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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Version 1 Simulation\n",
"\n",
"The first version of this series is a basic control model. Given an elevation profile $H(x)$ and a time target, minimize energy usage.\n",
"We assume the time target is constant, since we are racing at a given overall pace. In other words, we already know the average speed $E(V) = dist/time$"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import jax.numpy as jnp\n",
"from jax import jit, vmap, lax\n",
"from jax import random\n",
"import matplotlib.pyplot as plt\n",
"\n",
"@jit\n",
"def _cov_math(t, s, H):\n",
" return 0.5 * (jnp.abs(t) ** 2 * H + jnp.abs(s) ** 2 * H - jnp.abs(t - s) ** 2 * H)\n",
"\n",
"\n",
"def _fbm_covariance(n, H) -> jnp.ndarray:\n",
" tidx = jnp.arange(1, n + 1)\n",
" t, s = jnp.meshgrid(tidx, tidx)\n",
"\n",
" # fBm covariance equation from wikipedia\n",
" cov = 0.5 * (jnp.abs(t) ** 2 * H + jnp.abs(s) ** 2 * H - jnp.abs(t - s) ** 2 * H)\n",
" return cov\n",
"\n",
"# generate terrain using fractional brownian motion\n",
"def gen_elevation_profile(rngkey: random.PRNGKey, n_steps: int, H: float):\n",
" t = jnp.linspace(0,1,n_steps)\n",
" cov = _fbm_covariance(n_steps, H)\n",
" # using the \"method 1\" (cholesky decomposition)\n",
" sigma = jnp.linalg.cholesky(cov)\n",
" # create a vector of n_steps gaussian normal values\n",
" v = random.normal(rngkey, shape=(n_steps))\n",
" # convert these to fbm lines\n",
"\n",
" fbm_samples = sigma * v\n",
"\n",
" return t, fbm_samples\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"An NVIDIA GPU may be present on this machine, but a CUDA-enabled jaxlib is not installed. Falling back to cpu.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[[nan -0. -0. ... -0. -0. -0.]\n",
" [nan nan -0. ... -0. -0. -0.]\n",
" [nan nan nan ... -0. -0. -0.]\n",
" ...\n",
" [nan nan nan ... nan -0. -0.]\n",
" [nan nan nan ... nan nan -0.]\n",
" [nan nan nan ... nan nan nan]]\n"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"key = random.PRNGKey(0)\n",
"steps = 1000\n",
"samples = 5\n",
"\n",
"H = 0.6\n",
"\n",
"t, fbm = gen_elevation_profile(key, steps, H)\n",
"plt.figure(figsize=(12,6))\n",
"print(fbm)\n",
"for i in range(fbm.shape[0]):\n",
" plt.plot(t, fbm[i], label=f\"Sample {i}\")"
]
},
{
"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
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"[<matplotlib.lines.Line2D at 0x7101983fd730>]"
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]
},
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"execution_count": 3,
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"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAjgAAAGdCAYAAAAfTAk2AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8hTgPZAAAACXBIWXMAAA9hAAAPYQGoP6dpAACR7klEQVR4nO3dd3xT9foH8E+Stunem5bSslp22WUoCLJcKC5EQUW8eHGB16t4XehP4epVrxdx4AAVEUURFBXZu2wKtEChZXTvvdKM8/vjm5PRpm3SnuRkPO/Xq6+cJqfJt6EkT57v832+Eo7jOBBCCCGEOBGp2AMghBBCCBEaBTiEEEIIcToU4BBCCCHE6VCAQwghhBCnQwEOIYQQQpwOBTiEEEIIcToU4BBCCCHE6VCAQwghhBCn4yb2AMSg0WhQUFAAPz8/SCQSsYdDCCGEEDNwHIfa2lpER0dDKm0/R+OSAU5BQQFiY2PFHgYhhBBCOiE3NxcxMTHtnuOSAY6fnx8A9gT5+/uLPBpCCCGEmKOmpgaxsbG69/H2uGSAw09L+fv7U4BDCCGEOBhzykuoyJgQQgghTocCHEIIIYQ4HQpwCCGEEOJ0KMAhhBBCiNOhAIcQQgghTocCHEIIIYQ4HQpwCCGEEOJ0KMAhhBBCiNOhAIcQQgghTocCHEIIIYQ4HQpwCCGEEOJ0KMAhhBBCiNMRPcDp0aMHJBJJq69FixaZPH/t2rWtzvX09LTxqAkhhBACADj/K5C+SexRtCL6buLHjx+HWq3WfZ+eno6bb74Z99xzT5s/4+/vj8zMTN335uwqSgghhBCBNTcAPz0KaJRA5VVg/HNij0hH9AAnLCzM6PsVK1agZ8+euPHGG9v8GYlEgsjISGsPjRBCCCHtaaxkwQ0A7HoDcPMEUkzPwNia6FNUhpqbm7Fu3To8+uij7WZl6urqEBcXh9jYWNxxxx3IyMho934VCgVqamqMvgghhBDSRYoW76d/vQQc+1ycsbRgVwHO5s2bUVVVhYcffrjNc/r27YuvvvoKW7Zswbp166DRaDBmzBjk5eW1+TPLly9HQECA7is2NtYKoyeEEEJcTJM2wAnqAYxbzI7/+Adw6lvRhsSTcBzHiT0I3tSpU+Hh4YHffvvN7J9RKpVISkrC7Nmz8eabb5o8R6FQQKFQ6L6vqalBbGwsqqur4e/v3+VxE0IIIS7p8k7gu1lA5CDgb/tZBufIxwAkwF2rgUH3CvpwNTU1CAgIMOv9W/QaHN7169exc+dObNpkWSW2u7s7kpOTkZWV1eY5crkccrm8q0MkhBBCiCFFNbv0DAAkEmDq24BKAZz4ErjwGzDwHna9COwmwFmzZg3Cw8Nxyy23WPRzarUa586dw4wZM6w0MkIIIYSYxE9Ryf3YpUQCzPgPEDkQSH5QtOAGsJMaHI1GgzVr1mDevHlwczOOuebOnYulS5fqvn/jjTewfft2XLlyBadOncKDDz6I69ev47HHHrP1sAkhhBDXxhcZyw2mi6RSYPgjgMxdnDFp2UUGZ+fOncjJycGjjz7a6racnBxIpfo4rLKyEgsWLEBRURGCgoIwbNgwHD58GP369bPlkAkhhBDCZ3A87a+e1a6KjG3FkiIlQgghhLThj+eBY6uB8f8AJr1i9Yez5P3bLqaoCCGEEOKAFLXs0g4zOBTgEEIIIaRzmkzU4NgJCnAIIYQQ0jmKFquo7AgFOIQQQgjpnCaDPjh2hgIcQgghhHSOqWXidoICHEIIIYR0jh0vE6cAhxBCCCGW4zjK4BBCCCHEyaiaAI2KHVMGhxBCCCFOgZ+eggTw8BV1KKZQgEMIIYQQyxlOT4m4qWZbKMAhhBBCiOXsuMAYoACHEEIIIZ2h0PbAscMCY4ACHEIIIYR0BmVwCCGEEOJ0+I02KYNDCCGEEKehoAwOIYQQQpxNk/1utAlQgEMIIYSQzrDjLsYABTiEEEII6QwqMiaEEEKI06Fl4oQQQghxOvwqKs8AccfRBgpwCCGEEGK5JqrBIYQQQoizUdAqKkIIIYQ4GyoyJoQQQojToWXihBBCCHEqqmZA1cSOKYNDCCGEEKfAr6ACKINDCCGEECfB98Dx8AWkMnHH0gYKcAghhBBiGTvfhwqgAIcQQgghlrLzAmOAAhxCCCGEWMrOl4gDFOAQQgghxFKUwenY66+/DolEYvSVmJjY7s9s3LgRiYmJ8PT0xMCBA/HHH3/YaLSEEEII0e9DRQFOu/r374/CwkLd18GDB9s89/Dhw5g9ezbmz5+P06dPY+bMmZg5cybS09NtOGJCCCHEhdn5PlSAnQQ4bm5uiIyM1H2Fhoa2ee6HH36IadOm4fnnn0dSUhLefPNNDB06FB999JENR0wIIYS4MH6ZOGVw2nf58mVER0cjISEBc+bMQU5OTpvnpqamYvLkyUbXTZ06FampqdYeJiGEEEIAh8jguIk9gFGjRmHt2rXo27cvCgsLsWzZMowfPx7p6enw82u9vr6oqAgRERFG10VERKCoqKjNx1AoFFAoFLrva2pqhPsFCCGEEFfjAEXGogc406dP1x0PGjQIo0aNQlxcHH788UfMnz9fkMdYvnw5li1bJsh9EUIIIS6PlolbLjAwEH369EFWVpbJ2yMjI1FcXGx0XXFxMSIjI9u8z6VLl6K6ulr3lZubK+iYCSGEEJfCr6Ky4wyO3QU4dXV1yM7ORlRUlMnbU1JSsGvXLqPrduzYgZSUlDbvUy6Xw9/f3+iLEEIIIZ2koAxOh/7xj39g3759uHbtGg4fPow777wTMpkMs2fPBgDMnTsXS5cu1Z3/zDPPYNu2bXjvvfdw8eJFvP766zhx4gSefPJJsX4FQgghxLVQkXHH8vLyMHv2bJSXlyMsLAzjxo3DkSNHEBYWBgDIycmBVKqPw8aMGYP169fj5ZdfxksvvYTevXtj8+bNGDBggFi/AiGEEOJaFPa/2aaE4zhO7EHYWk1NDQICAlBdXU3TVYQQQoglNGrgjWB2/Hw24NN27zqhWfL+LfoUFSGEEEIciMKg1YodT1FRgEMIIYQQ8/ErqNw8ATcPccfSDgpwCCGEEGI+BygwBijAIYQQQoglHGCJOEABDiGEEEIs0WT/K6gACnAIIYQQYgkH2IcKoACHEEIIIZZoqmaXNEVFCCGEEKeh24cqQNxxdIACHEIIIYSYj4qMCSGEEOJ0aJk4IYQQQpwOZXAIIYQQ4nRomTghhBDiQNQq4HoqoGwSeyT2jZaJE0IIIQ7k9LfAmmnA/nfEHol941dR0RQVIYQQ4gCuHWCXpZnijsPe6aaoaJk4IYQQYv8K0thlfZmow7B7Cmr0RwghhDiGphqgIpsd15eKOxZ7xnEGjf4owCGEEELsW9FZ/TFlcNrWXAdwGnZMq6gIIYQQO8dPTwFsCkalEG0odo2vv5G6Ae5e4o6lAxTgEEIIIYVnjL+naSrTDJeISyTijqUDFOAQYkscJ/YICCGmFKYZf08BjmkOskQcoACHENva+TqwPBaouCr2SAghPEUtUHaZHftFs0uqwzHNQfahAijAIcR2NGrg5FqW4r26X+zREEJ4RecAcCy4CU9i11EGxzTdEnH77oEDAG5iD4AQl1F0DmiqYsc1BaIOhRBigK+/iR6iz0xQgGOag+xDBVAGhxDb4bukAkBNnnjjIMKruAL8uwewZ7nYIxHH1QPAjleB2iKxR9I5/AqqqCGATyg7pgDHNAfZhwqgAIcQ2zGclqIMjnPJ2gU0VgLHPmNTka4i5yjw9W3A17cChz4ETqwRe0SdwxcYRw0GfMLYMdXgmMZncBygyJimqAixBbUSuH5Y/311vnhjIcKrus4uGyuB/JNA7Ehxx2NtReeAncuArB3G19cVizOermiuB8ousePoIUBjBTuuKxFtSHbNQboYA5TBIcQ2Ck6zDqASGfueMjjOpfK6/vjyjrbPcwZ1JcBX01lwI5EBQ+cCY55mt/HBgSMpSmedeX0jAb9IgwwOTVGZVK2dXveNEHccZqAAhxBbuLqPXfa8iV021wJN1eKNhwirKkd/fHm7eOOwhayd7O83uCfw5HHg9pVA5CB2W4M
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"steps = 100\n",
"key = random.key(25)\n",
"\n",
"def uniform_window(n):\n",
" return jnp.ones(n)/n\n",
"\n",
"def generate_basic_terrain(key, steps=100, yscale=1.0, xscale=10.0, window=uniform_window, window_size=5):\n",
" key, split = random.split(key)\n",
" v = random.normal(split, shape=(steps))\n",
" y = jnp.cumsum(v) * yscale\n",
" # smooth with a windowing function\n",
" y_smooth = jnp.convolve(y, window(window_size), mode='same')\n",
" # compute the x-values\n",
" x = jnp.arange(steps) * xscale\n",
" return x,y_smooth\n",
"\n",
"\n",
"x,y = generate_basic_terrain(key)\n",
" \n",
"slope = jnp.atan(jnp.diff(y, prepend=0) / 10.0) * 180 / jnp.pi\n",
"plt.plot(x,y)\n",
"plt.plot(x, slope)"
]
},
{
"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
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"[<matplotlib.lines.Line2D at 0x7101ac7f1070>]"
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]
},
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"execution_count": 4,
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"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"image/png": "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
2024-12-12 01:59:37 +00:00
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# we can compute the slope at any point along the terrain\n",
"plt.plot(x, slope)"
]
},
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{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"%run ../src/solarcarsim/physsim.py"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CarParams(mass=800, frontal_area=1.3, drag_coeff=0.18, rolling_coeff=0.002, moter_eff=0.93, wheel_radius=0.23, max_speed=30.0, solar_area=5.0, solar_eff=0.2, n_motors=2, motor=MotorParams(kv=8.43, kt=1.1, resistance=100.0, friction_coeff=0.001, iron_coeff=0.001), battery=BatteryParams(shape=(36, 19), resistance=0.0126, initial_energy=66600.0))\n"
]
}
],
"source": [
"from functools import partial\n",
"import jax\n",
"p = CarParams()\n",
"print(p)\n",
"\n",
"\n",
"def control_fn(time):\n",
" # for the first minute, go at 15 m/s\n",
" return 10 + time * 10/60\n",
"\n",
"def wrapper(curr_state, _):\n",
" vel = control_fn(curr_state[1])\n",
" next_state = forward(curr_state, 0.1, vel, p)\n",
" return next_state, next_state\n",
"\n",
"state_init = jnp.array([0.0, 0.0, 45.5e6])\n",
"_, out = jax.lax.scan(wrapper, state_init, None, length=1000)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7101ac1667b0>]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax1 = plt.subplots()\n",
"ax2 = ax1.twinx()\n",
"x = out[:,1]\n",
"ax1.plot(x, out[:,0], label=\"position\")\n",
"ax2.plot(x, out[:,2], label=\"energy\")\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"x = jnp.linspace(0,30, 1000)\n",
"dragf = drag_force(x, 1.3, 0.18, 1.184)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7101a4010b30>]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(x, dragf)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"%run ../src/solarcarsim/noise.py"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"key = random.key(123)\n",
"fractal_tex = generate_noise_texture(key, 256, 256, \"fractal\")"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7101a4373b30>"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.imshow(fractal_tex)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"import pyvista as pv\n",
"import numpy as np\n",
"a = np.array(fractal_tex)\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/saji/Documents/Code/solarcarsim/.venv/lib/python3.12/site-packages/pyvista/plotting/texture.py:682: UserWarning: Expected `image` dtype to be ``np.uint8``. `image` has been copied and converted to np.uint8.\n",
" warnings.warn(\n"
]
}
],
"source": [
"tex = pv.numpy_to_texture(a)\n"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/saji/Documents/Code/solarcarsim/.venv/lib/python3.12/site-packages/pyvista/core/utilities/points.py:55: UserWarning: Points is not a float type. This can cause issues when transforming or applying filters. Casting to ``np.float32``. Disable this by passing ``force_float=False``.\n",
" warnings.warn(\n"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"x = np.arange(0,256)\n",
"y = np.arange(0,256)\n",
"x, y = np.meshgrid(x, y)\n",
"fig, ax = plt.subplots(subplot_kw={\"projection\": \"3d\"})\n",
"ax.plot_surface(x,y,a)\n",
"grid=pv.StructuredGrid(x,y, a * 100)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7100e506cf80>]"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"key = random.key(123)\n",
"key, subkey = random.split(key)\n",
"y = generate_elevation_profile(subkey, 100, scale=100)\n",
"plt.plot(y)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7100e4f72db0>"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"key, subkey = random.split(key)\n",
"y = generate_wind_field(subkey, 100, 100)\n",
"plt.imshow(y)"
]
},
{
"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
"outputs": [
{
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 1000x400 with 3 Axes>"
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%run ../src/solarcarsim/physsim.py\n",
"from jax import random\n",
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"import matplotlib.pyplot as plt\n",
"plt.rcParams.update({\n",
" \"text.usetex\": True,\n",
"})\n",
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"wind, elevation, slope = make_environment(random.key(123))\n",
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"fig, (ax1, ax2) = plt.subplots(1,2, figsize=(10,4))\n",
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"fig.set_tight_layout('auto')\n",
"fig.suptitle(\"Generated Environment\")\n",
"\n",
"ax1.imshow(wind, aspect='auto')\n",
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"ax1.set_title(\"Wind Map\")\n",
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"ax1.set_ylabel(\"Time (sec)\")\n",
"ax1.set_xlabel(\"Distance (m)\")\n",
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"\n",
"\n",
"ax2.set_title(\"Terrain\")\n",
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"ax_slope = ax2.twinx()\n",
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"\n",
"ax2.plot(elevation, label=\"Elevation\")\n",
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"ax2.set_ylabel(\"Elevation (m)\")\n",
"ax2.set_xlabel(\"Distance (m)\")\n",
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"ax_slope.plot(slope, color='r', label='Slope')\n",
"ax_slope.set_ylabel(\"Slope (rad)\")\n",
"ax2.legend(loc=2)\n",
"ax_slope.legend(loc=1)\n",
"fig.savefig(\"environment.pdf\")"
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]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7100e4dcb050>"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# testing the indexing into the wind array.\n",
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"ax2.legend()\n",
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"# given an array of shape (10,2)\n",
"# return an array of (10,100,100)\n",
"key = random.key(0)\n",
"@jit\n",
"def lookup(x):\n",
" return lax.dynamic_slice(wind, x, (100, 100))\n",
"vlookup = vmap(lookup)\n",
"res = vlookup(jnp.array([[10,20], [9999, 600]]))\n",
"\n",
"fig, (ax1, ax2) = plt.subplots(1,2)\n",
"ax1.imshow(res[0])\n",
"ax2.imshow(res[1])"
]
},
{
"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
"outputs": [],
"source": [
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"%run ../src/solarcarsim/simv1.py\n",
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"import gymnasium as gym\n",
"from gymnasium.wrappers.jax_to_numpy import JaxToNumpy\n",
"from gymnasium.wrappers.vector import JaxToNumpy as VJaxToNumpy"
]
},
{
"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/saji/Documents/Code/solarcarsim/.venv/lib/python3.12/site-packages/stable_baselines3/common/env_checker.py:271: UserWarning: Your observation wind has an unconventional shape (neither an image, nor a 1D vector). We recommend you to flatten the observation to have only a 1D vector or use a custom policy to properly process the data.\n",
" warnings.warn(\n",
"/home/saji/Documents/Code/solarcarsim/.venv/lib/python3.12/site-packages/gymnasium/utils/env_checker.py:384: UserWarning: \u001b[33mWARN: The environment (<JaxToNumpy<SolarRaceV1 instance>>) is different from the unwrapped version (<SolarRaceV1 instance>). This could effect the environment checker as the environment most likely has a wrapper applied to it. We recommend using the raw environment for `check_env` using `env.unwrapped`.\u001b[0m\n",
" logger.warn(\n",
"/home/saji/Documents/Code/solarcarsim/.venv/lib/python3.12/site-packages/gymnasium/utils/env_checker.py:434: UserWarning: \u001b[33mWARN: Not able to test alternative render modes due to the environment not having a spec. Try instantiating the environment through `gymnasium.make`\u001b[0m\n",
" logger.warn(\n"
]
}
],
"source": [
"env = SolarRaceV1()\n",
"wrapped_env = JaxToNumpy(env)\n",
"env.reset()\n",
"from stable_baselines3.common.env_checker import check_env\n",
"from gymnasium.utils.env_checker import check_env as gym_check_env\n",
"check_env(wrapped_env)\n",
"gym_check_env(wrapped_env)"
]
},
{
"cell_type": "code",
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"execution_count": 25,
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"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Using cuda device\n",
"Wrapping the env with a `Monitor` wrapper\n",
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"Wrapping the env in a DummyVecEnv.\n",
"---------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.77e+11 |\n",
"| time/ | |\n",
"| fps | 335 |\n",
"| iterations | 1 |\n",
"| time_elapsed | 6 |\n",
"| total_timesteps | 2048 |\n",
"---------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.72e+11 |\n",
"| time/ | |\n",
"| fps | 313 |\n",
"| iterations | 2 |\n",
"| time_elapsed | 13 |\n",
"| total_timesteps | 4096 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.52e+20 |\n",
"| n_updates | 10 |\n",
"| policy_gradient_loss | 6.05e-10 |\n",
"| std | 1 |\n",
"| value_loss | 6.84e+20 |\n",
"--------------------------------------\n",
"--------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.55e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 3 |\n",
"| time_elapsed | 19 |\n",
"| total_timesteps | 6144 |\n",
"| train/ | |\n",
"| approx_kl | -2.0372681e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.5e+20 |\n",
"| n_updates | 20 |\n",
"| policy_gradient_loss | -2.82e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.52e+20 |\n",
"--------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 4 |\n",
"| time_elapsed | 26 |\n",
"| total_timesteps | 8192 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.23e+20 |\n",
"| n_updates | 30 |\n",
"| policy_gradient_loss | -6.43e-10 |\n",
"| std | 1 |\n",
"| value_loss | 6.91e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 5 |\n",
"| time_elapsed | 33 |\n",
"| total_timesteps | 10240 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.09e+20 |\n",
"| n_updates | 40 |\n",
"| policy_gradient_loss | -1.82e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.55e+20 |\n",
"---------------------------------------\n",
"--------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 6 |\n",
"| time_elapsed | 39 |\n",
"| total_timesteps | 12288 |\n",
"| train/ | |\n",
"| approx_kl | -1.1641532e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.86e+20 |\n",
"| n_updates | 50 |\n",
"| policy_gradient_loss | 7.23e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.96e+20 |\n",
"--------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 7 |\n",
"| time_elapsed | 46 |\n",
"| total_timesteps | 14336 |\n",
"| train/ | |\n",
"| approx_kl | 5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.05e+20 |\n",
"| n_updates | 60 |\n",
"| policy_gradient_loss | -6.76e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.04e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.6e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 8 |\n",
"| time_elapsed | 53 |\n",
"| total_timesteps | 16384 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.27e+20 |\n",
"| n_updates | 70 |\n",
"| policy_gradient_loss | 6.42e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.66e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 9 |\n",
"| time_elapsed | 59 |\n",
"| total_timesteps | 18432 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.38e+20 |\n",
"| n_updates | 80 |\n",
"| policy_gradient_loss | -2.08e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.94e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 10 |\n",
"| time_elapsed | 66 |\n",
"| total_timesteps | 20480 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.77e+20 |\n",
"| n_updates | 90 |\n",
"| policy_gradient_loss | -4.44e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.87e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 11 |\n",
"| time_elapsed | 73 |\n",
"| total_timesteps | 22528 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.84e+20 |\n",
"| n_updates | 100 |\n",
"| policy_gradient_loss | -3.09e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.7e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 12 |\n",
"| time_elapsed | 79 |\n",
"| total_timesteps | 24576 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.47e+20 |\n",
"| n_updates | 110 |\n",
"| policy_gradient_loss | 5.43e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.17e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 13 |\n",
"| time_elapsed | 86 |\n",
"| total_timesteps | 26624 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.95e+20 |\n",
"| n_updates | 120 |\n",
"| policy_gradient_loss | -4.86e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.55e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 14 |\n",
"| time_elapsed | 92 |\n",
"| total_timesteps | 28672 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.6e+20 |\n",
"| n_updates | 130 |\n",
"| policy_gradient_loss | 4.9e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.01e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 15 |\n",
"| time_elapsed | 99 |\n",
"| total_timesteps | 30720 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.84e+20 |\n",
"| n_updates | 140 |\n",
"| policy_gradient_loss | -7.74e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.1e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.6e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 16 |\n",
"| time_elapsed | 106 |\n",
"| total_timesteps | 32768 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.22e+20 |\n",
"| n_updates | 150 |\n",
"| policy_gradient_loss | -2.27e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.73e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.6e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 17 |\n",
"| time_elapsed | 112 |\n",
"| total_timesteps | 34816 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.86e+20 |\n",
"| n_updates | 160 |\n",
"| policy_gradient_loss | -6.14e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.47e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.6e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 18 |\n",
"| time_elapsed | 119 |\n",
"| total_timesteps | 36864 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.05e+20 |\n",
"| n_updates | 170 |\n",
"| policy_gradient_loss | 2.55e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.59e+20 |\n",
"------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.6e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 19 |\n",
"| time_elapsed | 126 |\n",
"| total_timesteps | 38912 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.49e+20 |\n",
"| n_updates | 180 |\n",
"| policy_gradient_loss | 3.69e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.98e+20 |\n",
"--------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 20 |\n",
"| time_elapsed | 132 |\n",
"| total_timesteps | 40960 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.71e+20 |\n",
"| n_updates | 190 |\n",
"| policy_gradient_loss | 1.04e-08 |\n",
"| std | 1 |\n",
"| value_loss | 7.52e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 21 |\n",
"| time_elapsed | 139 |\n",
"| total_timesteps | 43008 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.89e+20 |\n",
"| n_updates | 200 |\n",
"| policy_gradient_loss | -1.36e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.76e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 22 |\n",
"| time_elapsed | 146 |\n",
"| total_timesteps | 45056 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.69e+20 |\n",
"| n_updates | 210 |\n",
"| policy_gradient_loss | -4.9e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.35e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 23 |\n",
"| time_elapsed | 153 |\n",
"| total_timesteps | 47104 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.12e+20 |\n",
"| n_updates | 220 |\n",
"| policy_gradient_loss | 2.67e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 24 |\n",
"| time_elapsed | 159 |\n",
"| total_timesteps | 49152 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.49e+20 |\n",
"| n_updates | 230 |\n",
"| policy_gradient_loss | 4.05e-10 |\n",
"| std | 1 |\n",
"| value_loss | 6.71e+20 |\n",
"--------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 25 |\n",
"| time_elapsed | 166 |\n",
"| total_timesteps | 51200 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.78e+20 |\n",
"| n_updates | 240 |\n",
"| policy_gradient_loss | 8.82e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.44e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 26 |\n",
"| time_elapsed | 173 |\n",
"| total_timesteps | 53248 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.82e+20 |\n",
"| n_updates | 250 |\n",
"| policy_gradient_loss | -6.17e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.43e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 27 |\n",
"| time_elapsed | 179 |\n",
"| total_timesteps | 55296 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.37e+20 |\n",
"| n_updates | 260 |\n",
"| policy_gradient_loss | -6.08e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.17e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 28 |\n",
"| time_elapsed | 186 |\n",
"| total_timesteps | 57344 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.01e+20 |\n",
"| n_updates | 270 |\n",
"| policy_gradient_loss | -3.07e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.19e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 29 |\n",
"| time_elapsed | 192 |\n",
"| total_timesteps | 59392 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.78e+20 |\n",
"| n_updates | 280 |\n",
"| policy_gradient_loss | -1.64e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.88e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.6e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 30 |\n",
"| time_elapsed | 199 |\n",
"| total_timesteps | 61440 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.14e+20 |\n",
"| n_updates | 290 |\n",
"| policy_gradient_loss | 1.87e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.11e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 31 |\n",
"| time_elapsed | 206 |\n",
"| total_timesteps | 63488 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.92e+20 |\n",
"| n_updates | 300 |\n",
"| policy_gradient_loss | 2.99e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.51e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 32 |\n",
"| time_elapsed | 212 |\n",
"| total_timesteps | 65536 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.27e+20 |\n",
"| n_updates | 310 |\n",
"| policy_gradient_loss | 4.27e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.65e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 33 |\n",
"| time_elapsed | 219 |\n",
"| total_timesteps | 67584 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.35e+20 |\n",
"| n_updates | 320 |\n",
"| policy_gradient_loss | -7.1e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.61e+20 |\n",
"--------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 34 |\n",
"| time_elapsed | 225 |\n",
"| total_timesteps | 69632 |\n",
"| train/ | |\n",
"| approx_kl | 5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.07e+20 |\n",
"| n_updates | 330 |\n",
"| policy_gradient_loss | 4.04e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.28e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 35 |\n",
"| time_elapsed | 232 |\n",
"| total_timesteps | 71680 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.25e+20 |\n",
"| n_updates | 340 |\n",
"| policy_gradient_loss | -1.33e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.93e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 36 |\n",
"| time_elapsed | 239 |\n",
"| total_timesteps | 73728 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.7e+20 |\n",
"| n_updates | 350 |\n",
"| policy_gradient_loss | 5.44e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.46e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 37 |\n",
"| time_elapsed | 245 |\n",
"| total_timesteps | 75776 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.51e+20 |\n",
"| n_updates | 360 |\n",
"| policy_gradient_loss | 7.37e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.79e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 38 |\n",
"| time_elapsed | 252 |\n",
"| total_timesteps | 77824 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.31e+20 |\n",
"| n_updates | 370 |\n",
"| policy_gradient_loss | 7.54e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.89e+20 |\n",
"------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 39 |\n",
"| time_elapsed | 258 |\n",
"| total_timesteps | 79872 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.61e+20 |\n",
"| n_updates | 380 |\n",
"| policy_gradient_loss | -1.65e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.02e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 40 |\n",
"| time_elapsed | 265 |\n",
"| total_timesteps | 81920 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.13e+20 |\n",
"| n_updates | 390 |\n",
"| policy_gradient_loss | -1.05e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.72e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 41 |\n",
"| time_elapsed | 271 |\n",
"| total_timesteps | 83968 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.44e+20 |\n",
"| n_updates | 400 |\n",
"| policy_gradient_loss | 9.9e-11 |\n",
"| std | 1 |\n",
"| value_loss | 7.51e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 42 |\n",
"| time_elapsed | 278 |\n",
"| total_timesteps | 86016 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.82e+20 |\n",
"| n_updates | 410 |\n",
"| policy_gradient_loss | 3.73e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.65e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 43 |\n",
"| time_elapsed | 285 |\n",
"| total_timesteps | 88064 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.15e+20 |\n",
"| n_updates | 420 |\n",
"| policy_gradient_loss | 1.07e-08 |\n",
"| std | 1 |\n",
"| value_loss | 8.22e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 44 |\n",
"| time_elapsed | 291 |\n",
"| total_timesteps | 90112 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.26e+20 |\n",
"| n_updates | 430 |\n",
"| policy_gradient_loss | -6.7e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.38e+20 |\n",
"--------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 45 |\n",
"| time_elapsed | 298 |\n",
"| total_timesteps | 92160 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.17e+20 |\n",
"| n_updates | 440 |\n",
"| policy_gradient_loss | -3.11e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.41e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 46 |\n",
"| time_elapsed | 304 |\n",
"| total_timesteps | 94208 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.36e+20 |\n",
"| n_updates | 450 |\n",
"| policy_gradient_loss | -1.6e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.61e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 47 |\n",
"| time_elapsed | 311 |\n",
"| total_timesteps | 96256 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.51e+20 |\n",
"| n_updates | 460 |\n",
"| policy_gradient_loss | -2.65e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.34e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 48 |\n",
"| time_elapsed | 318 |\n",
"| total_timesteps | 98304 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.17e+20 |\n",
"| n_updates | 470 |\n",
"| policy_gradient_loss | -2.4e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.91e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 49 |\n",
"| time_elapsed | 325 |\n",
"| total_timesteps | 100352 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.99e+20 |\n",
"| n_updates | 480 |\n",
"| policy_gradient_loss | -1.58e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.04e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 50 |\n",
"| time_elapsed | 331 |\n",
"| total_timesteps | 102400 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.47e+20 |\n",
"| n_updates | 490 |\n",
"| policy_gradient_loss | 1.78e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.01e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 51 |\n",
"| time_elapsed | 338 |\n",
"| total_timesteps | 104448 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.19e+20 |\n",
"| n_updates | 500 |\n",
"| policy_gradient_loss | -4e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.91e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.67e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 52 |\n",
"| time_elapsed | 345 |\n",
"| total_timesteps | 106496 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.02e+20 |\n",
"| n_updates | 510 |\n",
"| policy_gradient_loss | 7.63e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.35e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 53 |\n",
"| time_elapsed | 351 |\n",
"| total_timesteps | 108544 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.7e+20 |\n",
"| n_updates | 520 |\n",
"| policy_gradient_loss | -4.46e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.62e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.66e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 54 |\n",
"| time_elapsed | 358 |\n",
"| total_timesteps | 110592 |\n",
"| train/ | |\n",
"| approx_kl | 1.7462298e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.5e+20 |\n",
"| n_updates | 530 |\n",
"| policy_gradient_loss | 2.7e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.65e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.66e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 55 |\n",
"| time_elapsed | 365 |\n",
"| total_timesteps | 112640 |\n",
"| train/ | |\n",
"| approx_kl | 2.3283064e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.57e+20 |\n",
"| n_updates | 540 |\n",
"| policy_gradient_loss | -4.66e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.58e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.68e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 56 |\n",
"| time_elapsed | 371 |\n",
"| total_timesteps | 114688 |\n",
"| train/ | |\n",
"| approx_kl | 1.7462298e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.89e+20 |\n",
"| n_updates | 550 |\n",
"| policy_gradient_loss | -1.26e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.07e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.66e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 57 |\n",
"| time_elapsed | 378 |\n",
"| total_timesteps | 116736 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.73e+20 |\n",
"| n_updates | 560 |\n",
"| policy_gradient_loss | 3.36e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.93e+20 |\n",
"------------------------------------------\n",
"--------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 58 |\n",
"| time_elapsed | 385 |\n",
"| total_timesteps | 118784 |\n",
"| train/ | |\n",
"| approx_kl | -2.0372681e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.49e+20 |\n",
"| n_updates | 570 |\n",
"| policy_gradient_loss | 3.67e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.24e+20 |\n",
"--------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 59 |\n",
"| time_elapsed | 391 |\n",
"| total_timesteps | 120832 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.87e+20 |\n",
"| n_updates | 580 |\n",
"| policy_gradient_loss | -2.44e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.7e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 60 |\n",
"| time_elapsed | 398 |\n",
"| total_timesteps | 122880 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.35e+20 |\n",
"| n_updates | 590 |\n",
"| policy_gradient_loss | 9.02e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.98e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 61 |\n",
"| time_elapsed | 404 |\n",
"| total_timesteps | 124928 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.22e+20 |\n",
"| n_updates | 600 |\n",
"| policy_gradient_loss | -1.74e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.01e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 62 |\n",
"| time_elapsed | 411 |\n",
"| total_timesteps | 126976 |\n",
"| train/ | |\n",
"| approx_kl | 1.1641532e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.65e+20 |\n",
"| n_updates | 610 |\n",
"| policy_gradient_loss | 4.34e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.57e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 63 |\n",
"| time_elapsed | 418 |\n",
"| total_timesteps | 129024 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.07e+20 |\n",
"| n_updates | 620 |\n",
"| policy_gradient_loss | 8.41e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.21e+20 |\n",
"--------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 64 |\n",
"| time_elapsed | 424 |\n",
"| total_timesteps | 131072 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.94e+20 |\n",
"| n_updates | 630 |\n",
"| policy_gradient_loss | 4.04e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.44e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 65 |\n",
"| time_elapsed | 431 |\n",
"| total_timesteps | 133120 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.45e+20 |\n",
"| n_updates | 640 |\n",
"| policy_gradient_loss | -4.02e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.26e+20 |\n",
"---------------------------------------\n",
"--------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 66 |\n",
"| time_elapsed | 437 |\n",
"| total_timesteps | 135168 |\n",
"| train/ | |\n",
"| approx_kl | -1.4551915e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.24e+20 |\n",
"| n_updates | 650 |\n",
"| policy_gradient_loss | -7.53e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.25e+20 |\n",
"--------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 67 |\n",
"| time_elapsed | 444 |\n",
"| total_timesteps | 137216 |\n",
"| train/ | |\n",
"| approx_kl | 2.6193447e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.49e+20 |\n",
"| n_updates | 660 |\n",
"| policy_gradient_loss | -9.75e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.22e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 68 |\n",
"| time_elapsed | 451 |\n",
"| total_timesteps | 139264 |\n",
"| train/ | |\n",
"| approx_kl | 5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.36e+20 |\n",
"| n_updates | 670 |\n",
"| policy_gradient_loss | 4.05e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.64e+20 |\n",
"------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 69 |\n",
"| time_elapsed | 457 |\n",
"| total_timesteps | 141312 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.4e+20 |\n",
"| n_updates | 680 |\n",
"| policy_gradient_loss | 2.14e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.54e+20 |\n",
"--------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 70 |\n",
"| time_elapsed | 464 |\n",
"| total_timesteps | 143360 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.52e+20 |\n",
"| n_updates | 690 |\n",
"| policy_gradient_loss | 4.44e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.43e+20 |\n",
"--------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 71 |\n",
"| time_elapsed | 471 |\n",
"| total_timesteps | 145408 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.75e+20 |\n",
"| n_updates | 700 |\n",
"| policy_gradient_loss | 1.57e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.35e+20 |\n",
"--------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 72 |\n",
"| time_elapsed | 478 |\n",
"| total_timesteps | 147456 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.54e+20 |\n",
"| n_updates | 710 |\n",
"| policy_gradient_loss | 3.18e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.9e+20 |\n",
"--------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 73 |\n",
"| time_elapsed | 485 |\n",
"| total_timesteps | 149504 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.12e+20 |\n",
"| n_updates | 720 |\n",
"| policy_gradient_loss | -3.43e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 74 |\n",
"| time_elapsed | 491 |\n",
"| total_timesteps | 151552 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.43e+20 |\n",
"| n_updates | 730 |\n",
"| policy_gradient_loss | 3.68e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.32e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 75 |\n",
"| time_elapsed | 498 |\n",
"| total_timesteps | 153600 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.3e+20 |\n",
"| n_updates | 740 |\n",
"| policy_gradient_loss | 5.75e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.27e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 76 |\n",
"| time_elapsed | 505 |\n",
"| total_timesteps | 155648 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.25e+20 |\n",
"| n_updates | 750 |\n",
"| policy_gradient_loss | -7.98e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.22e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 77 |\n",
"| time_elapsed | 511 |\n",
"| total_timesteps | 157696 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.46e+20 |\n",
"| n_updates | 760 |\n",
"| policy_gradient_loss | -9.47e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.11e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 78 |\n",
"| time_elapsed | 518 |\n",
"| total_timesteps | 159744 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.8e+20 |\n",
"| n_updates | 770 |\n",
"| policy_gradient_loss | 7.7e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.45e+20 |\n",
"--------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 79 |\n",
"| time_elapsed | 525 |\n",
"| total_timesteps | 161792 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.52e+20 |\n",
"| n_updates | 780 |\n",
"| policy_gradient_loss | -1.09e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.03e+20 |\n",
"------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 80 |\n",
"| time_elapsed | 531 |\n",
"| total_timesteps | 163840 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.44e+20 |\n",
"| n_updates | 790 |\n",
"| policy_gradient_loss | -1.34e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.34e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 81 |\n",
"| time_elapsed | 538 |\n",
"| total_timesteps | 165888 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.67e+20 |\n",
"| n_updates | 800 |\n",
"| policy_gradient_loss | -4.87e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.82e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 82 |\n",
"| time_elapsed | 545 |\n",
"| total_timesteps | 167936 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.25e+20 |\n",
"| n_updates | 810 |\n",
"| policy_gradient_loss | 6.9e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.02e+20 |\n",
"--------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 83 |\n",
"| time_elapsed | 551 |\n",
"| total_timesteps | 169984 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.73e+20 |\n",
"| n_updates | 820 |\n",
"| policy_gradient_loss | 1.06e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.56e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 84 |\n",
"| time_elapsed | 558 |\n",
"| total_timesteps | 172032 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.39e+20 |\n",
"| n_updates | 830 |\n",
"| policy_gradient_loss | 6.23e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.77e+20 |\n",
"--------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 85 |\n",
"| time_elapsed | 565 |\n",
"| total_timesteps | 174080 |\n",
"| train/ | |\n",
"| approx_kl | 2.0372681e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.28e+20 |\n",
"| n_updates | 840 |\n",
"| policy_gradient_loss | 2.09e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.28e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 86 |\n",
"| time_elapsed | 572 |\n",
"| total_timesteps | 176128 |\n",
"| train/ | |\n",
"| approx_kl | -1.7462298e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.39e+20 |\n",
"| n_updates | 850 |\n",
"| policy_gradient_loss | 3.62e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.58e+20 |\n",
"--------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.66e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 87 |\n",
"| time_elapsed | 578 |\n",
"| total_timesteps | 178176 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -2.38e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.77e+20 |\n",
"| n_updates | 860 |\n",
"| policy_gradient_loss | -6e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.84e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.66e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 88 |\n",
"| time_elapsed | 585 |\n",
"| total_timesteps | 180224 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.77e+20 |\n",
"| n_updates | 870 |\n",
"| policy_gradient_loss | -1.66e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.08e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.66e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 89 |\n",
"| time_elapsed | 592 |\n",
"| total_timesteps | 182272 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.75e+20 |\n",
"| n_updates | 880 |\n",
"| policy_gradient_loss | -5.66e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.9e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.66e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 90 |\n",
"| time_elapsed | 598 |\n",
"| total_timesteps | 184320 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.41e+20 |\n",
"| n_updates | 890 |\n",
"| policy_gradient_loss | 1.07e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.39e+20 |\n",
"------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.67e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 91 |\n",
"| time_elapsed | 605 |\n",
"| total_timesteps | 186368 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.59e+20 |\n",
"| n_updates | 900 |\n",
"| policy_gradient_loss | -5.2e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.35e+20 |\n",
"--------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.66e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 92 |\n",
"| time_elapsed | 612 |\n",
"| total_timesteps | 188416 |\n",
"| train/ | |\n",
"| approx_kl | 8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.91e+20 |\n",
"| n_updates | 910 |\n",
"| policy_gradient_loss | -1.26e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.09e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 93 |\n",
"| time_elapsed | 619 |\n",
"| total_timesteps | 190464 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.86e+20 |\n",
"| n_updates | 920 |\n",
"| policy_gradient_loss | -1.74e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.42e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 94 |\n",
"| time_elapsed | 626 |\n",
"| total_timesteps | 192512 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.13e+20 |\n",
"| n_updates | 930 |\n",
"| policy_gradient_loss | 7.95e-10 |\n",
"| std | 1 |\n",
"| value_loss | 8.04e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 95 |\n",
"| time_elapsed | 633 |\n",
"| total_timesteps | 194560 |\n",
"| train/ | |\n",
"| approx_kl | 1.4551915e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.92e+20 |\n",
"| n_updates | 940 |\n",
"| policy_gradient_loss | 1.34e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.42e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.67e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 96 |\n",
"| time_elapsed | 639 |\n",
"| total_timesteps | 196608 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.69e+20 |\n",
"| n_updates | 950 |\n",
"| policy_gradient_loss | 1.96e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.04e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.67e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 97 |\n",
"| time_elapsed | 646 |\n",
"| total_timesteps | 198656 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.81e+20 |\n",
"| n_updates | 960 |\n",
"| policy_gradient_loss | 5.85e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.1e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.67e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 98 |\n",
"| time_elapsed | 653 |\n",
"| total_timesteps | 200704 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.93e+20 |\n",
"| n_updates | 970 |\n",
"| policy_gradient_loss | 4.95e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.2e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.68e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 99 |\n",
"| time_elapsed | 660 |\n",
"| total_timesteps | 202752 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.75e+20 |\n",
"| n_updates | 980 |\n",
"| policy_gradient_loss | -3.31e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.1e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.69e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 100 |\n",
"| time_elapsed | 666 |\n",
"| total_timesteps | 204800 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.16e+20 |\n",
"| n_updates | 990 |\n",
"| policy_gradient_loss | -4.21e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.06e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.69e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 101 |\n",
"| time_elapsed | 673 |\n",
"| total_timesteps | 206848 |\n",
"| train/ | |\n",
"| approx_kl | -8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.1e+20 |\n",
"| n_updates | 1000 |\n",
"| policy_gradient_loss | 3.49e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.6e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.7e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 102 |\n",
"| time_elapsed | 679 |\n",
"| total_timesteps | 208896 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.46e+20 |\n",
"| n_updates | 1010 |\n",
"| policy_gradient_loss | -4.23e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.04e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.7e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 103 |\n",
"| time_elapsed | 686 |\n",
"| total_timesteps | 210944 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.53e+20 |\n",
"| n_updates | 1020 |\n",
"| policy_gradient_loss | -2.27e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.27e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.69e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 104 |\n",
"| time_elapsed | 693 |\n",
"| total_timesteps | 212992 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.15e+20 |\n",
"| n_updates | 1030 |\n",
"| policy_gradient_loss | -6.14e-10 |\n",
"| std | 1 |\n",
"| value_loss | 8.04e+20 |\n",
"---------------------------------------\n",
"--------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.7e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 105 |\n",
"| time_elapsed | 699 |\n",
"| total_timesteps | 215040 |\n",
"| train/ | |\n",
"| approx_kl | -1.4551915e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.98e+20 |\n",
"| n_updates | 1040 |\n",
"| policy_gradient_loss | 4.92e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.48e+20 |\n",
"--------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.69e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 106 |\n",
"| time_elapsed | 706 |\n",
"| total_timesteps | 217088 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.4e+20 |\n",
"| n_updates | 1050 |\n",
"| policy_gradient_loss | 2.12e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.6e+20 |\n",
"--------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.68e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 107 |\n",
"| time_elapsed | 713 |\n",
"| total_timesteps | 219136 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.93e+20 |\n",
"| n_updates | 1060 |\n",
"| policy_gradient_loss | 1.12e-08 |\n",
"| std | 1 |\n",
"| value_loss | 7.37e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.68e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 108 |\n",
"| time_elapsed | 719 |\n",
"| total_timesteps | 221184 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.51e+20 |\n",
"| n_updates | 1070 |\n",
"| policy_gradient_loss | -7.58e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.43e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.69e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 109 |\n",
"| time_elapsed | 726 |\n",
"| total_timesteps | 223232 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.42e+20 |\n",
"| n_updates | 1080 |\n",
"| policy_gradient_loss | -1.91e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.34e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.69e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 110 |\n",
"| time_elapsed | 733 |\n",
"| total_timesteps | 225280 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.01e+20 |\n",
"| n_updates | 1090 |\n",
"| policy_gradient_loss | -3.17e-10 |\n",
"| std | 1 |\n",
"| value_loss | 6.45e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.69e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 111 |\n",
"| time_elapsed | 739 |\n",
"| total_timesteps | 227328 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.57e+20 |\n",
"| n_updates | 1100 |\n",
"| policy_gradient_loss | -1.47e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.72e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.69e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 112 |\n",
"| time_elapsed | 746 |\n",
"| total_timesteps | 229376 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.44e+20 |\n",
"| n_updates | 1110 |\n",
"| policy_gradient_loss | -7.1e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.55e+20 |\n",
"--------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.69e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 113 |\n",
"| time_elapsed | 753 |\n",
"| total_timesteps | 231424 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.91e+20 |\n",
"| n_updates | 1120 |\n",
"| policy_gradient_loss | 1.29e-08 |\n",
"| std | 1 |\n",
"| value_loss | 7.22e+20 |\n",
"--------------------------------------\n",
"--------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.68e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 114 |\n",
"| time_elapsed | 760 |\n",
"| total_timesteps | 233472 |\n",
"| train/ | |\n",
"| approx_kl | -1.1641532e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.18e+20 |\n",
"| n_updates | 1130 |\n",
"| policy_gradient_loss | -3.49e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.99e+20 |\n",
"--------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.69e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 115 |\n",
"| time_elapsed | 766 |\n",
"| total_timesteps | 235520 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.49e+20 |\n",
"| n_updates | 1140 |\n",
"| policy_gradient_loss | -5.62e-10 |\n",
"| std | 1 |\n",
"| value_loss | 6.98e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.68e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 116 |\n",
"| time_elapsed | 773 |\n",
"| total_timesteps | 237568 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -2.38e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.13e+20 |\n",
"| n_updates | 1150 |\n",
"| policy_gradient_loss | 2.58e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.67e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.67e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 117 |\n",
"| time_elapsed | 779 |\n",
"| total_timesteps | 239616 |\n",
"| train/ | |\n",
"| approx_kl | 2.3283064e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.24e+20 |\n",
"| n_updates | 1160 |\n",
"| policy_gradient_loss | -4.64e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.08e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.67e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 118 |\n",
"| time_elapsed | 786 |\n",
"| total_timesteps | 241664 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.8e+20 |\n",
"| n_updates | 1170 |\n",
"| policy_gradient_loss | -1.2e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.3e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 119 |\n",
"| time_elapsed | 792 |\n",
"| total_timesteps | 243712 |\n",
"| train/ | |\n",
"| approx_kl | 1.1641532e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.04e+20 |\n",
"| n_updates | 1180 |\n",
"| policy_gradient_loss | -3.09e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.8e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.66e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 120 |\n",
"| time_elapsed | 799 |\n",
"| total_timesteps | 245760 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.45e+20 |\n",
"| n_updates | 1190 |\n",
"| policy_gradient_loss | 4.03e-10 |\n",
"| std | 1 |\n",
"| value_loss | 6.61e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.66e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 121 |\n",
"| time_elapsed | 805 |\n",
"| total_timesteps | 247808 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.63e+20 |\n",
"| n_updates | 1200 |\n",
"| policy_gradient_loss | -5.43e-10 |\n",
"| std | 1 |\n",
"| value_loss | 8.45e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.66e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 122 |\n",
"| time_elapsed | 811 |\n",
"| total_timesteps | 249856 |\n",
"| train/ | |\n",
"| approx_kl | 5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.99e+20 |\n",
"| n_updates | 1210 |\n",
"| policy_gradient_loss | 1.86e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.59e+20 |\n",
"------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 123 |\n",
"| time_elapsed | 818 |\n",
"| total_timesteps | 251904 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.85e+20 |\n",
"| n_updates | 1220 |\n",
"| policy_gradient_loss | -1.14e-08 |\n",
"| std | 1 |\n",
"| value_loss | 7.44e+20 |\n",
"------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 124 |\n",
"| time_elapsed | 824 |\n",
"| total_timesteps | 253952 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.3e+20 |\n",
"| n_updates | 1230 |\n",
"| policy_gradient_loss | 2.21e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.75e+20 |\n",
"--------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 125 |\n",
"| time_elapsed | 830 |\n",
"| total_timesteps | 256000 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.37e+20 |\n",
"| n_updates | 1240 |\n",
"| policy_gradient_loss | -4.63e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.79e+20 |\n",
"------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 126 |\n",
"| time_elapsed | 836 |\n",
"| total_timesteps | 258048 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.11e+20 |\n",
"| n_updates | 1250 |\n",
"| policy_gradient_loss | -5.74e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.72e+20 |\n",
"------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 127 |\n",
"| time_elapsed | 843 |\n",
"| total_timesteps | 260096 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.79e+20 |\n",
"| n_updates | 1260 |\n",
"| policy_gradient_loss | 3.38e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.82e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 128 |\n",
"| time_elapsed | 849 |\n",
"| total_timesteps | 262144 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.91e+20 |\n",
"| n_updates | 1270 |\n",
"| policy_gradient_loss | 3.41e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.62e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 129 |\n",
"| time_elapsed | 856 |\n",
"| total_timesteps | 264192 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.33e+20 |\n",
"| n_updates | 1280 |\n",
"| policy_gradient_loss | 4.79e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.22e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 130 |\n",
"| time_elapsed | 862 |\n",
"| total_timesteps | 266240 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.22e+20 |\n",
"| n_updates | 1290 |\n",
"| policy_gradient_loss | -1.57e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.75e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 131 |\n",
"| time_elapsed | 868 |\n",
"| total_timesteps | 268288 |\n",
"| train/ | |\n",
"| approx_kl | 1.4551915e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.14e+20 |\n",
"| n_updates | 1300 |\n",
"| policy_gradient_loss | -3.55e-10 |\n",
"| std | 1 |\n",
"| value_loss | 8.36e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 132 |\n",
"| time_elapsed | 875 |\n",
"| total_timesteps | 270336 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.27e+20 |\n",
"| n_updates | 1310 |\n",
"| policy_gradient_loss | 6.04e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.36e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 133 |\n",
"| time_elapsed | 881 |\n",
"| total_timesteps | 272384 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.09e+20 |\n",
"| n_updates | 1320 |\n",
"| policy_gradient_loss | -5.18e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.34e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 134 |\n",
"| time_elapsed | 887 |\n",
"| total_timesteps | 274432 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.58e+20 |\n",
"| n_updates | 1330 |\n",
"| policy_gradient_loss | -1.22e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.27e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 135 |\n",
"| time_elapsed | 894 |\n",
"| total_timesteps | 276480 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.35e+20 |\n",
"| n_updates | 1340 |\n",
"| policy_gradient_loss | -2.39e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.82e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 136 |\n",
"| time_elapsed | 900 |\n",
"| total_timesteps | 278528 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.12e+20 |\n",
"| n_updates | 1350 |\n",
"| policy_gradient_loss | -2.61e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.26e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 137 |\n",
"| time_elapsed | 907 |\n",
"| total_timesteps | 280576 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.59e+20 |\n",
"| n_updates | 1360 |\n",
"| policy_gradient_loss | -4.31e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.52e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 138 |\n",
"| time_elapsed | 913 |\n",
"| total_timesteps | 282624 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.44e+20 |\n",
"| n_updates | 1370 |\n",
"| policy_gradient_loss | 1.35e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.26e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 139 |\n",
"| time_elapsed | 919 |\n",
"| total_timesteps | 284672 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.68e+20 |\n",
"| n_updates | 1380 |\n",
"| policy_gradient_loss | 4.9e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.15e+20 |\n",
"--------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 140 |\n",
"| time_elapsed | 926 |\n",
"| total_timesteps | 286720 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.53e+20 |\n",
"| n_updates | 1390 |\n",
"| policy_gradient_loss | -3.98e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.89e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 141 |\n",
"| time_elapsed | 932 |\n",
"| total_timesteps | 288768 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 5.04e+20 |\n",
"| n_updates | 1400 |\n",
"| policy_gradient_loss | 3.41e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.59e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.57e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 142 |\n",
"| time_elapsed | 938 |\n",
"| total_timesteps | 290816 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.64e+20 |\n",
"| n_updates | 1410 |\n",
"| policy_gradient_loss | -2.99e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.82e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.57e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 143 |\n",
"| time_elapsed | 944 |\n",
"| total_timesteps | 292864 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.05e+20 |\n",
"| n_updates | 1420 |\n",
"| policy_gradient_loss | -1.03e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.54e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 144 |\n",
"| time_elapsed | 951 |\n",
"| total_timesteps | 294912 |\n",
"| train/ | |\n",
"| approx_kl | 8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.29e+20 |\n",
"| n_updates | 1430 |\n",
"| policy_gradient_loss | -5.52e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.57e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.57e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 145 |\n",
"| time_elapsed | 957 |\n",
"| total_timesteps | 296960 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.79e+20 |\n",
"| n_updates | 1440 |\n",
"| policy_gradient_loss | 9.34e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.39e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 146 |\n",
"| time_elapsed | 963 |\n",
"| total_timesteps | 299008 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.6e+20 |\n",
"| n_updates | 1450 |\n",
"| policy_gradient_loss | -1.21e-08 |\n",
"| std | 1 |\n",
"| value_loss | 7.85e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.57e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 147 |\n",
"| time_elapsed | 970 |\n",
"| total_timesteps | 301056 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.8e+20 |\n",
"| n_updates | 1460 |\n",
"| policy_gradient_loss | -2.56e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.97e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 148 |\n",
"| time_elapsed | 976 |\n",
"| total_timesteps | 303104 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.77e+20 |\n",
"| n_updates | 1470 |\n",
"| policy_gradient_loss | -5.72e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.11e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.6e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 149 |\n",
"| time_elapsed | 983 |\n",
"| total_timesteps | 305152 |\n",
"| train/ | |\n",
"| approx_kl | -8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.35e+20 |\n",
"| n_updates | 1480 |\n",
"| policy_gradient_loss | -3.17e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.27e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 150 |\n",
"| time_elapsed | 989 |\n",
"| total_timesteps | 307200 |\n",
"| train/ | |\n",
"| approx_kl | -8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.86e+20 |\n",
"| n_updates | 1490 |\n",
"| policy_gradient_loss | -1.05e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.64e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 151 |\n",
"| time_elapsed | 995 |\n",
"| total_timesteps | 309248 |\n",
"| train/ | |\n",
"| approx_kl | 5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.36e+20 |\n",
"| n_updates | 1500 |\n",
"| policy_gradient_loss | -5.21e-10 |\n",
"| std | 1 |\n",
"| value_loss | 8.21e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.6e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 152 |\n",
"| time_elapsed | 1002 |\n",
"| total_timesteps | 311296 |\n",
"| train/ | |\n",
"| approx_kl | 1.7462298e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4e+20 |\n",
"| n_updates | 1510 |\n",
"| policy_gradient_loss | 2.01e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.84e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.6e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 153 |\n",
"| time_elapsed | 1008 |\n",
"| total_timesteps | 313344 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.96e+20 |\n",
"| n_updates | 1520 |\n",
"| policy_gradient_loss | 1.63e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.87e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 154 |\n",
"| time_elapsed | 1014 |\n",
"| total_timesteps | 315392 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.64e+20 |\n",
"| n_updates | 1530 |\n",
"| policy_gradient_loss | -3.11e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.15e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 155 |\n",
"| time_elapsed | 1020 |\n",
"| total_timesteps | 317440 |\n",
"| train/ | |\n",
"| approx_kl | 1.1641532e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.85e+20 |\n",
"| n_updates | 1540 |\n",
"| policy_gradient_loss | -8.58e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.28e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.6e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 156 |\n",
"| time_elapsed | 1027 |\n",
"| total_timesteps | 319488 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.16e+20 |\n",
"| n_updates | 1550 |\n",
"| policy_gradient_loss | -2.01e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.75e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 157 |\n",
"| time_elapsed | 1033 |\n",
"| total_timesteps | 321536 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.25e+20 |\n",
"| n_updates | 1560 |\n",
"| policy_gradient_loss | -1.96e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.13e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 158 |\n",
"| time_elapsed | 1040 |\n",
"| total_timesteps | 323584 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -2.38e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.72e+20 |\n",
"| n_updates | 1570 |\n",
"| policy_gradient_loss | -2.49e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.97e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 159 |\n",
"| time_elapsed | 1046 |\n",
"| total_timesteps | 325632 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.67e+20 |\n",
"| n_updates | 1580 |\n",
"| policy_gradient_loss | -1.06e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.72e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 160 |\n",
"| time_elapsed | 1052 |\n",
"| total_timesteps | 327680 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.86e+20 |\n",
"| n_updates | 1590 |\n",
"| policy_gradient_loss | -3.42e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.59e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 161 |\n",
"| time_elapsed | 1058 |\n",
"| total_timesteps | 329728 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.92e+20 |\n",
"| n_updates | 1600 |\n",
"| policy_gradient_loss | 4.93e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.36e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 162 |\n",
"| time_elapsed | 1065 |\n",
"| total_timesteps | 331776 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.62e+20 |\n",
"| n_updates | 1610 |\n",
"| policy_gradient_loss | -2.09e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.25e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.6e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 163 |\n",
"| time_elapsed | 1072 |\n",
"| total_timesteps | 333824 |\n",
"| train/ | |\n",
"| approx_kl | 1.1641532e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.58e+20 |\n",
"| n_updates | 1620 |\n",
"| policy_gradient_loss | -5.06e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.1e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 164 |\n",
"| time_elapsed | 1078 |\n",
"| total_timesteps | 335872 |\n",
"| train/ | |\n",
"| approx_kl | -8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.62e+20 |\n",
"| n_updates | 1630 |\n",
"| policy_gradient_loss | 4.85e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.93e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 165 |\n",
"| time_elapsed | 1084 |\n",
"| total_timesteps | 337920 |\n",
"| train/ | |\n",
"| approx_kl | -1.7462298e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.69e+20 |\n",
"| n_updates | 1640 |\n",
"| policy_gradient_loss | -3.42e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.06e+20 |\n",
"--------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 166 |\n",
"| time_elapsed | 1091 |\n",
"| total_timesteps | 339968 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.86e+20 |\n",
"| n_updates | 1650 |\n",
"| policy_gradient_loss | -1.39e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.25e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 167 |\n",
"| time_elapsed | 1097 |\n",
"| total_timesteps | 342016 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.36e+20 |\n",
"| n_updates | 1660 |\n",
"| policy_gradient_loss | 2.51e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.95e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 168 |\n",
"| time_elapsed | 1103 |\n",
"| total_timesteps | 344064 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.84e+20 |\n",
"| n_updates | 1670 |\n",
"| policy_gradient_loss | 1.31e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.74e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 169 |\n",
"| time_elapsed | 1110 |\n",
"| total_timesteps | 346112 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.85e+20 |\n",
"| n_updates | 1680 |\n",
"| policy_gradient_loss | 2.5e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.09e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 170 |\n",
"| time_elapsed | 1116 |\n",
"| total_timesteps | 348160 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.58e+20 |\n",
"| n_updates | 1690 |\n",
"| policy_gradient_loss | -1.57e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.12e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 171 |\n",
"| time_elapsed | 1123 |\n",
"| total_timesteps | 350208 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.88e+20 |\n",
"| n_updates | 1700 |\n",
"| policy_gradient_loss | -2.62e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.43e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 172 |\n",
"| time_elapsed | 1129 |\n",
"| total_timesteps | 352256 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.39e+20 |\n",
"| n_updates | 1710 |\n",
"| policy_gradient_loss | -5.16e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.11e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 173 |\n",
"| time_elapsed | 1136 |\n",
"| total_timesteps | 354304 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.92e+20 |\n",
"| n_updates | 1720 |\n",
"| policy_gradient_loss | 1.08e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.98e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 174 |\n",
"| time_elapsed | 1143 |\n",
"| total_timesteps | 356352 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.47e+20 |\n",
"| n_updates | 1730 |\n",
"| policy_gradient_loss | 3.02e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.93e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 175 |\n",
"| time_elapsed | 1149 |\n",
"| total_timesteps | 358400 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.88e+20 |\n",
"| n_updates | 1740 |\n",
"| policy_gradient_loss | 4.55e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.44e+20 |\n",
"--------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 176 |\n",
"| time_elapsed | 1156 |\n",
"| total_timesteps | 360448 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.04e+20 |\n",
"| n_updates | 1750 |\n",
"| policy_gradient_loss | -1.49e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.06e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 177 |\n",
"| time_elapsed | 1163 |\n",
"| total_timesteps | 362496 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.63e+20 |\n",
"| n_updates | 1760 |\n",
"| policy_gradient_loss | 7.19e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.68e+20 |\n",
"---------------------------------------\n",
"--------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 178 |\n",
"| time_elapsed | 1170 |\n",
"| total_timesteps | 364544 |\n",
"| train/ | |\n",
"| approx_kl | -1.4551915e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.73e+20 |\n",
"| n_updates | 1770 |\n",
"| policy_gradient_loss | -4.8e-10 |\n",
"| std | 1 |\n",
"| value_loss | 8.09e+20 |\n",
"--------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 179 |\n",
"| time_elapsed | 1176 |\n",
"| total_timesteps | 366592 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.99e+20 |\n",
"| n_updates | 1780 |\n",
"| policy_gradient_loss | -5.09e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.05e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 180 |\n",
"| time_elapsed | 1183 |\n",
"| total_timesteps | 368640 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.6e+20 |\n",
"| n_updates | 1790 |\n",
"| policy_gradient_loss | -4.17e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.91e+20 |\n",
"------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 181 |\n",
"| time_elapsed | 1190 |\n",
"| total_timesteps | 370688 |\n",
"| train/ | |\n",
"| approx_kl | 5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.23e+20 |\n",
"| n_updates | 1800 |\n",
"| policy_gradient_loss | 3.55e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.3e+20 |\n",
"------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 182 |\n",
"| time_elapsed | 1197 |\n",
"| total_timesteps | 372736 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.88e+20 |\n",
"| n_updates | 1810 |\n",
"| policy_gradient_loss | 3.87e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.55e+20 |\n",
"--------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 183 |\n",
"| time_elapsed | 1203 |\n",
"| total_timesteps | 374784 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.95e+20 |\n",
"| n_updates | 1820 |\n",
"| policy_gradient_loss | -5.22e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.24e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 184 |\n",
"| time_elapsed | 1210 |\n",
"| total_timesteps | 376832 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.49e+20 |\n",
"| n_updates | 1830 |\n",
"| policy_gradient_loss | 3.16e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.13e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 185 |\n",
"| time_elapsed | 1217 |\n",
"| total_timesteps | 378880 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.05e+20 |\n",
"| n_updates | 1840 |\n",
"| policy_gradient_loss | 8.54e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.17e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 186 |\n",
"| time_elapsed | 1223 |\n",
"| total_timesteps | 380928 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.91e+20 |\n",
"| n_updates | 1850 |\n",
"| policy_gradient_loss | 4.47e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.75e+20 |\n",
"--------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.66e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 187 |\n",
"| time_elapsed | 1230 |\n",
"| total_timesteps | 382976 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.65e+20 |\n",
"| n_updates | 1860 |\n",
"| policy_gradient_loss | 1.96e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.6e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 311 |\n",
"| iterations | 188 |\n",
"| time_elapsed | 1237 |\n",
"| total_timesteps | 385024 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.39e+20 |\n",
"| n_updates | 1870 |\n",
"| policy_gradient_loss | -4.21e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.77e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 189 |\n",
"| time_elapsed | 1244 |\n",
"| total_timesteps | 387072 |\n",
"| train/ | |\n",
"| approx_kl | 1.1641532e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.16e+20 |\n",
"| n_updates | 1880 |\n",
"| policy_gradient_loss | -2.6e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.65e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 190 |\n",
"| time_elapsed | 1251 |\n",
"| total_timesteps | 389120 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.93e+20 |\n",
"| n_updates | 1890 |\n",
"| policy_gradient_loss | 1.39e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.18e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.65e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 191 |\n",
"| time_elapsed | 1258 |\n",
"| total_timesteps | 391168 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.31e+20 |\n",
"| n_updates | 1900 |\n",
"| policy_gradient_loss | -1.09e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.92e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.64e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 192 |\n",
"| time_elapsed | 1265 |\n",
"| total_timesteps | 393216 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.42e+20 |\n",
"| n_updates | 1910 |\n",
"| policy_gradient_loss | 3.49e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.98e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 193 |\n",
"| time_elapsed | 1273 |\n",
"| total_timesteps | 395264 |\n",
"| train/ | |\n",
"| approx_kl | -8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.98e+20 |\n",
"| n_updates | 1920 |\n",
"| policy_gradient_loss | -9.79e-10 |\n",
"| std | 1 |\n",
"| value_loss | 6.83e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.63e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 194 |\n",
"| time_elapsed | 1280 |\n",
"| total_timesteps | 397312 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.5e+20 |\n",
"| n_updates | 1930 |\n",
"| policy_gradient_loss | 1.64e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.09e+20 |\n",
"--------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 195 |\n",
"| time_elapsed | 1286 |\n",
"| total_timesteps | 399360 |\n",
"| train/ | |\n",
"| approx_kl | -8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.15e+20 |\n",
"| n_updates | 1940 |\n",
"| policy_gradient_loss | 1.91e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.95e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 196 |\n",
"| time_elapsed | 1293 |\n",
"| total_timesteps | 401408 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.39e+20 |\n",
"| n_updates | 1950 |\n",
"| policy_gradient_loss | -3.75e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.44e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 197 |\n",
"| time_elapsed | 1300 |\n",
"| total_timesteps | 403456 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
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"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.92e+20 |\n",
"| n_updates | 1960 |\n",
"| policy_gradient_loss | 2.71e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.42e+20 |\n",
"--------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 198 |\n",
"| time_elapsed | 1307 |\n",
"| total_timesteps | 405504 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -2.38e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.41e+20 |\n",
"| n_updates | 1970 |\n",
"| policy_gradient_loss | 2.62e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.96e+20 |\n",
"------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 199 |\n",
"| time_elapsed | 1314 |\n",
"| total_timesteps | 407552 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.46e+20 |\n",
"| n_updates | 1980 |\n",
"| policy_gradient_loss | 6.41e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.64e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.62e+11 |\n",
"| time/ | |\n",
"| fps | 310 |\n",
"| iterations | 200 |\n",
"| time_elapsed | 1321 |\n",
"| total_timesteps | 409600 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.18e+20 |\n",
"| n_updates | 1990 |\n",
"| policy_gradient_loss | -2.67e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.2e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.6e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 201 |\n",
"| time_elapsed | 1328 |\n",
"| total_timesteps | 411648 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.13e+20 |\n",
"| n_updates | 2000 |\n",
"| policy_gradient_loss | 7.92e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.34e+20 |\n",
"--------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 202 |\n",
"| time_elapsed | 1335 |\n",
"| total_timesteps | 413696 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.53e+20 |\n",
"| n_updates | 2010 |\n",
"| policy_gradient_loss | -3.51e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.15e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 203 |\n",
"| time_elapsed | 1341 |\n",
"| total_timesteps | 415744 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.48e+20 |\n",
"| n_updates | 2020 |\n",
"| policy_gradient_loss | 1.69e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.11e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.61e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 204 |\n",
"| time_elapsed | 1348 |\n",
"| total_timesteps | 417792 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.07e+20 |\n",
"| n_updates | 2030 |\n",
"| policy_gradient_loss | -4.74e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.08e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.6e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 205 |\n",
"| time_elapsed | 1355 |\n",
"| total_timesteps | 419840 |\n",
"| train/ | |\n",
"| approx_kl | 1.1641532e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.17e+20 |\n",
"| n_updates | 2040 |\n",
"| policy_gradient_loss | -3.94e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.87e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 206 |\n",
"| time_elapsed | 1362 |\n",
"| total_timesteps | 421888 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.76e+20 |\n",
"| n_updates | 2050 |\n",
"| policy_gradient_loss | 3.55e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.46e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.57e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 207 |\n",
"| time_elapsed | 1369 |\n",
"| total_timesteps | 423936 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.56e+20 |\n",
"| n_updates | 2060 |\n",
"| policy_gradient_loss | -1.75e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.04e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.57e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 208 |\n",
"| time_elapsed | 1376 |\n",
"| total_timesteps | 425984 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.79e+20 |\n",
"| n_updates | 2070 |\n",
"| policy_gradient_loss | -1.17e-08 |\n",
"| std | 1 |\n",
"| value_loss | 6.1e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 209 |\n",
"| time_elapsed | 1383 |\n",
"| total_timesteps | 428032 |\n",
"| train/ | |\n",
"| approx_kl | 2.6193447e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.41e+20 |\n",
"| n_updates | 2080 |\n",
"| policy_gradient_loss | 9.74e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.75e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 210 |\n",
"| time_elapsed | 1390 |\n",
"| total_timesteps | 430080 |\n",
"| train/ | |\n",
"| approx_kl | 1.7462298e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.14e+20 |\n",
"| n_updates | 2090 |\n",
"| policy_gradient_loss | -5.02e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.2e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 211 |\n",
"| time_elapsed | 1397 |\n",
"| total_timesteps | 432128 |\n",
"| train/ | |\n",
"| approx_kl | 1.7462298e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.71e+20 |\n",
"| n_updates | 2100 |\n",
"| policy_gradient_loss | 3.52e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.23e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 212 |\n",
"| time_elapsed | 1403 |\n",
"| total_timesteps | 434176 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.44e+20 |\n",
"| n_updates | 2110 |\n",
"| policy_gradient_loss | 2.95e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.7e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.57e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 213 |\n",
"| time_elapsed | 1410 |\n",
"| total_timesteps | 436224 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.98e+20 |\n",
"| n_updates | 2120 |\n",
"| policy_gradient_loss | -4.42e-10 |\n",
"| std | 1 |\n",
"| value_loss | 6.62e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 214 |\n",
"| time_elapsed | 1417 |\n",
"| total_timesteps | 438272 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.47e+20 |\n",
"| n_updates | 2130 |\n",
"| policy_gradient_loss | -1.04e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.43e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 309 |\n",
"| iterations | 215 |\n",
"| time_elapsed | 1424 |\n",
"| total_timesteps | 440320 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.59e+20 |\n",
"| n_updates | 2140 |\n",
"| policy_gradient_loss | -6.51e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.91e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 216 |\n",
"| time_elapsed | 1431 |\n",
"| total_timesteps | 442368 |\n",
"| train/ | |\n",
"| approx_kl | -1.1641532e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.57e+20 |\n",
"| n_updates | 2150 |\n",
"| policy_gradient_loss | -2.45e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.32e+20 |\n",
"--------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 217 |\n",
"| time_elapsed | 1438 |\n",
"| total_timesteps | 444416 |\n",
"| train/ | |\n",
"| approx_kl | -8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.72e+20 |\n",
"| n_updates | 2160 |\n",
"| policy_gradient_loss | 8.11e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.65e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.56e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 218 |\n",
"| time_elapsed | 1445 |\n",
"| total_timesteps | 446464 |\n",
"| train/ | |\n",
"| approx_kl | 5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.21e+20 |\n",
"| n_updates | 2170 |\n",
"| policy_gradient_loss | -4.02e-10 |\n",
"| std | 1 |\n",
"| value_loss | 6.93e+20 |\n",
"------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.55e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 219 |\n",
"| time_elapsed | 1452 |\n",
"| total_timesteps | 448512 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 5.96e-08 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.26e+20 |\n",
"| n_updates | 2180 |\n",
"| policy_gradient_loss | 2.76e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.84e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.55e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 220 |\n",
"| time_elapsed | 1460 |\n",
"| total_timesteps | 450560 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.45e+20 |\n",
"| n_updates | 2190 |\n",
"| policy_gradient_loss | 4.91e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.09e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.56e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 221 |\n",
"| time_elapsed | 1467 |\n",
"| total_timesteps | 452608 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.4e+20 |\n",
"| n_updates | 2200 |\n",
"| policy_gradient_loss | 2.73e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.29e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.57e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 222 |\n",
"| time_elapsed | 1474 |\n",
"| total_timesteps | 454656 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.69e+20 |\n",
"| n_updates | 2210 |\n",
"| policy_gradient_loss | 3.09e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.16e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.56e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 223 |\n",
"| time_elapsed | 1481 |\n",
"| total_timesteps | 456704 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.4e+20 |\n",
"| n_updates | 2220 |\n",
"| policy_gradient_loss | -2.49e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.83e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 224 |\n",
"| time_elapsed | 1487 |\n",
"| total_timesteps | 458752 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.23e+20 |\n",
"| n_updates | 2230 |\n",
"| policy_gradient_loss | 6.27e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.98e+20 |\n",
"------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.57e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 225 |\n",
"| time_elapsed | 1494 |\n",
"| total_timesteps | 460800 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.31e+20 |\n",
"| n_updates | 2240 |\n",
"| policy_gradient_loss | 1.68e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.97e+20 |\n",
"--------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.57e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 226 |\n",
"| time_elapsed | 1501 |\n",
"| total_timesteps | 462848 |\n",
"| train/ | |\n",
"| approx_kl | 5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.34e+20 |\n",
"| n_updates | 2250 |\n",
"| policy_gradient_loss | 1.34e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.23e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.56e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 227 |\n",
"| time_elapsed | 1508 |\n",
"| total_timesteps | 464896 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.18e+20 |\n",
"| n_updates | 2260 |\n",
"| policy_gradient_loss | -1.05e-08 |\n",
"| std | 1 |\n",
"| value_loss | 7.11e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.55e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 228 |\n",
"| time_elapsed | 1514 |\n",
"| total_timesteps | 466944 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.67e+20 |\n",
"| n_updates | 2270 |\n",
"| policy_gradient_loss | 9.96e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.88e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.53e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 229 |\n",
"| time_elapsed | 1521 |\n",
"| total_timesteps | 468992 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.16e+20 |\n",
"| n_updates | 2280 |\n",
"| policy_gradient_loss | -1.16e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.4e+20 |\n",
"---------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.54e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 230 |\n",
"| time_elapsed | 1528 |\n",
"| total_timesteps | 471040 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.63e+20 |\n",
"| n_updates | 2290 |\n",
"| policy_gradient_loss | 1.45e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.63e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.53e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 231 |\n",
"| time_elapsed | 1534 |\n",
"| total_timesteps | 473088 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.48e+20 |\n",
"| n_updates | 2300 |\n",
"| policy_gradient_loss | -3.34e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.29e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.53e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 232 |\n",
"| time_elapsed | 1541 |\n",
"| total_timesteps | 475136 |\n",
"| train/ | |\n",
"| approx_kl | 8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.87e+20 |\n",
"| n_updates | 2310 |\n",
"| policy_gradient_loss | -4.51e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.1e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.53e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 233 |\n",
"| time_elapsed | 1548 |\n",
"| total_timesteps | 477184 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.61e+20 |\n",
"| n_updates | 2320 |\n",
"| policy_gradient_loss | 2.87e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.51e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.52e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 234 |\n",
"| time_elapsed | 1554 |\n",
"| total_timesteps | 479232 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.23e+20 |\n",
"| n_updates | 2330 |\n",
"| policy_gradient_loss | -5.88e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.24e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.52e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 235 |\n",
"| time_elapsed | 1562 |\n",
"| total_timesteps | 481280 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.22e+20 |\n",
"| n_updates | 2340 |\n",
"| policy_gradient_loss | -2.38e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.19e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.51e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 236 |\n",
"| time_elapsed | 1568 |\n",
"| total_timesteps | 483328 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.3e+20 |\n",
"| n_updates | 2350 |\n",
"| policy_gradient_loss | -1.01e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.09e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.51e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 237 |\n",
"| time_elapsed | 1575 |\n",
"| total_timesteps | 485376 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.9e+20 |\n",
"| n_updates | 2360 |\n",
"| policy_gradient_loss | -2.64e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.85e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.52e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 238 |\n",
"| time_elapsed | 1582 |\n",
"| total_timesteps | 487424 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.95e+20 |\n",
"| n_updates | 2370 |\n",
"| policy_gradient_loss | -3.15e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.31e+20 |\n",
"-------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.52e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 239 |\n",
"| time_elapsed | 1588 |\n",
"| total_timesteps | 489472 |\n",
"| train/ | |\n",
"| approx_kl | -8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.58e+20 |\n",
"| n_updates | 2380 |\n",
"| policy_gradient_loss | 5.26e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.31e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.53e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 240 |\n",
"| time_elapsed | 1595 |\n",
"| total_timesteps | 491520 |\n",
"| train/ | |\n",
"| approx_kl | -2.6193447e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.16e+20 |\n",
"| n_updates | 2390 |\n",
"| policy_gradient_loss | -2.83e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.82e+20 |\n",
"--------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.53e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 241 |\n",
"| time_elapsed | 1602 |\n",
"| total_timesteps | 493568 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.39e+20 |\n",
"| n_updates | 2400 |\n",
"| policy_gradient_loss | 2.51e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.5e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.53e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 242 |\n",
"| time_elapsed | 1608 |\n",
"| total_timesteps | 495616 |\n",
"| train/ | |\n",
"| approx_kl | -8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.06e+20 |\n",
"| n_updates | 2410 |\n",
"| policy_gradient_loss | -6.89e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.06e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.51e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 243 |\n",
"| time_elapsed | 1615 |\n",
"| total_timesteps | 497664 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.18e+20 |\n",
"| n_updates | 2420 |\n",
"| policy_gradient_loss | -3.41e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.76e+20 |\n",
"---------------------------------------\n",
"--------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.49e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 244 |\n",
"| time_elapsed | 1622 |\n",
"| total_timesteps | 499712 |\n",
"| train/ | |\n",
"| approx_kl | -1.1641532e-10 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.97e+20 |\n",
"| n_updates | 2430 |\n",
"| policy_gradient_loss | -7.16e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.5e+20 |\n",
"--------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.51e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 245 |\n",
"| time_elapsed | 1628 |\n",
"| total_timesteps | 501760 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.48e+20 |\n",
"| n_updates | 2440 |\n",
"| policy_gradient_loss | -2.81e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.7e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.51e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 246 |\n",
"| time_elapsed | 1635 |\n",
"| total_timesteps | 503808 |\n",
"| train/ | |\n",
"| approx_kl | 8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.45e+20 |\n",
"| n_updates | 2450 |\n",
"| policy_gradient_loss | 4.88e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.99e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.52e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 247 |\n",
"| time_elapsed | 1641 |\n",
"| total_timesteps | 505856 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4e+20 |\n",
"| n_updates | 2460 |\n",
"| policy_gradient_loss | -3.23e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.21e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.53e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 248 |\n",
"| time_elapsed | 1649 |\n",
"| total_timesteps | 507904 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.82e+20 |\n",
"| n_updates | 2470 |\n",
"| policy_gradient_loss | -6.64e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.33e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.52e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 249 |\n",
"| time_elapsed | 1655 |\n",
"| total_timesteps | 509952 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.87e+20 |\n",
"| n_updates | 2480 |\n",
"| policy_gradient_loss | -2e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.59e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.52e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 250 |\n",
"| time_elapsed | 1662 |\n",
"| total_timesteps | 512000 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.21e+20 |\n",
"| n_updates | 2490 |\n",
"| policy_gradient_loss | 1.76e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.45e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.51e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 251 |\n",
"| time_elapsed | 1669 |\n",
"| total_timesteps | 514048 |\n",
"| train/ | |\n",
"| approx_kl | -2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.16e+20 |\n",
"| n_updates | 2500 |\n",
"| policy_gradient_loss | 1.24e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.98e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.52e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 252 |\n",
"| time_elapsed | 1675 |\n",
"| total_timesteps | 516096 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.71e+20 |\n",
"| n_updates | 2510 |\n",
"| policy_gradient_loss | -3.89e-10 |\n",
"| std | 1 |\n",
"| value_loss | 6.88e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.52e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 253 |\n",
"| time_elapsed | 1682 |\n",
"| total_timesteps | 518144 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.46e+20 |\n",
"| n_updates | 2520 |\n",
"| policy_gradient_loss | 6.97e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.13e+20 |\n",
"-------------------------------------------\n",
"--------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.52e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 254 |\n",
"| time_elapsed | 1689 |\n",
"| total_timesteps | 520192 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.25e+20 |\n",
"| n_updates | 2530 |\n",
"| policy_gradient_loss | -3.5e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.1e+20 |\n",
"--------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.51e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 255 |\n",
"| time_elapsed | 1695 |\n",
"| total_timesteps | 522240 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.07e+20 |\n",
"| n_updates | 2540 |\n",
"| policy_gradient_loss | -3.22e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.55e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.52e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 256 |\n",
"| time_elapsed | 1702 |\n",
"| total_timesteps | 524288 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.85e+20 |\n",
"| n_updates | 2550 |\n",
"| policy_gradient_loss | 5.49e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.33e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.53e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 257 |\n",
"| time_elapsed | 1708 |\n",
"| total_timesteps | 526336 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -2.38e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3e+20 |\n",
"| n_updates | 2560 |\n",
"| policy_gradient_loss | 3.43e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.02e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.52e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 258 |\n",
"| time_elapsed | 1715 |\n",
"| total_timesteps | 528384 |\n",
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"| loss | 3.28e+20 |\n",
"| n_updates | 2570 |\n",
"| policy_gradient_loss | -1.44e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.71e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.53e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 259 |\n",
"| time_elapsed | 1722 |\n",
"| total_timesteps | 530432 |\n",
"| train/ | |\n",
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"| n_updates | 2580 |\n",
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"| std | 1 |\n",
"| value_loss | 7.16e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.53e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 260 |\n",
"| time_elapsed | 1728 |\n",
"| total_timesteps | 532480 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
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"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
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"| n_updates | 2590 |\n",
"| policy_gradient_loss | 6.02e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.2e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.55e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 261 |\n",
"| time_elapsed | 1735 |\n",
"| total_timesteps | 534528 |\n",
"| train/ | |\n",
"| approx_kl | -8.731149e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
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"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 5e+20 |\n",
"| n_updates | 2600 |\n",
"| policy_gradient_loss | 4.48e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.02e+20 |\n",
"-------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.55e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 262 |\n",
"| time_elapsed | 1741 |\n",
"| total_timesteps | 536576 |\n",
"| train/ | |\n",
"| approx_kl | 5.820766e-11 |\n",
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"| learning_rate | 0.0003 |\n",
"| loss | 4.15e+20 |\n",
"| n_updates | 2610 |\n",
"| policy_gradient_loss | -5.84e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.04e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.55e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 263 |\n",
"| time_elapsed | 1748 |\n",
"| total_timesteps | 538624 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.89e+20 |\n",
"| n_updates | 2620 |\n",
"| policy_gradient_loss | -3.63e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.62e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.57e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 264 |\n",
"| time_elapsed | 1754 |\n",
"| total_timesteps | 540672 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.73e+20 |\n",
"| n_updates | 2630 |\n",
"| policy_gradient_loss | -2.57e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.07e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 265 |\n",
"| time_elapsed | 1761 |\n",
"| total_timesteps | 542720 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
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"| policy_gradient_loss | -5.97e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.42e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 266 |\n",
"| time_elapsed | 1768 |\n",
"| total_timesteps | 544768 |\n",
"| train/ | |\n",
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"| policy_gradient_loss | -1.79e-09 |\n",
"| std | 1 |\n",
"| value_loss | 8.32e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 267 |\n",
"| time_elapsed | 1774 |\n",
"| total_timesteps | 546816 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.5e+20 |\n",
"| n_updates | 2660 |\n",
"| policy_gradient_loss | 6.34e-09 |\n",
"| std | 1 |\n",
"| value_loss | 6.9e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 268 |\n",
"| time_elapsed | 1781 |\n",
"| total_timesteps | 548864 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -2.38e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.39e+20 |\n",
"| n_updates | 2670 |\n",
"| policy_gradient_loss | 2.16e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.59e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 269 |\n",
"| time_elapsed | 1788 |\n",
"| total_timesteps | 550912 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.3e+20 |\n",
"| n_updates | 2680 |\n",
"| policy_gradient_loss | 6.27e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.17e+20 |\n",
"------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.57e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 270 |\n",
"| time_elapsed | 1795 |\n",
"| total_timesteps | 552960 |\n",
"| train/ | |\n",
"| approx_kl | 5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.02e+20 |\n",
"| n_updates | 2690 |\n",
"| policy_gradient_loss | -1.96e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.08e+20 |\n",
"------------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 271 |\n",
"| time_elapsed | 1801 |\n",
"| total_timesteps | 555008 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.98e+20 |\n",
"| n_updates | 2700 |\n",
"| policy_gradient_loss | 4.61e-10 |\n",
"| std | 1 |\n",
"| value_loss | 7.76e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 272 |\n",
"| time_elapsed | 1808 |\n",
"| total_timesteps | 557056 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 2.9e+20 |\n",
"| n_updates | 2710 |\n",
"| policy_gradient_loss | -6.43e-10 |\n",
"| std | 1 |\n",
"| value_loss | 6.67e+20 |\n",
"---------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 273 |\n",
"| time_elapsed | 1815 |\n",
"| total_timesteps | 559104 |\n",
"| train/ | |\n",
"| approx_kl | 2.910383e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | 0 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.34e+20 |\n",
"| n_updates | 2720 |\n",
"| policy_gradient_loss | 7.83e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.53e+20 |\n",
"------------------------------------------\n",
"------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 274 |\n",
"| time_elapsed | 1821 |\n",
"| total_timesteps | 561152 |\n",
"| train/ | |\n",
"| approx_kl | 5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -2.38e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.21e+20 |\n",
"| n_updates | 2730 |\n",
"| policy_gradient_loss | -2.04e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.01e+20 |\n",
"------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.58e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 275 |\n",
"| time_elapsed | 1828 |\n",
"| total_timesteps | 563200 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.16e+20 |\n",
"| n_updates | 2740 |\n",
"| policy_gradient_loss | -8.44e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.38e+20 |\n",
"---------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 308 |\n",
"| iterations | 276 |\n",
"| time_elapsed | 1835 |\n",
"| total_timesteps | 565248 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -2.38e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.1e+20 |\n",
"| n_updates | 2750 |\n",
"| policy_gradient_loss | 2.26e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.69e+20 |\n",
"---------------------------------------\n",
"-------------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 277 |\n",
"| time_elapsed | 1841 |\n",
"| total_timesteps | 567296 |\n",
"| train/ | |\n",
"| approx_kl | -5.820766e-11 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -1.19e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 4.02e+20 |\n",
"| n_updates | 2760 |\n",
"| policy_gradient_loss | -1.79e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.44e+20 |\n",
"-------------------------------------------\n",
"---------------------------------------\n",
"| rollout/ | |\n",
"| ep_len_mean | 601 |\n",
"| ep_rew_mean | 8.59e+11 |\n",
"| time/ | |\n",
"| fps | 307 |\n",
"| iterations | 278 |\n",
"| time_elapsed | 1848 |\n",
"| total_timesteps | 569344 |\n",
"| train/ | |\n",
"| approx_kl | 0.0 |\n",
"| clip_fraction | 0 |\n",
"| clip_range | 0.2 |\n",
"| entropy_loss | -1.42 |\n",
"| explained_variance | -2.38e-07 |\n",
"| learning_rate | 0.0003 |\n",
"| loss | 3.88e+20 |\n",
"| n_updates | 2770 |\n",
"| policy_gradient_loss | 3.25e-09 |\n",
"| std | 1 |\n",
"| value_loss | 7.91e+20 |\n",
"---------------------------------------\n"
2024-12-13 23:31:10 +00:00
]
},
{
2024-12-14 01:40:15 +00:00
"ename": "KeyboardInterrupt",
"evalue": "",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[25], line 4\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mstable_baselines3\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m PPO\n\u001b[1;32m 3\u001b[0m model \u001b[38;5;241m=\u001b[39m PPO(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMultiInputPolicy\u001b[39m\u001b[38;5;124m\"\u001b[39m, wrapped_env, verbose\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m----> 4\u001b[0m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlearn\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtotal_timesteps\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1_000_000\u001b[39;49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/Documents/Code/solarcarsim/.venv/lib/python3.12/site-packages/stable_baselines3/ppo/ppo.py:311\u001b[0m, in \u001b[0;36mPPO.learn\u001b[0;34m(self, total_timesteps, callback, log_interval, tb_log_name, reset_num_timesteps, progress_bar)\u001b[0m\n\u001b[1;32m 302\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mlearn\u001b[39m(\n\u001b[1;32m 303\u001b[0m \u001b[38;5;28mself\u001b[39m: SelfPPO,\n\u001b[1;32m 304\u001b[0m total_timesteps: \u001b[38;5;28mint\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 309\u001b[0m progress_bar: \u001b[38;5;28mbool\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m 310\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m SelfPPO:\n\u001b[0;32m--> 311\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlearn\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 312\u001b[0m \u001b[43m \u001b[49m\u001b[43mtotal_timesteps\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtotal_timesteps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 313\u001b[0m \u001b[43m \u001b[49m\u001b[43mcallback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcallback\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 314\u001b[0m \u001b[43m \u001b[49m\u001b[43mlog_interval\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlog_interval\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 315\u001b[0m \u001b[43m \u001b[49m\u001b[43mtb_log_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtb_log_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 316\u001b[0m \u001b[43m \u001b[49m\u001b[43mreset_num_timesteps\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mreset_num_timesteps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 317\u001b[0m \u001b[43m \u001b[49m\u001b[43mprogress_bar\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprogress_bar\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 318\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/Documents/Code/solarcarsim/.venv/lib/python3.12/site-packages/stable_baselines3/common/on_policy_algorithm.py:336\u001b[0m, in \u001b[0;36mOnPolicyAlgorithm.learn\u001b[0;34m(self, total_timesteps, callback, log_interval, tb_log_name, reset_num_timesteps, progress_bar)\u001b[0m\n\u001b[1;32m 333\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mep_info_buffer \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 334\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dump_logs(iteration)\n\u001b[0;32m--> 336\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtrain\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 338\u001b[0m callback\u001b[38;5;241m.\u001b[39mon_training_end()\n\u001b[1;32m 340\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\n",
"File \u001b[0;32m~/Documents/Code/solarcarsim/.venv/lib/python3.12/site-packages/stable_baselines3/ppo/ppo.py:213\u001b[0m, in \u001b[0;36mPPO.train\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 209\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maction_space, spaces\u001b[38;5;241m.\u001b[39mDiscrete):\n\u001b[1;32m 210\u001b[0m \u001b[38;5;66;03m# Convert discrete action from float to long\u001b[39;00m\n\u001b[1;32m 211\u001b[0m actions \u001b[38;5;241m=\u001b[39m rollout_data\u001b[38;5;241m.\u001b[39mactions\u001b[38;5;241m.\u001b[39mlong()\u001b[38;5;241m.\u001b[39mflatten()\n\u001b[0;32m--> 213\u001b[0m values, log_prob, entropy \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpolicy\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mevaluate_actions\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrollout_data\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mobservations\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mactions\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 214\u001b[0m values \u001b[38;5;241m=\u001b[39m values\u001b[38;5;241m.\u001b[39mflatten()\n\u001b[1;32m 215\u001b[0m \u001b[38;5;66;03m# Normalize advantage\u001b[39;00m\n",
"File \u001b[0;32m~/Documents/Code/solarcarsim/.venv/lib/python3.12/site-packages/stable_baselines3/common/policies.py:739\u001b[0m, in \u001b[0;36mActorCriticPolicy.evaluate_actions\u001b[0;34m(self, obs, actions)\u001b[0m\n\u001b[1;32m 737\u001b[0m distribution \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_action_dist_from_latent(latent_pi)\n\u001b[1;32m 738\u001b[0m log_prob \u001b[38;5;241m=\u001b[39m distribution\u001b[38;5;241m.\u001b[39mlog_prob(actions)\n\u001b[0;32m--> 739\u001b[0m values \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalue_net\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlatent_vf\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 740\u001b[0m entropy \u001b[38;5;241m=\u001b[39m distribution\u001b[38;5;241m.\u001b[39mentropy()\n\u001b[1;32m 741\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m values, log_prob, entropy\n",
"File \u001b[0;32m~/Documents/Code/solarcarsim/.venv/lib/python3.12/site-packages/torch/nn/modules/module.py:1736\u001b[0m, in \u001b[0;36mModule._wrapped_call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1734\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_compiled_call_impl(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs) \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[1;32m 1735\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 1736\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[0;32m~/Documents/Code/solarcarsim/.venv/lib/python3.12/site-packages/torch/nn/modules/module.py:1747\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m 1742\u001b[0m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1743\u001b[0m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1744\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_forward_pre_hooks\n\u001b[1;32m 1745\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1746\u001b[0m \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1747\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mforward_call\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1749\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1750\u001b[0m called_always_called_hooks \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mset\u001b[39m()\n",
"File \u001b[0;32m~/Documents/Code/solarcarsim/.venv/lib/python3.12/site-packages/torch/nn/modules/linear.py:125\u001b[0m, in \u001b[0;36mLinear.forward\u001b[0;34m(self, input)\u001b[0m\n\u001b[1;32m 124\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mforward\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28minput\u001b[39m: Tensor) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tensor:\n\u001b[0;32m--> 125\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mF\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlinear\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mweight\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbias\u001b[49m\u001b[43m)\u001b[49m\n",
"\u001b[0;31mKeyboardInterrupt\u001b[0m: "
2024-12-13 23:31:10 +00:00
]
}
],
"source": [
"# import a model and try it out!\n",
"from stable_baselines3 import PPO\n",
"model = PPO(\"MultiInputPolicy\", wrapped_env, verbose=1)\n",
"model.learn(total_timesteps=1_000_000)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Array([[[-4.9999666, -5.031969 , -5.063982 , ..., -6.714849 ,\n",
" -6.71299 , -6.7111654],\n",
" [-4.9998884, -5.031891 , -5.0639033, ..., -6.705859 ,\n",
" -6.7038655, -6.701909 ],\n",
" [-4.9997377, -5.03174 , -5.0637527, ..., -6.6968226,\n",
" -6.694696 , -6.692607 ],\n",
" ...,\n",
" [-4.8104963, -4.840162 , -4.869858 , ..., -6.505874 ,\n",
" -6.499703 , -6.4934487],\n",
" [-4.8117733, -4.8413825, -4.871023 , ..., -6.511339 ,\n",
" -6.5052385, -6.499054 ],\n",
" [-4.812991 , -4.8425455, -4.8721304, ..., -6.5165534,\n",
" -6.510523 , -6.504408 ]]], dtype=float32)"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pos = jnp.array([0])\n",
"time = jnp.array([0])\n",
"x = jnp.stack([pos,time], axis=1)\n",
"vlookup(x)"
]
},
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{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
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