"| AverageQ1Vals | -75.7 |\n",
"| StdQ1Vals | 132 |\n",
"| MaxQ1Vals | 44.9 |\n",
"| MinQ1Vals | -1.16e+03 |\n",
"| AverageQ2Vals | -75.7 |\n",
"| StdQ2Vals | 132 |\n",
"| MaxQ2Vals | 44.4 |\n",
"| MinQ2Vals | -1.13e+03 |\n",
"| LossPi | 69.6 |\n",
"| LossQ | 201 |\n",
"| Time | 3.36e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 115 |\n",
"| AverageEpRet | -487 |\n",
"| StdEpRet | 240 |\n",
"| MaxEpRet | -108 |\n",
"| MinEpRet | -932 |\n",
"| AverageTestEpRet | -371 |\n",
"| StdTestEpRet | 152 |\n",
"| MaxTestEpRet | -143 |\n",
"| MinTestEpRet | -616 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.53e+05 |\n",
"| AverageQ1Vals | -75.4 |\n",
"| StdQ1Vals | 132 |\n",
"| MaxQ1Vals | 21.2 |\n",
"| MinQ1Vals | -1.14e+03 |\n",
"| AverageQ2Vals | -75.4 |\n",
"| StdQ2Vals | 132 |\n",
"| MaxQ2Vals | 29.5 |\n",
"| MinQ2Vals | -1.11e+03 |\n",
"| LossPi | 69.7 |\n",
"| LossQ | 205 |\n",
"| Time | 3.4e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 116 |\n",
"| AverageEpRet | -538 |\n",
"| StdEpRet | 220 |\n",
"| MaxEpRet | -110 |\n",
"| MinEpRet | -960 |\n",
"| AverageTestEpRet | -475 |\n",
"| StdTestEpRet | 311 |\n",
"| MaxTestEpRet | -173 |\n",
"| MinTestEpRet | -1.23e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.55e+05 |\n",
"| AverageQ1Vals | -75.4 |\n",
"| StdQ1Vals | 132 |\n",
"| MaxQ1Vals | 26 |\n",
"| MinQ1Vals | -1.18e+03 |\n",
"| AverageQ2Vals | -75.4 |\n",
"| StdQ2Vals | 132 |\n",
"| MaxQ2Vals | 37.1 |\n",
"| MinQ2Vals | -1.17e+03 |\n",
"| LossPi | 69.3 |\n",
"| LossQ | 201 |\n",
"| Time | 3.43e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 117 |\n",
"| AverageEpRet | -437 |\n",
"| StdEpRet | 203 |\n",
"| MaxEpRet | -92.8 |\n",
"| MinEpRet | -857 |\n",
"| AverageTestEpRet | -582 |\n",
"| StdTestEpRet | 247 |\n",
"| MaxTestEpRet | -79.8 |\n",
"| MinTestEpRet | -861 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.57e+05 |\n",
"| AverageQ1Vals | -75.5 |\n",
"| StdQ1Vals | 132 |\n",
"| MaxQ1Vals | 49.5 |\n",
"| MinQ1Vals | -1.13e+03 |\n",
"| AverageQ2Vals | -75.5 |\n",
"| StdQ2Vals | 132 |\n",
"| MaxQ2Vals | 51 |\n",
"| MinQ2Vals | -1.14e+03 |\n",
"| LossPi | 69.4 |\n",
"| LossQ | 201 |\n",
"| Time | 3.47e+03 |\n",
"---------------------------------------\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"---------------------------------------\n",
"| Epoch | 118 |\n",
"| AverageEpRet | -549 |\n",
"| StdEpRet | 236 |\n",
"| MaxEpRet | -111 |\n",
"| MinEpRet | -1.28e+03 |\n",
"| AverageTestEpRet | -588 |\n",
"| StdTestEpRet | 404 |\n",
"| MaxTestEpRet | -138 |\n",
"| MinTestEpRet | -1.66e+03 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.6e+05 |\n",
"| AverageQ1Vals | -75.1 |\n",
"| StdQ1Vals | 130 |\n",
"| MaxQ1Vals | 31.7 |\n",
"| MinQ1Vals | -1.05e+03 |\n",
"| AverageQ2Vals | -75.1 |\n",
"| StdQ2Vals | 130 |\n",
"| MaxQ2Vals | 38.6 |\n",
"| MinQ2Vals | -1.05e+03 |\n",
"| LossPi | 69 |\n",
"| LossQ | 192 |\n",
"| Time | 3.5e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 119 |\n",
"| AverageEpRet | -491 |\n",
"| StdEpRet | 247 |\n",
"| MaxEpRet | -102 |\n",
"| MinEpRet | -945 |\n",
"| AverageTestEpRet | -535 |\n",
"| StdTestEpRet | 217 |\n",
"| MaxTestEpRet | -173 |\n",
"| MinTestEpRet | -879 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.62e+05 |\n",
"| AverageQ1Vals | -74.9 |\n",
"| StdQ1Vals | 130 |\n",
"| MaxQ1Vals | 60.9 |\n",
"| MinQ1Vals | -1.11e+03 |\n",
"| AverageQ2Vals | -74.9 |\n",
"| StdQ2Vals | 130 |\n",
"| MaxQ2Vals | 28.6 |\n",
"| MinQ2Vals | -1.12e+03 |\n",
"| LossPi | 69.2 |\n",
"| LossQ | 204 |\n",
"| Time | 3.53e+03 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| Epoch | 120 |\n",
"| AverageEpRet | -431 |\n",
"| StdEpRet | 249 |\n",
"| MaxEpRet | -64.6 |\n",
"| MinEpRet | -885 |\n",
"| AverageTestEpRet | -519 |\n",
"| StdTestEpRet | 242 |\n",
"| MaxTestEpRet | -56.1 |\n",
"| MinTestEpRet | -838 |\n",
"| EpLen | 110 |\n",
"| TestEpLen | 110 |\n",
"| TotalEnvInteracts | 2.64e+05 |\n",
"| AverageQ1Vals | -74.8 |\n",
"| StdQ1Vals | 129 |\n",
"| MaxQ1Vals | 105 |\n",
"| MinQ1Vals | -1.11e+03 |\n",
"| AverageQ2Vals | -74.8 |\n",
"| StdQ2Vals | 129 |\n",
"| MaxQ2Vals | 77.4 |\n",
"| MinQ2Vals | -1.08e+03 |\n",
"| LossPi | 69.1 |\n",
"| LossQ | 197 |\n",
"| Time | 3.56e+03 |\n",
"---------------------------------------\n"
]
}
],
"source": [
"# Setup experiment\n",
"logger_kwargs = dict(output_dir='model', exp_name='v0')\n",
"\n",
"# Run training\n",
"spinup.td3_pytorch(GyroscopeEnv, seed=0, steps_per_epoch=110*20, epochs=120, replay_size=1000000, gamma=0.95,\n",
"polyak=0.995, batch_size=100, start_steps=20000, update_after=800, update_every=50,max_ep_len=110,logger_kwargs=logger_kwargs)"
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "Gn3Gp40bcOVz"
},
"source": [
"## Test"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 106
},
"colab_type": "code",
"executionInfo": {
"elapsed": 972,
"status": "ok",
"timestamp": 1584036455886,
"user": {
"displayName": "Matthieu Le Cauchois",
"photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgY9gRlHHK-FHlINeRnTJw_wewJsr639GH8MAWl=s64",
"userId": "10992927378504656501"
},
"user_tz": -60
},
"id": "6GyY0wE-QBOj",
"outputId": "9a5e9011-e024-4a65-8383-83c062cdcad9"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/matthieulc/Documents/MA2/PS1/ps1venv/lib/python3.6/site-packages/gym/logger.py:30: UserWarning: \u001b[33mWARN: Box bound precision lowered by casting to float32\u001b[0m\n",
" warnings.warn(colorize('%s: %s'%('WARN', msg % args), 'yellow'))\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-900.18321242575\n"
]
}
],
"source": [
"# Creat environment\n",
"env = GyroscopeEnv()\n",
"env.seed(2)\n",
"\n",
"# Create agent\n",
"agent = torch.load('model/pyt_save/model.pt')\n",
"\n",
"# Test parameters\n",
"x1,x2,x3,x4,x1_ref,x3_ref,w = 0,1,0,1,1,3,25\n",
"state = env.reset(np.array([x1,x2,x3,x4,x1_ref,x3_ref,w]))\n",
"val = []\n",
"act = []\n",
"dt = 0.01\n",
"time = np.arange(0, 4, dt)\n",
"score = 0\n",
"for i in range(len(time)):\n",
" val.append(state)\n",
" action = agent.act(torch.as_tensor(state, dtype=torch.float32))\n",
" act.append(action)\n",
" state, reward, done, _ = env.step(action)\n",
" score += reward\n",
" if done:\n",
" break \n",
"\n",
"env.close()\n",
"print(score)"
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "vvMjuRHDcfrE"
},
"source": [
"## Plot"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"colab_type": "code",
"executionInfo": {
"elapsed": 1856,
"status": "ok",
"timestamp": 1584036457424,
"user": {
"displayName": "Matthieu Le Cauchois",
"photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GgY9gRlHHK-FHlINeRnTJw_wewJsr639GH8MAWl=s64",
"userId": "10992927378504656501"
},
"user_tz": -60
},
"id": "aCZCqujgcMVA",
"outputId": "05490294-aab8-4933-ca9b-e13ba85ecf6d"
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
""
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"f, axs = plt.subplots(4,2,figsize=(30,30))\n",
"plt.subplot(4,2,1)\n",
"plt.title('Red gimbal angle',fontsize=20)\n",
"plt.xlabel('time (s)',fontsize=16)\n",
"plt.ylabel(r'$\\theta$ (rad)',fontsize=16)\n",
"plt.grid()\n",
"plt.plot(time,[row[0] for row in val],'r-')\n",
"plt.plot(time, [row[4] for row in val], color='black', linestyle='dashed')\n",
"\n",
"plt.subplot(4,2,2)\n",
"plt.title('Blue gimbal angle',fontsize=20)\n",
"plt.xlabel('time (s)',fontsize=16)\n",
"plt.ylabel(r'$\\phi$ (rad)',fontsize=16)\n",
"plt.grid()\n",
"plt.plot(time,[row[2] for row in val],'b-')\n",
"plt.plot(time, [row[5] for row in val], color='black', linestyle='dashed')\n",
"\n",
"plt.subplot(4,2,3)\n",
"plt.title('Red gimbal speed',fontsize=20)\n",
"plt.xlabel('time (s)',fontsize=16)\n",
"plt.ylabel(r'$\\dot \\theta$ (rad/s)',fontsize=16)\n",
"plt.grid()\n",
"plt.plot(time,[row[1] for row in val],'r-')\n",
"\n",
"plt.subplot(4,2,4)\n",
"plt.title('Blue gimbal speed',fontsize=20)\n",
"plt.xlabel('time (s)',fontsize=16)\n",
"plt.ylabel(r'$\\dot \\phi$ (rad/s)',fontsize=16)\n",
"plt.grid()\n",
"plt.plot(time,[row[3] for row in val],'b-')\n",
"\n",
"plt.subplot(4,2,5)\n",
"plt.title('Red gimbal tracking error',fontsize=20)\n",
"plt.xlabel('time (s)',fontsize=16)\n",
"plt.ylabel(r'$\\theta$ error (rad)',fontsize=16)\n",
"plt.grid()\n",
"plt.plot(time,[angle_normalize(row[0]- row[4]) for row in val],'r-')\n",
"\n",
"plt.subplot(4,2,6)\n",
"plt.title('Blue gimbal tracking error',fontsize=20)\n",
"plt.xlabel('time (s)',fontsize=16)\n",
"plt.ylabel(r'$\\phi$ error (rad)',fontsize=16)\n",
"plt.grid()\n",
"plt.plot(time,[angle_normalize(row[2]- row[5]) for row in val],'b-')\n",
"\n",
"plt.subplot(4,2,7)\n",
"plt.title('Red gimbal input',fontsize=20)\n",
"plt.xlabel('time (s)',fontsize=16)\n",
"plt.ylabel(r'u1 (V)',fontsize=16)\n",
"plt.grid()\n",
"plt.plot(time,[row[0] for row in act],'r-')\n",
"\n",
"plt.subplot(4,2,8)\n",
"plt.title('Blue gimbal input',fontsize=20)\n",
"plt.xlabel('time (s)',fontsize=16)\n",
"plt.ylabel(r'u2 (V)',fontsize=16)\n",
"plt.grid()\n",
"plt.plot(time,[row[1] for row in act],'b-')\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"colab_type": "text",
"id": "fz9r-gaStzpk"
},
"source": [
"## 3D rendering"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"colab": {},
"colab_type": "code",
"id": "HQM1E8JYc-cC"
},
"outputs": [
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/javascript": [
"if (typeof Jupyter !== \"undefined\") { window.__context = { glowscript_container: $(\"#glowscript\").removeAttr(\"id\")};}else{ element.textContent = ' ';}"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Scene\n",
"scene = canvas(background=color.white) \n",
"\n",
"# Objects\n",
"redGimbal = ring(pos=vector(0,0,0), axis=vector(0,0,1), radius=2, thickness=0.2,color=vector(0.9,0,0))\n",
"blueGimbal1 = cylinder(pos=vector(0,0,0), axis=vector(0,2,0), radius=0.3,color=color.blue)\n",
"blueGimbal2 = cylinder(pos=vector(0,0,0), axis=vector(0,-2,0), radius=0.3,color=color.blue)\n",
"disk1 = cylinder(pos=vector(0,0,0), axis=vector(0,0,0.15), radius=1.3,color=color.yellow)\n",
"disk2 = cylinder(pos=vector(0,0,0), axis=vector(0,0,-0.15), radius=1.3,color=color.yellow)\n",
"baseR = extrusion(path=[vec(0,0,0), vec(0.7,0,0)],shape=[ shapes.circle(radius=0.5) ], pos=vec(2,0,0), color=color.black)\n",
"baseL = extrusion(path=[vec(-0.7,0,0), vec(0,0,0)],shape=[ shapes.circle(radius=0.5) ], pos=vec(-2,0,0), color=color.black)\n",
"\n",
"loops = 0\n",
"ctime = 0\n",
"start = clock()\n",
"N = 400\n",
"\n",
"for k in range(len(time)):\n",
" rate(N)\n",
" ct = clock()\n",
" theta = val[k][0]\n",
" phi = val[k][2]\n",
" redGimbal.axis = vector(0,-sin(theta), cos(theta))\n",
" blueGimbal1.axis = 2*vector(0,cos(theta), sin(theta))\n",
" blueGimbal2.axis = -2*vector(0,cos(theta), sin(theta))\n",
" disk1.axis = 0.15*vector(-sin(phi),-sin(theta)*cos(phi),cos(theta)*cos(phi))\n",
" disk2.axis = -0.15*vector(-sin(phi),-sin(theta)*cos(phi),cos(theta)*cos(phi))\n",
" ctime += clock()-ct\n",
" loops += 1"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"collapsed_sections": [],
"name": "gyroscope_ddpg_testing.ipynb",
"provenance": []
},
"kernelspec": {
"display_name": "ps1venv",
"language": "python",
"name": "ps1venv"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.9"
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