From af5f1bd37a6847ea65db0f6283b89984ad950b47 Mon Sep 17 00:00:00 2001
From: Majdi Karim <karim.majdi@etu.ec-lyon.fr>
Date: Tue, 19 Mar 2024 23:43:51 +0000
Subject: [PATCH] Upload New File
---
RL_cartepole__3_.ipynb | 12825 +++++++++++++++++++++++++++++++++++++++
1 file changed, 12825 insertions(+)
create mode 100644 RL_cartepole__3_.ipynb
diff --git a/RL_cartepole__3_.ipynb b/RL_cartepole__3_.ipynb
new file mode 100644
index 0000000..53618f6
--- /dev/null
+++ b/RL_cartepole__3_.ipynb
@@ -0,0 +1,12825 @@
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+ "source": [
+ "!pip install gymnasium\n",
+ "!pip install pyglet==2.0.10\n",
+ "!pip install pygame==2.5.2\n",
+ "!pip install PyQt5\n",
+ "!pip install huggingface-sb3==2.3.1\n",
+ "!pip install wandb tensorboard\n",
+ "!apt-get update && apt-get install ffmpeg freeglut3-dev xvfb # For visualization\n",
+ "!pip install \"stable-baselines3[extra]>=2.0.0a4\"\n",
+ "!pip install panda-gym\n",
+ "\n"
+ ],
+ "metadata": {
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+ },
+ "id": "vg3Sp873bVEU",
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+ },
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+ {
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+ "name": "stdout",
+ "text": [
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+ "Installing collected packages: huggingface-sb3\n",
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+ "Requirement already satisfied: tensorboard-data-server<0.8.0,>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard) (0.7.2)\n",
+ "Requirement already satisfied: werkzeug>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from tensorboard) (3.0.1)\n",
+ "Collecting gitdb<5,>=4.0.1 (from GitPython!=3.1.29,>=1.0.0->wandb)\n",
+ " Downloading gitdb-4.0.11-py3-none-any.whl (62 kB)\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m62.7/62.7 kB\u001b[0m \u001b[31m10.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[?25hRequirement already satisfied: cachetools<6.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard) (5.3.3)\n",
+ "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard) (0.3.0)\n",
+ "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard) (4.9)\n",
+ "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from google-auth-oauthlib<2,>=0.5->tensorboard) (1.4.0)\n",
+ "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.0.0->wandb) (3.3.2)\n",
+ "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.0.0->wandb) (3.6)\n",
+ "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.0.0->wandb) (2.0.7)\n",
+ "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2.0.0->wandb) (2024.2.2)\n",
+ "Requirement already satisfied: MarkupSafe>=2.1.1 in /usr/local/lib/python3.10/dist-packages (from werkzeug>=1.0.1->tensorboard) (2.1.5)\n",
+ "Collecting smmap<6,>=3.0.1 (from gitdb<5,>=4.0.1->GitPython!=3.1.29,>=1.0.0->wandb)\n",
+ " Downloading smmap-5.0.1-py3-none-any.whl (24 kB)\n",
+ "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard) (0.5.1)\n",
+ "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<2,>=0.5->tensorboard) (3.2.2)\n",
+ "Installing collected packages: smmap, setproctitle, sentry-sdk, docker-pycreds, gitdb, GitPython, wandb\n",
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+ "Get:1 https://cloud.r-project.org/bin/linux/ubuntu jammy-cran40/ InRelease [3,626 B]\n",
+ "Hit:2 http://archive.ubuntu.com/ubuntu jammy InRelease\n",
+ "Get:3 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64 InRelease [1,581 B]\n",
+ "Get:4 http://archive.ubuntu.com/ubuntu jammy-updates InRelease [119 kB]\n",
+ "Get:5 http://security.ubuntu.com/ubuntu jammy-security InRelease [110 kB]\n",
+ "Get:6 http://archive.ubuntu.com/ubuntu jammy-backports InRelease [109 kB]\n",
+ "Hit:7 https://ppa.launchpadcontent.net/c2d4u.team/c2d4u4.0+/ubuntu jammy InRelease\n",
+ "Hit:8 https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu jammy InRelease\n",
+ "Get:9 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64 Packages [737 kB]\n",
+ "Hit:10 https://ppa.launchpadcontent.net/graphics-drivers/ppa/ubuntu jammy InRelease\n",
+ "Get:11 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 Packages [1,881 kB]\n",
+ "Hit:12 https://ppa.launchpadcontent.net/ubuntugis/ppa/ubuntu jammy InRelease\n",
+ "Get:13 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 Packages [1,353 kB]\n",
+ "Get:14 http://archive.ubuntu.com/ubuntu jammy-updates/restricted amd64 Packages [2,050 kB]\n",
+ "Get:15 http://archive.ubuntu.com/ubuntu jammy-backports/universe amd64 Packages [33.3 kB]\n",
+ "Get:16 http://security.ubuntu.com/ubuntu jammy-security/main amd64 Packages [1,569 kB]\n",
+ "Get:17 http://security.ubuntu.com/ubuntu jammy-security/universe amd64 Packages [1,079 kB]\n",
+ "Get:18 http://security.ubuntu.com/ubuntu jammy-security/restricted amd64 Packages [1,961 kB]\n",
+ "Fetched 11.0 MB in 2s (4,901 kB/s)\n",
+ "Reading package lists... Done\n",
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+ "Building dependency tree... Done\n",
+ "Reading state information... Done\n",
+ "ffmpeg is already the newest version (7:4.4.2-0ubuntu0.22.04.1).\n",
+ "The following additional packages will be installed:\n",
+ " freeglut3 libegl-dev libfontenc1 libgl-dev libgl1-mesa-dev libgles-dev libgles1 libglu1-mesa\n",
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+ " libsm-dev libxfont2 libxkbfile1 libxt-dev x11-xkb-utils xfonts-base xfonts-encodings xfonts-utils\n",
+ " xserver-common xvfb\n",
+ "0 upgraded, 25 newly installed, 0 to remove and 39 not upgraded.\n",
+ "Need to get 9,075 kB of archives.\n",
+ "After this operation, 18.7 MB of additional disk space will be used.\n",
+ "Get:1 http://archive.ubuntu.com/ubuntu jammy/universe amd64 freeglut3 amd64 2.8.1-6 [74.0 kB]\n",
+ "Get:2 http://archive.ubuntu.com/ubuntu jammy/main amd64 libglx-dev amd64 1.4.0-1 [14.1 kB]\n",
+ "Get:3 http://archive.ubuntu.com/ubuntu jammy/main amd64 libgl-dev amd64 1.4.0-1 [101 kB]\n",
+ "Get:4 http://archive.ubuntu.com/ubuntu jammy/main amd64 libglvnd-core-dev amd64 1.4.0-1 [12.7 kB]\n",
+ "Get:5 http://archive.ubuntu.com/ubuntu jammy/main amd64 libegl-dev amd64 1.4.0-1 [18.0 kB]\n",
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+ "Get:7 http://archive.ubuntu.com/ubuntu jammy/main amd64 libgles-dev amd64 1.4.0-1 [49.4 kB]\n",
+ "Get:8 http://archive.ubuntu.com/ubuntu jammy/main amd64 libopengl-dev amd64 1.4.0-1 [3,400 B]\n",
+ "Get:9 http://archive.ubuntu.com/ubuntu jammy/main amd64 libglvnd-dev amd64 1.4.0-1 [3,162 B]\n",
+ "Get:10 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libgl1-mesa-dev amd64 23.2.1-1ubuntu3.1~22.04.2 [6,842 B]\n",
+ "Get:11 http://archive.ubuntu.com/ubuntu jammy/main amd64 libglu1-mesa amd64 9.0.2-1 [145 kB]\n",
+ "Get:12 http://archive.ubuntu.com/ubuntu jammy/main amd64 libglu1-mesa-dev amd64 9.0.2-1 [231 kB]\n",
+ "Get:13 http://archive.ubuntu.com/ubuntu jammy/main amd64 libice-dev amd64 2:1.0.10-1build2 [51.4 kB]\n",
+ "Get:14 http://archive.ubuntu.com/ubuntu jammy/main amd64 libsm-dev amd64 2:1.2.3-1build2 [18.1 kB]\n",
+ "Get:15 http://archive.ubuntu.com/ubuntu jammy/main amd64 libxt-dev amd64 1:1.2.1-1 [396 kB]\n",
+ "Get:16 http://archive.ubuntu.com/ubuntu jammy/universe amd64 freeglut3-dev amd64 2.8.1-6 [126 kB]\n",
+ "Get:17 http://archive.ubuntu.com/ubuntu jammy/main amd64 libfontenc1 amd64 1:1.1.4-1build3 [14.7 kB]\n",
+ "Get:18 http://archive.ubuntu.com/ubuntu jammy/main amd64 libxfont2 amd64 1:2.0.5-1build1 [94.5 kB]\n",
+ "Get:19 http://archive.ubuntu.com/ubuntu jammy/main amd64 libxkbfile1 amd64 1:1.1.0-1build3 [71.8 kB]\n",
+ "Get:20 http://archive.ubuntu.com/ubuntu jammy/main amd64 x11-xkb-utils amd64 7.7+5build4 [172 kB]\n",
+ "Get:21 http://archive.ubuntu.com/ubuntu jammy/main amd64 xfonts-encodings all 1:1.0.5-0ubuntu2 [578 kB]\n",
+ "Get:22 http://archive.ubuntu.com/ubuntu jammy/main amd64 xfonts-utils amd64 1:7.7+6build2 [94.6 kB]\n",
+ "Get:23 http://archive.ubuntu.com/ubuntu jammy/main amd64 xfonts-base all 1:1.0.5 [5,896 kB]\n",
+ "Get:24 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 xserver-common all 2:21.1.4-2ubuntu1.7~22.04.8 [28.6 kB]\n",
+ "Get:25 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 xvfb amd64 2:21.1.4-2ubuntu1.7~22.04.8 [863 kB]\n",
+ "Fetched 9,075 kB in 0s (21.4 MB/s)\n",
+ "Selecting previously unselected package freeglut3:amd64.\n",
+ "(Reading database ... 121752 files and directories currently installed.)\n",
+ "Preparing to unpack .../00-freeglut3_2.8.1-6_amd64.deb ...\n",
+ "Unpacking freeglut3:amd64 (2.8.1-6) ...\n",
+ "Selecting previously unselected package libglx-dev:amd64.\n",
+ "Preparing to unpack .../01-libglx-dev_1.4.0-1_amd64.deb ...\n",
+ "Unpacking libglx-dev:amd64 (1.4.0-1) ...\n",
+ "Selecting previously unselected package libgl-dev:amd64.\n",
+ "Preparing to unpack .../02-libgl-dev_1.4.0-1_amd64.deb ...\n",
+ "Unpacking libgl-dev:amd64 (1.4.0-1) ...\n",
+ "Selecting previously unselected package libglvnd-core-dev:amd64.\n",
+ "Preparing to unpack .../03-libglvnd-core-dev_1.4.0-1_amd64.deb ...\n",
+ "Unpacking libglvnd-core-dev:amd64 (1.4.0-1) ...\n",
+ "Selecting previously unselected package libegl-dev:amd64.\n",
+ "Preparing to unpack .../04-libegl-dev_1.4.0-1_amd64.deb ...\n",
+ "Unpacking libegl-dev:amd64 (1.4.0-1) ...\n",
+ "Selecting previously unselected package libgles1:amd64.\n",
+ "Preparing to unpack .../05-libgles1_1.4.0-1_amd64.deb ...\n",
+ "Unpacking libgles1:amd64 (1.4.0-1) ...\n",
+ "Selecting previously unselected package libgles-dev:amd64.\n",
+ "Preparing to unpack .../06-libgles-dev_1.4.0-1_amd64.deb ...\n",
+ "Unpacking libgles-dev:amd64 (1.4.0-1) ...\n",
+ "Selecting previously unselected package libopengl-dev:amd64.\n",
+ "Preparing to unpack .../07-libopengl-dev_1.4.0-1_amd64.deb ...\n",
+ "Unpacking libopengl-dev:amd64 (1.4.0-1) ...\n",
+ "Selecting previously unselected package libglvnd-dev:amd64.\n",
+ "Preparing to unpack .../08-libglvnd-dev_1.4.0-1_amd64.deb ...\n",
+ "Unpacking libglvnd-dev:amd64 (1.4.0-1) ...\n",
+ "Selecting previously unselected package libgl1-mesa-dev:amd64.\n",
+ "Preparing to unpack .../09-libgl1-mesa-dev_23.2.1-1ubuntu3.1~22.04.2_amd64.deb ...\n",
+ "Unpacking libgl1-mesa-dev:amd64 (23.2.1-1ubuntu3.1~22.04.2) ...\n",
+ "Selecting previously unselected package libglu1-mesa:amd64.\n",
+ "Preparing to unpack .../10-libglu1-mesa_9.0.2-1_amd64.deb ...\n",
+ "Unpacking libglu1-mesa:amd64 (9.0.2-1) ...\n",
+ "Selecting previously unselected package libglu1-mesa-dev:amd64.\n",
+ "Preparing to unpack .../11-libglu1-mesa-dev_9.0.2-1_amd64.deb ...\n",
+ "Unpacking libglu1-mesa-dev:amd64 (9.0.2-1) ...\n",
+ "Selecting previously unselected package libice-dev:amd64.\n",
+ "Preparing to unpack .../12-libice-dev_2%3a1.0.10-1build2_amd64.deb ...\n",
+ "Unpacking libice-dev:amd64 (2:1.0.10-1build2) ...\n",
+ "Selecting previously unselected package libsm-dev:amd64.\n",
+ "Preparing to unpack .../13-libsm-dev_2%3a1.2.3-1build2_amd64.deb ...\n",
+ "Unpacking libsm-dev:amd64 (2:1.2.3-1build2) ...\n",
+ "Selecting previously unselected package libxt-dev:amd64.\n",
+ "Preparing to unpack .../14-libxt-dev_1%3a1.2.1-1_amd64.deb ...\n",
+ "Unpacking libxt-dev:amd64 (1:1.2.1-1) ...\n",
+ "Selecting previously unselected package freeglut3-dev:amd64.\n",
+ "Preparing to unpack .../15-freeglut3-dev_2.8.1-6_amd64.deb ...\n",
+ "Unpacking freeglut3-dev:amd64 (2.8.1-6) ...\n",
+ "Selecting previously unselected package libfontenc1:amd64.\n",
+ "Preparing to unpack .../16-libfontenc1_1%3a1.1.4-1build3_amd64.deb ...\n",
+ "Unpacking libfontenc1:amd64 (1:1.1.4-1build3) ...\n",
+ "Selecting previously unselected package libxfont2:amd64.\n",
+ "Preparing to unpack .../17-libxfont2_1%3a2.0.5-1build1_amd64.deb ...\n",
+ "Unpacking libxfont2:amd64 (1:2.0.5-1build1) ...\n",
+ "Selecting previously unselected package libxkbfile1:amd64.\n",
+ "Preparing to unpack .../18-libxkbfile1_1%3a1.1.0-1build3_amd64.deb ...\n",
+ "Unpacking libxkbfile1:amd64 (1:1.1.0-1build3) ...\n",
+ "Selecting previously unselected package x11-xkb-utils.\n",
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+ "Selecting previously unselected package xfonts-encodings.\n",
+ "Preparing to unpack .../20-xfonts-encodings_1%3a1.0.5-0ubuntu2_all.deb ...\n",
+ "Unpacking xfonts-encodings (1:1.0.5-0ubuntu2) ...\n",
+ "Selecting previously unselected package xfonts-utils.\n",
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+ "Selecting previously unselected package xfonts-base.\n",
+ "Preparing to unpack .../22-xfonts-base_1%3a1.0.5_all.deb ...\n",
+ "Unpacking xfonts-base (1:1.0.5) ...\n",
+ "Selecting previously unselected package xserver-common.\n",
+ "Preparing to unpack .../23-xserver-common_2%3a21.1.4-2ubuntu1.7~22.04.8_all.deb ...\n",
+ "Unpacking xserver-common (2:21.1.4-2ubuntu1.7~22.04.8) ...\n",
+ "Selecting previously unselected package xvfb.\n",
+ "Preparing to unpack .../24-xvfb_2%3a21.1.4-2ubuntu1.7~22.04.8_amd64.deb ...\n",
+ "Unpacking xvfb (2:21.1.4-2ubuntu1.7~22.04.8) ...\n",
+ "Setting up freeglut3:amd64 (2.8.1-6) ...\n",
+ "Setting up libglvnd-core-dev:amd64 (1.4.0-1) ...\n",
+ "Setting up libice-dev:amd64 (2:1.0.10-1build2) ...\n",
+ "Setting up libsm-dev:amd64 (2:1.2.3-1build2) ...\n",
+ "Setting up libfontenc1:amd64 (1:1.1.4-1build3) ...\n",
+ "Setting up libxt-dev:amd64 (1:1.2.1-1) ...\n",
+ "Setting up libgles1:amd64 (1.4.0-1) ...\n",
+ "Setting up xfonts-encodings (1:1.0.5-0ubuntu2) ...\n",
+ "Setting up libglx-dev:amd64 (1.4.0-1) ...\n",
+ "Setting up libglu1-mesa:amd64 (9.0.2-1) ...\n",
+ "Setting up libxkbfile1:amd64 (1:1.1.0-1build3) ...\n",
+ "Setting up libopengl-dev:amd64 (1.4.0-1) ...\n",
+ "Setting up libxfont2:amd64 (1:2.0.5-1build1) ...\n",
+ "Setting up libgl-dev:amd64 (1.4.0-1) ...\n",
+ "Setting up libegl-dev:amd64 (1.4.0-1) ...\n",
+ "Setting up x11-xkb-utils (7.7+5build4) ...\n",
+ "Setting up xfonts-utils (1:7.7+6build2) ...\n",
+ "Setting up xfonts-base (1:1.0.5) ...\n",
+ "Setting up libglu1-mesa-dev:amd64 (9.0.2-1) ...\n",
+ "Setting up xserver-common (2:21.1.4-2ubuntu1.7~22.04.8) ...\n",
+ "Setting up libgles-dev:amd64 (1.4.0-1) ...\n",
+ "Setting up xvfb (2:21.1.4-2ubuntu1.7~22.04.8) ...\n",
+ "Setting up libglvnd-dev:amd64 (1.4.0-1) ...\n",
+ "Setting up libgl1-mesa-dev:amd64 (23.2.1-1ubuntu3.1~22.04.2) ...\n",
+ "Setting up freeglut3-dev:amd64 (2.8.1-6) ...\n",
+ "Processing triggers for libc-bin (2.35-0ubuntu3.4) ...\n",
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+ "\n",
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+ " Downloading stable_baselines3-2.3.0a4-py3-none-any.whl (182 kB)\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m182.1/182.1 kB\u001b[0m \u001b[31m1.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[?25hRequirement already satisfied: gymnasium<0.30,>=0.28.1 in /usr/local/lib/python3.10/dist-packages (from stable-baselines3[extra]>=2.0.0a4) (0.29.1)\n",
+ "Requirement already satisfied: numpy>=1.20 in /usr/local/lib/python3.10/dist-packages (from stable-baselines3[extra]>=2.0.0a4) (1.25.2)\n",
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+ "Requirement already satisfied: rich in /usr/local/lib/python3.10/dist-packages (from stable-baselines3[extra]>=2.0.0a4) (13.7.1)\n",
+ "Collecting shimmy[atari]~=1.3.0 (from stable-baselines3[extra]>=2.0.0a4)\n",
+ " Downloading Shimmy-1.3.0-py3-none-any.whl (37 kB)\n",
+ "Requirement already satisfied: pillow in /usr/local/lib/python3.10/dist-packages (from stable-baselines3[extra]>=2.0.0a4) (9.4.0)\n",
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+ " Downloading AutoROM-0.6.1-py3-none-any.whl (9.4 kB)\n",
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+ "Requirement already satisfied: importlib-resources in /usr/local/lib/python3.10/dist-packages (from ale-py~=0.8.1->shimmy[atari]~=1.3.0->stable-baselines3[extra]>=2.0.0a4) (6.3.0)\n",
+ "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard>=2.9.1->stable-baselines3[extra]>=2.0.0a4) (5.3.3)\n",
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+ "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from google-auth-oauthlib<2,>=0.5->tensorboard>=2.9.1->stable-baselines3[extra]>=2.0.0a4) (1.4.0)\n",
+ "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich->stable-baselines3[extra]>=2.0.0a4) (0.1.2)\n",
+ "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->autorom[accept-rom-license]~=0.6.1->stable-baselines3[extra]>=2.0.0a4) (3.3.2)\n",
+ "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->autorom[accept-rom-license]~=0.6.1->stable-baselines3[extra]>=2.0.0a4) (3.6)\n",
+ "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->autorom[accept-rom-license]~=0.6.1->stable-baselines3[extra]>=2.0.0a4) (2.0.7)\n",
+ "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->autorom[accept-rom-license]~=0.6.1->stable-baselines3[extra]>=2.0.0a4) (2024.2.2)\n",
+ "Requirement already satisfied: MarkupSafe>=2.1.1 in /usr/local/lib/python3.10/dist-packages (from werkzeug>=1.0.1->tensorboard>=2.9.1->stable-baselines3[extra]>=2.0.0a4) (2.1.5)\n",
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+ "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<2,>=0.5->tensorboard>=2.9.1->stable-baselines3[extra]>=2.0.0a4) (3.2.2)\n",
+ "Building wheels for collected packages: AutoROM.accept-rom-license\n",
+ " Building wheel for AutoROM.accept-rom-license (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+ " Created wheel for AutoROM.accept-rom-license: filename=AutoROM.accept_rom_license-0.6.1-py3-none-any.whl size=446659 sha256=52a129f60cb655d6a7a5e2fb0906c018f4b7dd79dc30f3c7f7b6249a4f8021a8\n",
+ " Stored in directory: /root/.cache/pip/wheels/6b/1b/ef/a43ff1a2f1736d5711faa1ba4c1f61be1131b8899e6a057811\n",
+ "Successfully built AutoROM.accept-rom-license\n",
+ "Installing collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, ale-py, shimmy, nvidia-cusparse-cu12, nvidia-cudnn-cu12, AutoROM.accept-rom-license, autorom, nvidia-cusolver-cu12, stable-baselines3\n",
+ "Successfully installed AutoROM.accept-rom-license-0.6.1 ale-py-0.8.1 autorom-0.6.1 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.19.3 nvidia-nvjitlink-cu12-12.4.99 nvidia-nvtx-cu12-12.1.105 shimmy-1.3.0 stable-baselines3-2.3.0a4\n",
+ "Collecting panda-gym\n",
+ " Downloading panda_gym-3.0.7-py3-none-any.whl (23 kB)\n",
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+ "Collecting pybullet (from panda-gym)\n",
+ " Downloading pybullet-3.2.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (103.2 MB)\n",
+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m103.2/103.2 MB\u001b[0m \u001b[31m7.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+ "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from panda-gym) (1.25.2)\n",
+ "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from panda-gym) (1.11.4)\n",
+ "Requirement already satisfied: cloudpickle>=1.2.0 in /usr/local/lib/python3.10/dist-packages (from gymnasium>=0.26->panda-gym) (2.2.1)\n",
+ "Requirement already satisfied: typing-extensions>=4.3.0 in /usr/local/lib/python3.10/dist-packages (from gymnasium>=0.26->panda-gym) (4.10.0)\n",
+ "Requirement already satisfied: farama-notifications>=0.0.1 in /usr/local/lib/python3.10/dist-packages (from gymnasium>=0.26->panda-gym) (0.0.4)\n",
+ "Installing collected packages: pybullet, panda-gym\n",
+ "Successfully installed panda-gym-3.0.7 pybullet-3.2.6\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "ebzIUtg8Ysbf"
+ },
+ "outputs": [],
+ "source": [
+ "import gymnasium as gym\n",
+ "import torch\n",
+ "import torch.nn as nn\n",
+ "import torch.optim as optim\n",
+ "import torch.nn.functional as F\n",
+ "from torch.distributions import Categorical\n",
+ "import matplotlib.pyplot as plt\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# 1.0 Cartepole using OpenAI Gym Environement with A custom policy model"
+ ],
+ "metadata": {
+ "id": "QIxa36SjeEfG"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Create the environment\n",
+ "env = gym.make(\"CartPole-v1\", render_mode=\"human\")\n",
+ "\n",
+ "# Reset the environment and get the initial observation\n",
+ "observation = env.reset()\n",
+ "\n",
+ "state_size = env.observation_space.shape[0]\n",
+ "action_size = env.action_space.n\n",
+ "# Define the agent neural network model\n",
+ "class Policy(nn.Module):\n",
+ " def __init__(self, state_size, action_size, hidden_size=128):\n",
+ " super(Policy, self).__init__()\n",
+ " self.fc1 = nn.Linear(state_size, hidden_size)\n",
+ " self.relu = nn.ReLU()\n",
+ " self.dropout = nn.Dropout(p=0.6) # Adjust dropout probability as needed\n",
+ " self.fc2 = nn.Linear(hidden_size, action_size)\n",
+ "\n",
+ " def forward(self, x):\n",
+ " x = self.fc1(x)\n",
+ " x = self.relu(x)\n",
+ " x = self.dropout(x)\n",
+ " x = self.fc2(x)\n",
+ " return F.softmax(x)\n",
+ "\n",
+ "policy_model = Policy(state_size, action_size)\n",
+ "optimizer = optim.Adam(policy_model.parameters(), lr=5e-3)\n",
+ "\n",
+ "gamma = 0.99\n",
+ "episodes_rewards = []\n",
+ "\n",
+ "for i in range(500):\n",
+ " # Reset the environment\n",
+ " # init buffers\n",
+ " observation, info = env.reset(seed=42)\n",
+ " episode_rewards = []\n",
+ " logarithmich_probabilities = []\n",
+ " done = False\n",
+ " # Render the environment to visualize the agent's behavior\n",
+ " env.render()\n",
+ "\n",
+ " while done == False:\n",
+ " # Get action probabilities from the policy model\n",
+ " action_probabilities = policy_model(torch.tensor(observation, dtype=torch.float32))\n",
+ " action_distribution = Categorical(action_probabilities)\n",
+ "\n",
+ " # Sample an action from the action distribution\n",
+ " action = action_distribution.sample()\n",
+ " logarithmich_probability = action_distribution.log_prob(action)\n",
+ " logarithmich_probabilities.append(logarithmich_probability)\n",
+ " print(int(action.item()))\n",
+ " # Take a step in the environment\n",
+ " #print(env.step(action.item()))\n",
+ " next_observation, reward, done, a, b = env.step(action.item())\n",
+ " episode_rewards.append(reward)\n",
+ "\n",
+ " # Update observation\n",
+ " observation = next_observation\n",
+ "\n",
+ "\n",
+ " # Compute the return for the episode\n",
+ " returns = []\n",
+ " R = 0\n",
+ " for r in reversed(episode_rewards):\n",
+ " R = r + gamma * R\n",
+ " returns.insert(0, R)\n",
+ "\n",
+ " policy_loss = []\n",
+ " #print(len(logarithmich_probabilities))\n",
+ " #print(len(returns))\n",
+ "\n",
+ " for log_prob, R in zip(logarithmich_probabilities, returns):\n",
+ " policy_loss += [torch.tensor([-log_prob * R])]\n",
+ "\n",
+ " policy_loss = torch.cat(policy_loss).sum()\n",
+ "\n",
+ " print(policy_loss)\n",
+ " # Compute the policy loss\n",
+ " #policy_loss = torch.cat(policy_loss).sum()\n",
+ " episodes_rewards += [-policy_loss]\n",
+ " # Update the policy model\n",
+ " optimizer.zero_grad()\n",
+ " #rint(policy_loss)\n",
+ " policy_loss.requires_grad = True\n",
+ "\n",
+ " policy_loss.backward()\n",
+ " optimizer.step()\n",
+ "\n",
+ "\n",
+ "env.close()\n"
+ ],
+ "metadata": {
+ "id": "2CPcLVf-YzDK",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "8bce9f49-103e-48e9-90f3-7fe0230fba19"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "<ipython-input-20-785bba2d7191>:23: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
+ " return F.softmax(x)\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
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+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "episodes_rewards = [-episodes_rewards[i] for i in range(0,len(episodes_rewards))]\n",
+ "# Plot the policy loss against iterations\n",
+ "plt.plot([i for i in range(0,500)],episodes_rewards)\n",
+ "plt.xlabel('Iterations')\n",
+ "plt.ylabel('Policy Loss')\n",
+ "plt.title('Policy Loss vs. Iterations')\n",
+ "plt.show()"
+ ],
+ "metadata": {
+ "id": "hY52xEWUSlUV",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 472
+ },
+ "outputId": "84ec7e07-4261-40ec-cf9e-28c516eae4af"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<Figure size 640x480 with 1 Axes>"
+ ],
+ "image/png": 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\n"
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# 2.0 cartpole with stable-baselines3\n",
+ "\n",
+ "\n"
+ ],
+ "metadata": {
+ "id": "StaIGs4U6ez6"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "!apt-get update && apt-get install ffmpeg freeglut3-dev xvfb # For visualization\n",
+ "!pip install \"stable-baselines3[extra]>=2.0.0a4\""
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "byLoAEfZp-33",
+ "outputId": "053b32f9-42c2-44e7-e6ef-5a916059b471"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\r0% [Working]\r \rGet:1 https://cloud.r-project.org/bin/linux/ubuntu jammy-cran40/ InRelease [3,626 B]\n",
+ "Hit:2 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64 InRelease\n",
+ "Get:3 http://security.ubuntu.com/ubuntu jammy-security InRelease [110 kB]\n",
+ "Get:4 https://cloud.r-project.org/bin/linux/ubuntu jammy-cran40/ Packages [50.4 kB]\n",
+ "Hit:5 http://archive.ubuntu.com/ubuntu jammy InRelease\n",
+ "Get:6 http://archive.ubuntu.com/ubuntu jammy-updates InRelease [119 kB]\n",
+ "Hit:7 https://ppa.launchpadcontent.net/c2d4u.team/c2d4u4.0+/ubuntu jammy InRelease\n",
+ "Hit:8 https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu jammy InRelease\n",
+ "Get:9 http://security.ubuntu.com/ubuntu jammy-security/restricted amd64 Packages [1,894 kB]\n",
+ "Hit:10 https://ppa.launchpadcontent.net/graphics-drivers/ppa/ubuntu jammy InRelease\n",
+ "Hit:11 https://ppa.launchpadcontent.net/ubuntugis/ppa/ubuntu jammy InRelease\n",
+ "Hit:12 http://archive.ubuntu.com/ubuntu jammy-backports InRelease\n",
+ "Get:13 http://security.ubuntu.com/ubuntu jammy-security/universe amd64 Packages [1,074 kB]\n",
+ "Get:14 http://security.ubuntu.com/ubuntu jammy-security/main amd64 Packages [1,522 kB]\n",
+ "Get:15 http://archive.ubuntu.com/ubuntu jammy-updates/restricted amd64 Packages [1,932 kB]\n",
+ "Get:16 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 Packages [1,801 kB]\n",
+ "Get:17 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 Packages [1,346 kB]\n",
+ "Fetched 9,854 kB in 3s (3,522 kB/s)\n",
+ "Reading package lists... Done\n",
+ "Reading package lists... Done\n",
+ "Building dependency tree... Done\n",
+ "Reading state information... Done\n",
+ "ffmpeg is already the newest version (7:4.4.2-0ubuntu0.22.04.1).\n",
+ "The following additional packages will be installed:\n",
+ " freeglut3 libegl-dev libfontenc1 libgl-dev libgl1-mesa-dev libgles-dev libgles1 libglu1-mesa\n",
+ " libglu1-mesa-dev libglvnd-core-dev libglvnd-dev libglx-dev libice-dev libopengl-dev libsm-dev\n",
+ " libxfont2 libxkbfile1 libxt-dev x11-xkb-utils xfonts-base xfonts-encodings xfonts-utils\n",
+ " xserver-common\n",
+ "Suggested packages:\n",
+ " libice-doc libsm-doc libxt-doc\n",
+ "The following NEW packages will be installed:\n",
+ " freeglut3 freeglut3-dev libegl-dev libfontenc1 libgl-dev libgl1-mesa-dev libgles-dev libgles1\n",
+ " libglu1-mesa libglu1-mesa-dev libglvnd-core-dev libglvnd-dev libglx-dev libice-dev libopengl-dev\n",
+ " libsm-dev libxfont2 libxkbfile1 libxt-dev x11-xkb-utils xfonts-base xfonts-encodings xfonts-utils\n",
+ " xserver-common xvfb\n",
+ "0 upgraded, 25 newly installed, 0 to remove and 41 not upgraded.\n",
+ "Need to get 9,075 kB of archives.\n",
+ "After this operation, 18.7 MB of additional disk space will be used.\n",
+ "Get:1 http://archive.ubuntu.com/ubuntu jammy/universe amd64 freeglut3 amd64 2.8.1-6 [74.0 kB]\n",
+ "Get:2 http://archive.ubuntu.com/ubuntu jammy/main amd64 libglx-dev amd64 1.4.0-1 [14.1 kB]\n",
+ "Get:3 http://archive.ubuntu.com/ubuntu jammy/main amd64 libgl-dev amd64 1.4.0-1 [101 kB]\n",
+ "Get:4 http://archive.ubuntu.com/ubuntu jammy/main amd64 libglvnd-core-dev amd64 1.4.0-1 [12.7 kB]\n",
+ "Get:5 http://archive.ubuntu.com/ubuntu jammy/main amd64 libegl-dev amd64 1.4.0-1 [18.0 kB]\n",
+ "Get:6 http://archive.ubuntu.com/ubuntu jammy/main amd64 libgles1 amd64 1.4.0-1 [11.5 kB]\n",
+ "Get:7 http://archive.ubuntu.com/ubuntu jammy/main amd64 libgles-dev amd64 1.4.0-1 [49.4 kB]\n",
+ "Get:8 http://archive.ubuntu.com/ubuntu jammy/main amd64 libopengl-dev amd64 1.4.0-1 [3,400 B]\n",
+ "Get:9 http://archive.ubuntu.com/ubuntu jammy/main amd64 libglvnd-dev amd64 1.4.0-1 [3,162 B]\n",
+ "Get:10 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libgl1-mesa-dev amd64 23.2.1-1ubuntu3.1~22.04.2 [6,842 B]\n",
+ "Get:11 http://archive.ubuntu.com/ubuntu jammy/main amd64 libglu1-mesa amd64 9.0.2-1 [145 kB]\n",
+ "Get:12 http://archive.ubuntu.com/ubuntu jammy/main amd64 libglu1-mesa-dev amd64 9.0.2-1 [231 kB]\n",
+ "Get:13 http://archive.ubuntu.com/ubuntu jammy/main amd64 libice-dev amd64 2:1.0.10-1build2 [51.4 kB]\n",
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+ "Get:15 http://archive.ubuntu.com/ubuntu jammy/main amd64 libxt-dev amd64 1:1.2.1-1 [396 kB]\n",
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+ "(Reading database ... 121749 files and directories currently installed.)\n",
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+ "Setting up freeglut3:amd64 (2.8.1-6) ...\n",
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+ "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard>=2.9.1->stable-baselines3[extra]>=2.0.0a4) (0.3.0)\n",
+ "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard>=2.9.1->stable-baselines3[extra]>=2.0.0a4) (4.9)\n",
+ "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from google-auth-oauthlib<2,>=0.5->tensorboard>=2.9.1->stable-baselines3[extra]>=2.0.0a4) (1.3.1)\n",
+ "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich->stable-baselines3[extra]>=2.0.0a4) (0.1.2)\n",
+ "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->autorom[accept-rom-license]~=0.6.1->stable-baselines3[extra]>=2.0.0a4) (3.3.2)\n",
+ "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->autorom[accept-rom-license]~=0.6.1->stable-baselines3[extra]>=2.0.0a4) (3.6)\n",
+ "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->autorom[accept-rom-license]~=0.6.1->stable-baselines3[extra]>=2.0.0a4) (2.0.7)\n",
+ "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->autorom[accept-rom-license]~=0.6.1->stable-baselines3[extra]>=2.0.0a4) (2024.2.2)\n",
+ "Requirement already satisfied: MarkupSafe>=2.1.1 in /usr/local/lib/python3.10/dist-packages (from werkzeug>=1.0.1->tensorboard>=2.9.1->stable-baselines3[extra]>=2.0.0a4) (2.1.5)\n",
+ "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.13->stable-baselines3[extra]>=2.0.0a4) (1.3.0)\n",
+ "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard>=2.9.1->stable-baselines3[extra]>=2.0.0a4) (0.5.1)\n",
+ "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<2,>=0.5->tensorboard>=2.9.1->stable-baselines3[extra]>=2.0.0a4) (3.2.2)\n",
+ "Building wheels for collected packages: AutoROM.accept-rom-license\n",
+ " Building wheel for AutoROM.accept-rom-license (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
+ " Created wheel for AutoROM.accept-rom-license: filename=AutoROM.accept_rom_license-0.6.1-py3-none-any.whl size=446660 sha256=525219ed92b07d52de7e8c459a922d2e6af7c544a54b55368db234aa0242a7da\n",
+ " Stored in directory: /root/.cache/pip/wheels/6b/1b/ef/a43ff1a2f1736d5711faa1ba4c1f61be1131b8899e6a057811\n",
+ "Successfully built AutoROM.accept-rom-license\n",
+ "Installing collected packages: ale-py, shimmy, AutoROM.accept-rom-license, autorom, stable-baselines3\n",
+ "Successfully installed AutoROM.accept-rom-license-0.6.1 ale-py-0.8.1 autorom-0.6.1 shimmy-1.3.0 stable-baselines3-2.3.0a2\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "import gymnasium as gym\n",
+ "import numpy as np\n",
+ "from stable_baselines3.common.evaluation import evaluate_policy\n",
+ "from stable_baselines3 import A2C\n",
+ "from huggingface_sb3 import push_to_hub\n",
+ "from huggingface_hub import login\n",
+ "\n",
+ "\n",
+ "\n",
+ "print(f\"{gym.__version__=}\")"
+ ],
+ "metadata": {
+ "id": "kTzxDZ4M1X7m",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "9f1cf826-ea0a-4f91-c615-876fcd7818fc"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "gym.__version__='0.29.1'\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "env = gym.make(\"CartPole-v1\", render_mode=\"rgb_array\")\n",
+ "model = A2C(\"MlpPolicy\", env, verbose=1)"
+ ],
+ "metadata": {
+ "id": "1jpK_90YZhwm",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "88980150-d623-495b-ce18-c0368ad389de"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Using cuda device\n",
+ "Wrapping the env with a `Monitor` wrapper\n",
+ "Wrapping the env in a DummyVecEnv.\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "def evaluate(model, num_episodes=100, deterministic=True):\n",
+ "\n",
+ " vec_env = model.get_env()\n",
+ " all_episode_rewards = []\n",
+ " for i in range(num_episodes):\n",
+ " episode_rewards = []\n",
+ " done = False\n",
+ " obs = vec_env.reset()\n",
+ " while not done:\n",
+ " # _states are only useful when using LSTM policies\n",
+ " action, _states = model.predict(obs, deterministic=deterministic)\n",
+ " # here, action, rewards and dones are arrays\n",
+ " # also note that the step only returns a 4-tuple, as the env that is returned\n",
+ " obs, reward, done, info = vec_env.step(action)\n",
+ " episode_rewards.append(reward)\n",
+ "\n",
+ " all_episode_rewards.append(sum(episode_rewards))\n",
+ "\n",
+ " mean_episode_reward = np.mean(all_episode_rewards)\n",
+ " print(\"Mean reward:\", mean_episode_reward, \"Num episodes:\", num_episodes)\n",
+ "\n",
+ " return mean_episode_reward"
+ ],
+ "metadata": {
+ "id": "Mih1B33mZSV0"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Use a separate environement for evaluation\n",
+ "eval_env = gym.make(\"CartPole-v1\", render_mode=\"rgb_array\")"
+ ],
+ "metadata": {
+ "id": "NHNZ0-eFZtUq"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Train the agent for 10000 steps\n",
+ "model.learn(total_timesteps=10_000)"
+ ],
+ "metadata": {
+ "id": "a4b9VAvuZvUJ",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "4a90467d-5d73-4eed-885a-6c0858eeb9fb"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 20 |\n",
+ "| ep_rew_mean | 20 |\n",
+ "| time/ | |\n",
+ "| fps | 186 |\n",
+ "| iterations | 100 |\n",
+ "| time_elapsed | 2 |\n",
+ "| total_timesteps | 500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.692 |\n",
+ "| explained_variance | 0.0184 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 99 |\n",
+ "| policy_loss | 1.85 |\n",
+ "| value_loss | 9 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 23.1 |\n",
+ "| ep_rew_mean | 23.1 |\n",
+ "| time/ | |\n",
+ "| fps | 258 |\n",
+ "| iterations | 200 |\n",
+ "| time_elapsed | 3 |\n",
+ "| total_timesteps | 1000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.692 |\n",
+ "| explained_variance | 0.0291 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 199 |\n",
+ "| policy_loss | -6.12 |\n",
+ "| value_loss | 107 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 25.5 |\n",
+ "| ep_rew_mean | 25.5 |\n",
+ "| time/ | |\n",
+ "| fps | 299 |\n",
+ "| iterations | 300 |\n",
+ "| time_elapsed | 5 |\n",
+ "| total_timesteps | 1500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.684 |\n",
+ "| explained_variance | -0.00656 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 299 |\n",
+ "| policy_loss | 1.56 |\n",
+ "| value_loss | 6.39 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 27.8 |\n",
+ "| ep_rew_mean | 27.8 |\n",
+ "| time/ | |\n",
+ "| fps | 326 |\n",
+ "| iterations | 400 |\n",
+ "| time_elapsed | 6 |\n",
+ "| total_timesteps | 2000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.675 |\n",
+ "| explained_variance | 0.0542 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 399 |\n",
+ "| policy_loss | 1.29 |\n",
+ "| value_loss | 5.63 |\n",
+ "------------------------------------\n",
+ "-------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 30.7 |\n",
+ "| ep_rew_mean | 30.7 |\n",
+ "| time/ | |\n",
+ "| fps | 343 |\n",
+ "| iterations | 500 |\n",
+ "| time_elapsed | 7 |\n",
+ "| total_timesteps | 2500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.68 |\n",
+ "| explained_variance | -0.000433 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 499 |\n",
+ "| policy_loss | 1.21 |\n",
+ "| value_loss | 5.6 |\n",
+ "-------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 32.4 |\n",
+ "| ep_rew_mean | 32.4 |\n",
+ "| time/ | |\n",
+ "| fps | 339 |\n",
+ "| iterations | 600 |\n",
+ "| time_elapsed | 8 |\n",
+ "| total_timesteps | 3000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.603 |\n",
+ "| explained_variance | -0.0121 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 599 |\n",
+ "| policy_loss | 1.24 |\n",
+ "| value_loss | 5.01 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 34.4 |\n",
+ "| ep_rew_mean | 34.4 |\n",
+ "| time/ | |\n",
+ "| fps | 342 |\n",
+ "| iterations | 700 |\n",
+ "| time_elapsed | 10 |\n",
+ "| total_timesteps | 3500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.644 |\n",
+ "| explained_variance | 0.00312 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 699 |\n",
+ "| policy_loss | 1.04 |\n",
+ "| value_loss | 4.48 |\n",
+ "------------------------------------\n",
+ "-------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 37 |\n",
+ "| ep_rew_mean | 37 |\n",
+ "| time/ | |\n",
+ "| fps | 345 |\n",
+ "| iterations | 800 |\n",
+ "| time_elapsed | 11 |\n",
+ "| total_timesteps | 4000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.644 |\n",
+ "| explained_variance | -0.000278 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 799 |\n",
+ "| policy_loss | 0.917 |\n",
+ "| value_loss | 3.97 |\n",
+ "-------------------------------------\n",
+ "-------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 40.9 |\n",
+ "| ep_rew_mean | 40.9 |\n",
+ "| time/ | |\n",
+ "| fps | 354 |\n",
+ "| iterations | 900 |\n",
+ "| time_elapsed | 12 |\n",
+ "| total_timesteps | 4500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.625 |\n",
+ "| explained_variance | -0.000446 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 899 |\n",
+ "| policy_loss | -17.7 |\n",
+ "| value_loss | 1.61e+03 |\n",
+ "-------------------------------------\n",
+ "-------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 44.7 |\n",
+ "| ep_rew_mean | 44.7 |\n",
+ "| time/ | |\n",
+ "| fps | 362 |\n",
+ "| iterations | 1000 |\n",
+ "| time_elapsed | 13 |\n",
+ "| total_timesteps | 5000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.487 |\n",
+ "| explained_variance | -7.62e-05 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 999 |\n",
+ "| policy_loss | 0.681 |\n",
+ "| value_loss | 3 |\n",
+ "-------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 48.1 |\n",
+ "| ep_rew_mean | 48.1 |\n",
+ "| time/ | |\n",
+ "| fps | 367 |\n",
+ "| iterations | 1100 |\n",
+ "| time_elapsed | 14 |\n",
+ "| total_timesteps | 5500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.616 |\n",
+ "| explained_variance | 0.00327 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 1099 |\n",
+ "| policy_loss | 0.828 |\n",
+ "| value_loss | 2.53 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 52.8 |\n",
+ "| ep_rew_mean | 52.8 |\n",
+ "| time/ | |\n",
+ "| fps | 373 |\n",
+ "| iterations | 1200 |\n",
+ "| time_elapsed | 16 |\n",
+ "| total_timesteps | 6000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.52 |\n",
+ "| explained_variance | -6.9e-05 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 1199 |\n",
+ "| policy_loss | 0.904 |\n",
+ "| value_loss | 2.11 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 56.5 |\n",
+ "| ep_rew_mean | 56.5 |\n",
+ "| time/ | |\n",
+ "| fps | 377 |\n",
+ "| iterations | 1300 |\n",
+ "| time_elapsed | 17 |\n",
+ "| total_timesteps | 6500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.566 |\n",
+ "| explained_variance | 1.93e-05 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 1299 |\n",
+ "| policy_loss | 0.926 |\n",
+ "| value_loss | 1.71 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 59.8 |\n",
+ "| ep_rew_mean | 59.8 |\n",
+ "| time/ | |\n",
+ "| fps | 381 |\n",
+ "| iterations | 1400 |\n",
+ "| time_elapsed | 18 |\n",
+ "| total_timesteps | 7000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.655 |\n",
+ "| explained_variance | 8.76e-06 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 1399 |\n",
+ "| policy_loss | 0.654 |\n",
+ "| value_loss | 1.37 |\n",
+ "------------------------------------\n",
+ "-------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 65 |\n",
+ "| ep_rew_mean | 65 |\n",
+ "| time/ | |\n",
+ "| fps | 384 |\n",
+ "| iterations | 1500 |\n",
+ "| time_elapsed | 19 |\n",
+ "| total_timesteps | 7500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.343 |\n",
+ "| explained_variance | -2.01e-05 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 1499 |\n",
+ "| policy_loss | 0.927 |\n",
+ "| value_loss | 1.08 |\n",
+ "-------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 69.3 |\n",
+ "| ep_rew_mean | 69.3 |\n",
+ "| time/ | |\n",
+ "| fps | 386 |\n",
+ "| iterations | 1600 |\n",
+ "| time_elapsed | 20 |\n",
+ "| total_timesteps | 8000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.579 |\n",
+ "| explained_variance | 6.14e-06 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 1599 |\n",
+ "| policy_loss | -36.9 |\n",
+ "| value_loss | 1.02e+03 |\n",
+ "------------------------------------\n",
+ "-------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 71.8 |\n",
+ "| ep_rew_mean | 71.8 |\n",
+ "| time/ | |\n",
+ "| fps | 386 |\n",
+ "| iterations | 1700 |\n",
+ "| time_elapsed | 21 |\n",
+ "| total_timesteps | 8500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.566 |\n",
+ "| explained_variance | -4.07e-05 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 1699 |\n",
+ "| policy_loss | 0.465 |\n",
+ "| value_loss | 0.579 |\n",
+ "-------------------------------------\n",
+ "-------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 77 |\n",
+ "| ep_rew_mean | 77 |\n",
+ "| time/ | |\n",
+ "| fps | 383 |\n",
+ "| iterations | 1800 |\n",
+ "| time_elapsed | 23 |\n",
+ "| total_timesteps | 9000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.583 |\n",
+ "| explained_variance | -1.61e-05 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 1799 |\n",
+ "| policy_loss | 0.334 |\n",
+ "| value_loss | 0.382 |\n",
+ "-------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 80.8 |\n",
+ "| ep_rew_mean | 80.8 |\n",
+ "| time/ | |\n",
+ "| fps | 386 |\n",
+ "| iterations | 1900 |\n",
+ "| time_elapsed | 24 |\n",
+ "| total_timesteps | 9500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.573 |\n",
+ "| explained_variance | 3.22e-05 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 1899 |\n",
+ "| policy_loss | 0.237 |\n",
+ "| value_loss | 0.229 |\n",
+ "------------------------------------\n",
+ "-------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 84.5 |\n",
+ "| ep_rew_mean | 84.5 |\n",
+ "| time/ | |\n",
+ "| fps | 388 |\n",
+ "| iterations | 2000 |\n",
+ "| time_elapsed | 25 |\n",
+ "| total_timesteps | 10000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -0.46 |\n",
+ "| explained_variance | -5.95e-05 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 1999 |\n",
+ "| policy_loss | 0.213 |\n",
+ "| value_loss | 0.119 |\n",
+ "-------------------------------------\n"
+ ]
+ },
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "<stable_baselines3.a2c.a2c.A2C at 0x7e7efb9c3f40>"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 9
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Evaluate the trained agent\n",
+ "mean_reward, std_reward = evaluate_policy(model, eval_env, n_eval_episodes=100)\n",
+ "\n",
+ "print(f\"mean_reward:{mean_reward:.2f} +/- {std_reward:.2f}\")"
+ ],
+ "metadata": {
+ "id": "A1b3dko0Zxix",
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "outputId": "090ab383-3321-4b5c-ef0b-d4fb9fea8351"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "/usr/local/lib/python3.10/dist-packages/stable_baselines3/common/evaluation.py:67: UserWarning: Evaluation environment is not wrapped with a ``Monitor`` wrapper. This may result in reporting modified episode lengths and rewards, if other wrappers happen to modify these. Consider wrapping environment first with ``Monitor`` wrapper.\n",
+ " warnings.warn(\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "mean_reward:152.85 +/- 17.30\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "### saving the learned model in hub"
+ ],
+ "metadata": {
+ "id": "x6FPQxixCU6A"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "login(token=\"****************\")"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "H0pKB3u7RNln",
+ "outputId": "03ccf8e1-baf5-4cdb-d915-49d8d881f2fd"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Token will not been saved to git credential helper. Pass `add_to_git_credential=True` if you want to set the git credential as well.\n",
+ "Token is valid (permission: write).\n",
+ "Your token has been saved to /root/.cache/huggingface/token\n",
+ "Login successful\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Save the trained model\n",
+ "model.save(\"ECL-TD-RL1-a2c_cartpole.zip\")\n",
+ "\n",
+ "# Load the trained model\n",
+ "model = A2C.load(\"ECL-TD-RL1-a2c_cartpole.zip\")\n",
+ "\n",
+ "push_to_hub(\n",
+ " repo_id=\"Karim-20/a2c_cartpole\",\n",
+ " filename=\"ECL-TD-RL1-a2c_cartpole.zip\",\n",
+ " commit_message=\"Add cartepole-v1 environement, agent used to train is A2C\"\n",
+ ")\n"
+ ],
+ "metadata": {
+ "id": "9lgpQBFeDIVx",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 136,
+ "referenced_widgets": [
+ "3bf20325eeb94361964c8a1620c38727",
+ "0fdb788454a34aa9bc545568ed8afad7",
+ "c61ff44a39204ce88d3a43c02388b6e6",
+ "e650459cdbdc425ca554d4f66c3d6d40",
+ "9ff1bdcd30904e669984f48e4a93ae0c",
+ "69ece13913d844ca8e7209cc125e2d7b",
+ "3525ebe3a5944b278adff0cd7c59a5d7",
+ "656ba980bd9247f0b9f9c4ecf8b1e4a7",
+ "572fe508383646baaf82b2349366c671",
+ "c9f0b1c6f1a74c238ccb347bee20b397",
+ "9d8e4e68afed4d90a59c4293cd4a6b9d"
+ ]
+ },
+ "outputId": "cea78c0f-ffdf-4318-def2-c8c3e19c0c35"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\u001b[38;5;4mℹ Pushing repo Karim-20/a2c_cartpole to the Hugging Face Hub\u001b[0m\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "ECL-TD-RL1-a2c_cartpole.zip: 0%| | 0.00/98.1k [00:00<?, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "3bf20325eeb94361964c8a1620c38727"
+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\u001b[38;5;2m✔ Your model has been uploaded to the Hub, you can find it here:\n",
+ "https://huggingface.co/Karim-20/a2c_cartpole/tree/main/\u001b[0m\n"
+ ]
+ },
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "CommitInfo(commit_url='https://huggingface.co/Karim-20/a2c_cartpole/commit/11ea47a77ed2f507464852dda3f3888abd0e692c', commit_message='Add cartepole-v1 environement, agent used to train is A2C', commit_description='', oid='11ea47a77ed2f507464852dda3f3888abd0e692c', pr_url=None, pr_revision=None, pr_num=None)"
+ ],
+ "application/vnd.google.colaboratory.intrinsic+json": {
+ "type": "string"
+ }
+ },
+ "metadata": {},
+ "execution_count": 20
+ }
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# 3.0 PandaReachJointsDense-v2"
+ ],
+ "metadata": {
+ "id": "nXlE_QHYd70G"
+ }
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "### LIBRARIES\n",
+ "\n",
+ "import gymnasium as gym\n",
+ "from stable_baselines3 import A2C\n",
+ "from stable_baselines3.common.monitor import Monitor\n",
+ "from stable_baselines3.common.vec_env import DummyVecEnv, VecVideoRecorder\n",
+ "import wandb\n",
+ "from wandb.integration.sb3 import WandbCallback\n",
+ "from huggingface_sb3 import push_to_hub\n",
+ "import panda_gym\n",
+ "import os\n",
+ "from huggingface_hub import login\n"
+ ],
+ "metadata": {
+ "id": "0YBce66VQoaL"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "\n",
+ "#dir_path = os.path.dirname(os.path.realpath(__file__))\n",
+ "#os.chdir(dir_path)\n",
+ "\n",
+ "config = {\n",
+ " \"policy_type\": \"MultiInputPolicy\",\n",
+ " \"total_timesteps\": 250000,\n",
+ " \"env_name\": \"PandaReachJointsDense-v3\",\n",
+ "}\n",
+ "\n",
+ "run = wandb.init(\n",
+ " project=\"sb3-panda-reach\",\n",
+ " config=config,\n",
+ " sync_tensorboard=True, # auto-upload sb3's tensorboard metrics\n",
+ " monitor_gym=True, # auto-upload the videos of agents playing the game\n",
+ " save_code=True, # optional\n",
+ ")\n",
+ "\n",
+ "def make_env():\n",
+ " env = gym.make(config[\"env_name\"])\n",
+ " env = Monitor(env) # record stats such as returns\n",
+ " return env\n",
+ "\n",
+ "env = DummyVecEnv([make_env])\n",
+ "# env = VecVideoRecorder(env, f\"videos/{run.id}\", record_video_trigger=lambda x: x % 2000 == 0, video_length=200)\n",
+ "model = A2C(config[\"policy_type\"], env, verbose=1, tensorboard_log=f\"runs/{run.id}\")\n",
+ "model.learn(\n",
+ " total_timesteps=config[\"total_timesteps\"],\n",
+ " callback=WandbCallback(\n",
+ " gradient_save_freq=100,\n",
+ " model_save_path=f\"models/{run.id}\",\n",
+ " verbose=2,\n",
+ " ),\n",
+ ")\n",
+ "\n",
+ "run.finish()\n",
+ "\n"
+ ],
+ "metadata": {
+ "id": "-iPcpsSpAWh0",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 1000,
+ "referenced_widgets": [
+ "c14a53fd35174f3ba632a22e3c9dda47",
+ "02913ffc7b024793ab252e74c0427aa9",
+ "53f02b9c14564874baecde3983423440",
+ "83c1d52aef7d421db0657103710bcd06",
+ "9346924fc0d14e10924684c0ab74891c",
+ "4cf73107b2a74863a612244964f0fc04",
+ "c056c0b446134ae69bdc93bd93f3af13",
+ "3d54d2c162b34319bfd1428fb18fd181"
+ ]
+ },
+ "outputId": "41cb3d73-4ca4-49f7-f258-f4062ca0cad8"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ],
+ "text/html": [
+ "Tracking run with wandb version 0.16.3"
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ],
+ "text/html": [
+ "Run data is saved locally in <code>/content/wandb/run-20240305_210146-ihcoeovn</code>"
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ],
+ "text/html": [
+ "Syncing run <strong><a href='https://wandb.ai/aiblackbelt/sb3-panda-reach/runs/ihcoeovn' target=\"_blank\">dashing-glitter-6</a></strong> to <a href='https://wandb.ai/aiblackbelt/sb3-panda-reach' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/run' target=\"_blank\">docs</a>)<br/>"
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ],
+ "text/html": [
+ " View project at <a href='https://wandb.ai/aiblackbelt/sb3-panda-reach' target=\"_blank\">https://wandb.ai/aiblackbelt/sb3-panda-reach</a>"
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ],
+ "text/html": [
+ " View run at <a href='https://wandb.ai/aiblackbelt/sb3-panda-reach/runs/ihcoeovn' target=\"_blank\">https://wandb.ai/aiblackbelt/sb3-panda-reach/runs/ihcoeovn</a>"
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m When using several event log directories, please call `wandb.tensorboard.patch(root_logdir=\"...\")` before `wandb.init`\n"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\u001b[1;30;43mLe flux de sortie a été tronqué et ne contient que les 5000 dernières lignes.\u001b[0m\n",
+ "| time/ | |\n",
+ "| fps | 216 |\n",
+ "| iterations | 22300 |\n",
+ "| time_elapsed | 515 |\n",
+ "| total_timesteps | 111500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.45 |\n",
+ "| explained_variance | 0.00867 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 22299 |\n",
+ "| policy_loss | -2.16 |\n",
+ "| std | 0.939 |\n",
+ "| value_loss | 0.0636 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 44.9 |\n",
+ "| ep_rew_mean | -7.03 |\n",
+ "| time/ | |\n",
+ "| fps | 216 |\n",
+ "| iterations | 22400 |\n",
+ "| time_elapsed | 518 |\n",
+ "| total_timesteps | 112000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.48 |\n",
+ "| explained_variance | -0.683 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 22399 |\n",
+ "| policy_loss | 1.14 |\n",
+ "| std | 0.943 |\n",
+ "| value_loss | 0.0359 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 43.9 |\n",
+ "| ep_rew_mean | -6.64 |\n",
+ "| time/ | |\n",
+ "| fps | 216 |\n",
+ "| iterations | 22500 |\n",
+ "| time_elapsed | 520 |\n",
+ "| total_timesteps | 112500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.5 |\n",
+ "| explained_variance | -0.145 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 22499 |\n",
+ "| policy_loss | -2.57 |\n",
+ "| std | 0.945 |\n",
+ "| value_loss | 0.0833 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 42.8 |\n",
+ "| ep_rew_mean | -6.33 |\n",
+ "| time/ | |\n",
+ "| fps | 216 |\n",
+ "| iterations | 22600 |\n",
+ "| time_elapsed | 522 |\n",
+ "| total_timesteps | 113000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.49 |\n",
+ "| explained_variance | -8.08 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 22599 |\n",
+ "| policy_loss | -1.29 |\n",
+ "| std | 0.945 |\n",
+ "| value_loss | 0.0271 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 36.1 |\n",
+ "| ep_rew_mean | -4.9 |\n",
+ "| time/ | |\n",
+ "| fps | 216 |\n",
+ "| iterations | 22700 |\n",
+ "| time_elapsed | 525 |\n",
+ "| total_timesteps | 113500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.46 |\n",
+ "| explained_variance | -0.776 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 22699 |\n",
+ "| policy_loss | 52.8 |\n",
+ "| std | 0.941 |\n",
+ "| value_loss | 42.4 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 32.1 |\n",
+ "| ep_rew_mean | -4.16 |\n",
+ "| time/ | |\n",
+ "| fps | 216 |\n",
+ "| iterations | 22800 |\n",
+ "| time_elapsed | 527 |\n",
+ "| total_timesteps | 114000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.47 |\n",
+ "| explained_variance | 0.752 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 22799 |\n",
+ "| policy_loss | -0.807 |\n",
+ "| std | 0.942 |\n",
+ "| value_loss | 0.00859 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.8 |\n",
+ "| ep_rew_mean | -2.49 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 22900 |\n",
+ "| time_elapsed | 530 |\n",
+ "| total_timesteps | 114500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.45 |\n",
+ "| explained_variance | -0.247 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 22899 |\n",
+ "| policy_loss | 62.9 |\n",
+ "| std | 0.939 |\n",
+ "| value_loss | 72.4 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 19.7 |\n",
+ "| ep_rew_mean | -2.21 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 23000 |\n",
+ "| time_elapsed | 532 |\n",
+ "| total_timesteps | 115000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.44 |\n",
+ "| explained_variance | 0.965 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 22999 |\n",
+ "| policy_loss | -4.07 |\n",
+ "| std | 0.938 |\n",
+ "| value_loss | 0.216 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.5 |\n",
+ "| ep_rew_mean | -2.51 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 23100 |\n",
+ "| time_elapsed | 534 |\n",
+ "| total_timesteps | 115500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.45 |\n",
+ "| explained_variance | -2.05 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 23099 |\n",
+ "| policy_loss | 2.27 |\n",
+ "| std | 0.939 |\n",
+ "| value_loss | 0.0759 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 23 |\n",
+ "| ep_rew_mean | -2.74 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 23200 |\n",
+ "| time_elapsed | 537 |\n",
+ "| total_timesteps | 116000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.45 |\n",
+ "| explained_variance | -6.83 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 23199 |\n",
+ "| policy_loss | 0.588 |\n",
+ "| std | 0.939 |\n",
+ "| value_loss | 0.0248 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 25.4 |\n",
+ "| ep_rew_mean | -3.11 |\n",
+ "| time/ | |\n",
+ "| fps | 216 |\n",
+ "| iterations | 23300 |\n",
+ "| time_elapsed | 539 |\n",
+ "| total_timesteps | 116500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.44 |\n",
+ "| explained_variance | -22 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 23299 |\n",
+ "| policy_loss | -0.0544 |\n",
+ "| std | 0.938 |\n",
+ "| value_loss | 0.0256 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 28 |\n",
+ "| ep_rew_mean | -3.46 |\n",
+ "| time/ | |\n",
+ "| fps | 216 |\n",
+ "| iterations | 23400 |\n",
+ "| time_elapsed | 541 |\n",
+ "| total_timesteps | 117000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.41 |\n",
+ "| explained_variance | -3 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 23399 |\n",
+ "| policy_loss | -0.346 |\n",
+ "| std | 0.933 |\n",
+ "| value_loss | 0.0151 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 31.2 |\n",
+ "| ep_rew_mean | -3.96 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 23500 |\n",
+ "| time_elapsed | 544 |\n",
+ "| total_timesteps | 117500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.4 |\n",
+ "| explained_variance | -43.3 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 23499 |\n",
+ "| policy_loss | 2.42 |\n",
+ "| std | 0.932 |\n",
+ "| value_loss | 0.07 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 30.6 |\n",
+ "| ep_rew_mean | -3.97 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 23600 |\n",
+ "| time_elapsed | 546 |\n",
+ "| total_timesteps | 118000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.41 |\n",
+ "| explained_variance | -53.5 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 23599 |\n",
+ "| policy_loss | -2.25 |\n",
+ "| std | 0.933 |\n",
+ "| value_loss | 0.0758 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 32 |\n",
+ "| ep_rew_mean | -4.39 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 23700 |\n",
+ "| time_elapsed | 548 |\n",
+ "| total_timesteps | 118500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.43 |\n",
+ "| explained_variance | -1.86 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 23699 |\n",
+ "| policy_loss | -1.53 |\n",
+ "| std | 0.937 |\n",
+ "| value_loss | 0.0645 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 32.3 |\n",
+ "| ep_rew_mean | -4.6 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 23800 |\n",
+ "| time_elapsed | 550 |\n",
+ "| total_timesteps | 119000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.41 |\n",
+ "| explained_variance | -2.95 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 23799 |\n",
+ "| policy_loss | 3.8 |\n",
+ "| std | 0.933 |\n",
+ "| value_loss | 0.316 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 32.8 |\n",
+ "| ep_rew_mean | -4.61 |\n",
+ "| time/ | |\n",
+ "| fps | 216 |\n",
+ "| iterations | 23900 |\n",
+ "| time_elapsed | 553 |\n",
+ "| total_timesteps | 119500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.4 |\n",
+ "| explained_variance | 0.991 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 23899 |\n",
+ "| policy_loss | -1.39 |\n",
+ "| std | 0.933 |\n",
+ "| value_loss | 0.0448 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 32.2 |\n",
+ "| ep_rew_mean | -4.6 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 24000 |\n",
+ "| time_elapsed | 556 |\n",
+ "| total_timesteps | 120000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.42 |\n",
+ "| explained_variance | -4.95 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 23999 |\n",
+ "| policy_loss | 2.49 |\n",
+ "| std | 0.935 |\n",
+ "| value_loss | 0.0738 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 30.8 |\n",
+ "| ep_rew_mean | -4.37 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 24100 |\n",
+ "| time_elapsed | 558 |\n",
+ "| total_timesteps | 120500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.42 |\n",
+ "| explained_variance | -6.33 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 24099 |\n",
+ "| policy_loss | -0.807 |\n",
+ "| std | 0.935 |\n",
+ "| value_loss | 0.0239 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 31 |\n",
+ "| ep_rew_mean | -4.31 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 24200 |\n",
+ "| time_elapsed | 560 |\n",
+ "| total_timesteps | 121000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.39 |\n",
+ "| explained_variance | -2.43 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 24199 |\n",
+ "| policy_loss | -9.51 |\n",
+ "| std | 0.931 |\n",
+ "| value_loss | 1.49 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 29.7 |\n",
+ "| ep_rew_mean | -3.95 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 24300 |\n",
+ "| time_elapsed | 562 |\n",
+ "| total_timesteps | 121500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.38 |\n",
+ "| explained_variance | -1.98 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 24299 |\n",
+ "| policy_loss | -0.455 |\n",
+ "| std | 0.93 |\n",
+ "| value_loss | 0.0111 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 28.1 |\n",
+ "| ep_rew_mean | -3.58 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 24400 |\n",
+ "| time_elapsed | 565 |\n",
+ "| total_timesteps | 122000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.35 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 24399 |\n",
+ "| policy_loss | -0.0601 |\n",
+ "| std | 0.926 |\n",
+ "| value_loss | 0.0105 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 27.9 |\n",
+ "| ep_rew_mean | -3.59 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 24500 |\n",
+ "| time_elapsed | 567 |\n",
+ "| total_timesteps | 122500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.37 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 24499 |\n",
+ "| policy_loss | -0.474 |\n",
+ "| std | 0.929 |\n",
+ "| value_loss | 0.00794 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 29.4 |\n",
+ "| ep_rew_mean | -4.04 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 24600 |\n",
+ "| time_elapsed | 570 |\n",
+ "| total_timesteps | 123000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.39 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 24599 |\n",
+ "| policy_loss | -1.6 |\n",
+ "| std | 0.931 |\n",
+ "| value_loss | 0.0356 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 30.6 |\n",
+ "| ep_rew_mean | -4.51 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 24700 |\n",
+ "| time_elapsed | 572 |\n",
+ "| total_timesteps | 123500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.38 |\n",
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+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | -3.84 |\n",
+ "| std | 0.93 |\n",
+ "| value_loss | 0.176 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 32.9 |\n",
+ "| ep_rew_mean | -5.19 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 24800 |\n",
+ "| time_elapsed | 574 |\n",
+ "| total_timesteps | 124000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.4 |\n",
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+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | 187 |\n",
+ "| std | 0.931 |\n",
+ "| value_loss | 547 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 32.5 |\n",
+ "| ep_rew_mean | -5.08 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 24900 |\n",
+ "| time_elapsed | 577 |\n",
+ "| total_timesteps | 124500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.39 |\n",
+ "| explained_variance | -2.02 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 24899 |\n",
+ "| policy_loss | -4.38 |\n",
+ "| std | 0.931 |\n",
+ "| value_loss | 0.253 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 33.5 |\n",
+ "| ep_rew_mean | -5.31 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 25000 |\n",
+ "| time_elapsed | 579 |\n",
+ "| total_timesteps | 125000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.39 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 24999 |\n",
+ "| policy_loss | -0.974 |\n",
+ "| std | 0.93 |\n",
+ "| value_loss | 0.0223 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 34.6 |\n",
+ "| ep_rew_mean | -5.53 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 25100 |\n",
+ "| time_elapsed | 582 |\n",
+ "| total_timesteps | 125500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.38 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 25099 |\n",
+ "| policy_loss | -2.16 |\n",
+ "| std | 0.929 |\n",
+ "| value_loss | 0.0498 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 36.2 |\n",
+ "| ep_rew_mean | -5.88 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 25200 |\n",
+ "| time_elapsed | 584 |\n",
+ "| total_timesteps | 126000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.38 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 25199 |\n",
+ "| policy_loss | 1.16 |\n",
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+ "| value_loss | 0.0288 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 37.1 |\n",
+ "| ep_rew_mean | -5.92 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 25300 |\n",
+ "| time_elapsed | 587 |\n",
+ "| total_timesteps | 126500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.37 |\n",
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+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | -1.05 |\n",
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+ "| value_loss | 0.0258 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 35 |\n",
+ "| ep_rew_mean | -5.25 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 25400 |\n",
+ "| time_elapsed | 589 |\n",
+ "| total_timesteps | 127000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.38 |\n",
+ "| explained_variance | -15.2 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 25399 |\n",
+ "| policy_loss | 3.79 |\n",
+ "| std | 0.929 |\n",
+ "| value_loss | 0.251 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
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+ "| ep_rew_mean | -5.17 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 25500 |\n",
+ "| time_elapsed | 591 |\n",
+ "| total_timesteps | 127500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.39 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 25499 |\n",
+ "| policy_loss | 1.61 |\n",
+ "| std | 0.93 |\n",
+ "| value_loss | 0.0388 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 37.3 |\n",
+ "| ep_rew_mean | -5.45 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 25600 |\n",
+ "| time_elapsed | 593 |\n",
+ "| total_timesteps | 128000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.39 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 25599 |\n",
+ "| policy_loss | 1.74 |\n",
+ "| std | 0.931 |\n",
+ "| value_loss | 0.0342 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 37.3 |\n",
+ "| ep_rew_mean | -5.49 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 25700 |\n",
+ "| time_elapsed | 596 |\n",
+ "| total_timesteps | 128500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.38 |\n",
+ "| explained_variance | -2.54 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 25699 |\n",
+ "| policy_loss | -1.86 |\n",
+ "| std | 0.929 |\n",
+ "| value_loss | 0.053 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 37.7 |\n",
+ "| ep_rew_mean | -5.64 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 25800 |\n",
+ "| time_elapsed | 598 |\n",
+ "| total_timesteps | 129000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.37 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 25799 |\n",
+ "| policy_loss | -0.621 |\n",
+ "| std | 0.928 |\n",
+ "| value_loss | 0.0133 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 37.3 |\n",
+ "| ep_rew_mean | -5.42 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 25900 |\n",
+ "| time_elapsed | 601 |\n",
+ "| total_timesteps | 129500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.38 |\n",
+ "| explained_variance | -76.5 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 25899 |\n",
+ "| policy_loss | 0.284 |\n",
+ "| std | 0.929 |\n",
+ "| value_loss | 0.0124 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 36.8 |\n",
+ "| ep_rew_mean | -5.41 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 26000 |\n",
+ "| time_elapsed | 603 |\n",
+ "| total_timesteps | 130000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.35 |\n",
+ "| explained_variance | -0.16 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 25999 |\n",
+ "| policy_loss | 2.86 |\n",
+ "| std | 0.925 |\n",
+ "| value_loss | 0.106 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 37.7 |\n",
+ "| ep_rew_mean | -5.52 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 26100 |\n",
+ "| time_elapsed | 605 |\n",
+ "| total_timesteps | 130500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.35 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 26099 |\n",
+ "| policy_loss | 0.113 |\n",
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+ "| value_loss | 0.000767 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 37.7 |\n",
+ "| ep_rew_mean | -5.61 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 26200 |\n",
+ "| time_elapsed | 608 |\n",
+ "| total_timesteps | 131000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.32 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 26199 |\n",
+ "| policy_loss | -0.0984 |\n",
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+ "| value_loss | 0.00199 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 37.3 |\n",
+ "| ep_rew_mean | -5.59 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 26300 |\n",
+ "| time_elapsed | 610 |\n",
+ "| total_timesteps | 131500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.29 |\n",
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+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | 1.5 |\n",
+ "| std | 0.918 |\n",
+ "| value_loss | 0.0374 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
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+ "| ep_rew_mean | -5.76 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 26400 |\n",
+ "| time_elapsed | 612 |\n",
+ "| total_timesteps | 132000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.3 |\n",
+ "| explained_variance | -3.7 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 26399 |\n",
+ "| policy_loss | 3.28 |\n",
+ "| std | 0.919 |\n",
+ "| value_loss | 0.12 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 38.2 |\n",
+ "| ep_rew_mean | -5.88 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 26500 |\n",
+ "| time_elapsed | 614 |\n",
+ "| total_timesteps | 132500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.3 |\n",
+ "| explained_variance | -1.6 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 26499 |\n",
+ "| policy_loss | -2.88 |\n",
+ "| std | 0.92 |\n",
+ "| value_loss | 0.159 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 38.4 |\n",
+ "| ep_rew_mean | -5.92 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 26600 |\n",
+ "| time_elapsed | 616 |\n",
+ "| total_timesteps | 133000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.3 |\n",
+ "| explained_variance | -0.651 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 26599 |\n",
+ "| policy_loss | 0.364 |\n",
+ "| std | 0.919 |\n",
+ "| value_loss | 0.00463 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 36 |\n",
+ "| ep_rew_mean | -5.42 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 26700 |\n",
+ "| time_elapsed | 619 |\n",
+ "| total_timesteps | 133500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.3 |\n",
+ "| explained_variance | -1.05 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 26699 |\n",
+ "| policy_loss | 1.63 |\n",
+ "| std | 0.921 |\n",
+ "| value_loss | 0.0252 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 34.8 |\n",
+ "| ep_rew_mean | -5.18 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 26800 |\n",
+ "| time_elapsed | 622 |\n",
+ "| total_timesteps | 134000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.29 |\n",
+ "| explained_variance | -1.78 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 26799 |\n",
+ "| policy_loss | 0.653 |\n",
+ "| std | 0.918 |\n",
+ "| value_loss | 0.00575 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 30.9 |\n",
+ "| ep_rew_mean | -4.33 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 26900 |\n",
+ "| time_elapsed | 624 |\n",
+ "| total_timesteps | 134500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.31 |\n",
+ "| explained_variance | -42.5 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 26899 |\n",
+ "| policy_loss | 0.447 |\n",
+ "| std | 0.922 |\n",
+ "| value_loss | 0.00399 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 24.8 |\n",
+ "| ep_rew_mean | -3.04 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 27000 |\n",
+ "| time_elapsed | 626 |\n",
+ "| total_timesteps | 135000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.3 |\n",
+ "| explained_variance | -11.1 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 26999 |\n",
+ "| policy_loss | -0.0141 |\n",
+ "| std | 0.92 |\n",
+ "| value_loss | 0.032 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 25.6 |\n",
+ "| ep_rew_mean | -3.05 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 27100 |\n",
+ "| time_elapsed | 628 |\n",
+ "| total_timesteps | 135500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.27 |\n",
+ "| explained_variance | -10.8 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 27099 |\n",
+ "| policy_loss | 1.04 |\n",
+ "| std | 0.917 |\n",
+ "| value_loss | 0.0236 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 25.4 |\n",
+ "| ep_rew_mean | -3.01 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 27200 |\n",
+ "| time_elapsed | 631 |\n",
+ "| total_timesteps | 136000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.26 |\n",
+ "| explained_variance | -8.63 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 27199 |\n",
+ "| policy_loss | -1.78 |\n",
+ "| std | 0.916 |\n",
+ "| value_loss | 0.0857 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 24.7 |\n",
+ "| ep_rew_mean | -2.86 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 27300 |\n",
+ "| time_elapsed | 634 |\n",
+ "| total_timesteps | 136500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.24 |\n",
+ "| explained_variance | -41.8 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 27299 |\n",
+ "| policy_loss | 0.747 |\n",
+ "| std | 0.913 |\n",
+ "| value_loss | 0.0168 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 26.7 |\n",
+ "| ep_rew_mean | -3.07 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 27400 |\n",
+ "| time_elapsed | 636 |\n",
+ "| total_timesteps | 137000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.24 |\n",
+ "| explained_variance | -10.4 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 27399 |\n",
+ "| policy_loss | 0.642 |\n",
+ "| std | 0.913 |\n",
+ "| value_loss | 0.0117 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 27 |\n",
+ "| ep_rew_mean | -3.17 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 27500 |\n",
+ "| time_elapsed | 638 |\n",
+ "| total_timesteps | 137500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.25 |\n",
+ "| explained_variance | -0.721 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 27499 |\n",
+ "| policy_loss | 0.0641 |\n",
+ "| std | 0.915 |\n",
+ "| value_loss | 0.00459 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 27.3 |\n",
+ "| ep_rew_mean | -3.14 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 27600 |\n",
+ "| time_elapsed | 640 |\n",
+ "| total_timesteps | 138000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.24 |\n",
+ "| explained_variance | -2.1 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 27599 |\n",
+ "| policy_loss | -1.93 |\n",
+ "| std | 0.914 |\n",
+ "| value_loss | 0.0774 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 26.6 |\n",
+ "| ep_rew_mean | -2.94 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 27700 |\n",
+ "| time_elapsed | 643 |\n",
+ "| total_timesteps | 138500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.21 |\n",
+ "| explained_variance | 0.992 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 27699 |\n",
+ "| policy_loss | 0.826 |\n",
+ "| std | 0.91 |\n",
+ "| value_loss | 0.0189 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 24.7 |\n",
+ "| ep_rew_mean | -2.71 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 27800 |\n",
+ "| time_elapsed | 646 |\n",
+ "| total_timesteps | 139000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.21 |\n",
+ "| explained_variance | -0.207 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 27799 |\n",
+ "| policy_loss | 1.73 |\n",
+ "| std | 0.91 |\n",
+ "| value_loss | 0.0429 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 24.4 |\n",
+ "| ep_rew_mean | -2.82 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 27900 |\n",
+ "| time_elapsed | 648 |\n",
+ "| total_timesteps | 139500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
+ "| explained_variance | -59.6 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 27899 |\n",
+ "| policy_loss | 1.17 |\n",
+ "| std | 0.907 |\n",
+ "| value_loss | 0.0255 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 24.4 |\n",
+ "| ep_rew_mean | -2.87 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 28000 |\n",
+ "| time_elapsed | 650 |\n",
+ "| total_timesteps | 140000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.2 |\n",
+ "| explained_variance | -13.3 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 27999 |\n",
+ "| policy_loss | -1.4 |\n",
+ "| std | 0.908 |\n",
+ "| value_loss | 0.022 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 26.1 |\n",
+ "| ep_rew_mean | -3.14 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 28100 |\n",
+ "| time_elapsed | 652 |\n",
+ "| total_timesteps | 140500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.2 |\n",
+ "| explained_variance | -34.4 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 28099 |\n",
+ "| policy_loss | -3.05 |\n",
+ "| std | 0.908 |\n",
+ "| value_loss | 0.145 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 26.6 |\n",
+ "| ep_rew_mean | -3.21 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 28200 |\n",
+ "| time_elapsed | 655 |\n",
+ "| total_timesteps | 141000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
+ "| explained_variance | -4.58 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 28199 |\n",
+ "| policy_loss | -1.39 |\n",
+ "| std | 0.908 |\n",
+ "| value_loss | 0.039 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 28.9 |\n",
+ "| ep_rew_mean | -3.74 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 28300 |\n",
+ "| time_elapsed | 657 |\n",
+ "| total_timesteps | 141500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.18 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 28299 |\n",
+ "| policy_loss | -1.4 |\n",
+ "| std | 0.905 |\n",
+ "| value_loss | 0.0386 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 32.1 |\n",
+ "| ep_rew_mean | -4.39 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 28400 |\n",
+ "| time_elapsed | 660 |\n",
+ "| total_timesteps | 142000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.18 |\n",
+ "| explained_variance | -4.65 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 28399 |\n",
+ "| policy_loss | -2.57 |\n",
+ "| std | 0.907 |\n",
+ "| value_loss | 0.117 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 34.4 |\n",
+ "| ep_rew_mean | -4.91 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 28500 |\n",
+ "| time_elapsed | 662 |\n",
+ "| total_timesteps | 142500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.17 |\n",
+ "| explained_variance | 0.988 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 28499 |\n",
+ "| policy_loss | 0.262 |\n",
+ "| std | 0.905 |\n",
+ "| value_loss | 0.00413 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 34.7 |\n",
+ "| ep_rew_mean | -4.88 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 28600 |\n",
+ "| time_elapsed | 665 |\n",
+ "| total_timesteps | 143000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.16 |\n",
+ "| explained_variance | 0.992 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 28599 |\n",
+ "| policy_loss | 0.674 |\n",
+ "| std | 0.904 |\n",
+ "| value_loss | 0.0167 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 37.4 |\n",
+ "| ep_rew_mean | -5.37 |\n",
+ "| time/ | |\n",
+ "| fps | 215 |\n",
+ "| iterations | 28700 |\n",
+ "| time_elapsed | 667 |\n",
+ "| total_timesteps | 143500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.17 |\n",
+ "| explained_variance | -5 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 28699 |\n",
+ "| policy_loss | -0.149 |\n",
+ "| std | 0.905 |\n",
+ "| value_loss | 0.011 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 38.5 |\n",
+ "| ep_rew_mean | -5.55 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 28800 |\n",
+ "| time_elapsed | 669 |\n",
+ "| total_timesteps | 144000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
+ "| explained_variance | -0.433 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 28799 |\n",
+ "| policy_loss | -0.77 |\n",
+ "| std | 0.907 |\n",
+ "| value_loss | 0.0233 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 37.5 |\n",
+ "| ep_rew_mean | -5.47 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 28900 |\n",
+ "| time_elapsed | 673 |\n",
+ "| total_timesteps | 144500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.2 |\n",
+ "| explained_variance | 0.646 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 28899 |\n",
+ "| policy_loss | -1.16 |\n",
+ "| std | 0.911 |\n",
+ "| value_loss | 0.0178 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 35 |\n",
+ "| ep_rew_mean | -4.91 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 29000 |\n",
+ "| time_elapsed | 675 |\n",
+ "| total_timesteps | 145000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
+ "| explained_variance | 0.712 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 28999 |\n",
+ "| policy_loss | 0.899 |\n",
+ "| std | 0.909 |\n",
+ "| value_loss | 0.0109 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 34 |\n",
+ "| ep_rew_mean | -4.6 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 29100 |\n",
+ "| time_elapsed | 677 |\n",
+ "| total_timesteps | 145500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.18 |\n",
+ "| explained_variance | 0.942 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 29099 |\n",
+ "| policy_loss | 1.19 |\n",
+ "| std | 0.907 |\n",
+ "| value_loss | 0.0268 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 32.6 |\n",
+ "| ep_rew_mean | -4.24 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 29200 |\n",
+ "| time_elapsed | 679 |\n",
+ "| total_timesteps | 146000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
+ "| explained_variance | -11.8 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 29199 |\n",
+ "| policy_loss | -0.626 |\n",
+ "| std | 0.909 |\n",
+ "| value_loss | 0.00733 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 31.1 |\n",
+ "| ep_rew_mean | -3.93 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 29300 |\n",
+ "| time_elapsed | 682 |\n",
+ "| total_timesteps | 146500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.16 |\n",
+ "| explained_variance | -40.1 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 29299 |\n",
+ "| policy_loss | -0.387 |\n",
+ "| std | 0.906 |\n",
+ "| value_loss | 0.0469 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 30.6 |\n",
+ "| ep_rew_mean | -3.81 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 29400 |\n",
+ "| time_elapsed | 685 |\n",
+ "| total_timesteps | 147000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.16 |\n",
+ "| explained_variance | -14.2 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 29399 |\n",
+ "| policy_loss | -0.0407 |\n",
+ "| std | 0.904 |\n",
+ "| value_loss | 0.00367 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 30.1 |\n",
+ "| ep_rew_mean | -3.68 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 29500 |\n",
+ "| time_elapsed | 687 |\n",
+ "| total_timesteps | 147500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.13 |\n",
+ "| explained_variance | -3.21 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 29499 |\n",
+ "| policy_loss | -0.565 |\n",
+ "| std | 0.901 |\n",
+ "| value_loss | 0.00505 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 30.4 |\n",
+ "| ep_rew_mean | -3.72 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 29600 |\n",
+ "| time_elapsed | 689 |\n",
+ "| total_timesteps | 148000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.15 |\n",
+ "| explained_variance | -364 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 29599 |\n",
+ "| policy_loss | -0.779 |\n",
+ "| std | 0.904 |\n",
+ "| value_loss | 0.0386 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 31.9 |\n",
+ "| ep_rew_mean | -3.82 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 29700 |\n",
+ "| time_elapsed | 692 |\n",
+ "| total_timesteps | 148500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.16 |\n",
+ "| explained_variance | -1.76 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 29699 |\n",
+ "| policy_loss | -1.5 |\n",
+ "| std | 0.905 |\n",
+ "| value_loss | 0.0229 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 33.1 |\n",
+ "| ep_rew_mean | -3.91 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 29800 |\n",
+ "| time_elapsed | 694 |\n",
+ "| total_timesteps | 149000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.15 |\n",
+ "| explained_variance | -1.26 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 29799 |\n",
+ "| policy_loss | 0.248 |\n",
+ "| std | 0.904 |\n",
+ "| value_loss | 0.00225 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 32.5 |\n",
+ "| ep_rew_mean | -3.8 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 29900 |\n",
+ "| time_elapsed | 697 |\n",
+ "| total_timesteps | 149500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.16 |\n",
+ "| explained_variance | -0.57 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 29899 |\n",
+ "| policy_loss | -3.42 |\n",
+ "| std | 0.905 |\n",
+ "| value_loss | 0.154 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 34.1 |\n",
+ "| ep_rew_mean | -3.98 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 30000 |\n",
+ "| time_elapsed | 699 |\n",
+ "| total_timesteps | 150000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.17 |\n",
+ "| explained_variance | -16 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 29999 |\n",
+ "| policy_loss | -1.03 |\n",
+ "| std | 0.907 |\n",
+ "| value_loss | 0.0146 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 34.4 |\n",
+ "| ep_rew_mean | -3.92 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 30100 |\n",
+ "| time_elapsed | 702 |\n",
+ "| total_timesteps | 150500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.16 |\n",
+ "| explained_variance | -41 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 30099 |\n",
+ "| policy_loss | -1.26 |\n",
+ "| std | 0.905 |\n",
+ "| value_loss | 0.0226 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 36.5 |\n",
+ "| ep_rew_mean | -4.12 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 30200 |\n",
+ "| time_elapsed | 704 |\n",
+ "| total_timesteps | 151000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.17 |\n",
+ "| explained_variance | -0.415 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 30199 |\n",
+ "| policy_loss | -2.32 |\n",
+ "| std | 0.906 |\n",
+ "| value_loss | 0.0702 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 34.5 |\n",
+ "| ep_rew_mean | -4.03 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 30300 |\n",
+ "| time_elapsed | 706 |\n",
+ "| total_timesteps | 151500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.16 |\n",
+ "| explained_variance | -7.4 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 30299 |\n",
+ "| policy_loss | 3.43 |\n",
+ "| std | 0.906 |\n",
+ "| value_loss | 0.095 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 32.2 |\n",
+ "| ep_rew_mean | -3.73 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 30400 |\n",
+ "| time_elapsed | 709 |\n",
+ "| total_timesteps | 152000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.21 |\n",
+ "| explained_variance | -46.4 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 30399 |\n",
+ "| policy_loss | 1.71 |\n",
+ "| std | 0.912 |\n",
+ "| value_loss | 0.0525 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 29.9 |\n",
+ "| ep_rew_mean | -3.48 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 30500 |\n",
+ "| time_elapsed | 712 |\n",
+ "| total_timesteps | 152500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.2 |\n",
+ "| explained_variance | -10.5 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 30499 |\n",
+ "| policy_loss | 82.9 |\n",
+ "| std | 0.912 |\n",
+ "| value_loss | 77.1 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 29.5 |\n",
+ "| ep_rew_mean | -3.36 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 30600 |\n",
+ "| time_elapsed | 714 |\n",
+ "| total_timesteps | 153000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
+ "| explained_variance | -9.28 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 30599 |\n",
+ "| policy_loss | -1.65 |\n",
+ "| std | 0.912 |\n",
+ "| value_loss | 0.0547 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 24 |\n",
+ "| ep_rew_mean | -2.71 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 30700 |\n",
+ "| time_elapsed | 716 |\n",
+ "| total_timesteps | 153500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
+ "| explained_variance | 0.204 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 30699 |\n",
+ "| policy_loss | 71.1 |\n",
+ "| std | 0.912 |\n",
+ "| value_loss | 71.5 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.5 |\n",
+ "| ep_rew_mean | -2.2 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 30800 |\n",
+ "| time_elapsed | 719 |\n",
+ "| total_timesteps | 154000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.18 |\n",
+ "| explained_variance | -10.6 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 30799 |\n",
+ "| policy_loss | -2.74 |\n",
+ "| std | 0.909 |\n",
+ "| value_loss | 0.103 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.1 |\n",
+ "| ep_rew_mean | -2.1 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 30900 |\n",
+ "| time_elapsed | 721 |\n",
+ "| total_timesteps | 154500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.17 |\n",
+ "| explained_variance | 0.33 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 30899 |\n",
+ "| policy_loss | 10.6 |\n",
+ "| std | 0.908 |\n",
+ "| value_loss | 12 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 22.1 |\n",
+ "| ep_rew_mean | -2.23 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 31000 |\n",
+ "| time_elapsed | 724 |\n",
+ "| total_timesteps | 155000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.14 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 30999 |\n",
+ "| policy_loss | 0.0295 |\n",
+ "| std | 0.904 |\n",
+ "| value_loss | 0.00765 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.4 |\n",
+ "| ep_rew_mean | -2.13 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 31100 |\n",
+ "| time_elapsed | 726 |\n",
+ "| total_timesteps | 155500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.13 |\n",
+ "| explained_variance | -11.4 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 31099 |\n",
+ "| policy_loss | 0.0987 |\n",
+ "| std | 0.903 |\n",
+ "| value_loss | 0.00813 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 22.6 |\n",
+ "| ep_rew_mean | -2.32 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 31200 |\n",
+ "| time_elapsed | 728 |\n",
+ "| total_timesteps | 156000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.12 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 31199 |\n",
+ "| policy_loss | -0.126 |\n",
+ "| std | 0.902 |\n",
+ "| value_loss | 0.0016 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 20.8 |\n",
+ "| ep_rew_mean | -2.13 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 31300 |\n",
+ "| time_elapsed | 731 |\n",
+ "| total_timesteps | 156500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.15 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 31299 |\n",
+ "| policy_loss | -2.48 |\n",
+ "| std | 0.905 |\n",
+ "| value_loss | 0.106 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 20.4 |\n",
+ "| ep_rew_mean | -2.06 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 31400 |\n",
+ "| time_elapsed | 733 |\n",
+ "| total_timesteps | 157000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.16 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 31399 |\n",
+ "| policy_loss | -0.531 |\n",
+ "| std | 0.906 |\n",
+ "| value_loss | 0.00477 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.8 |\n",
+ "| ep_rew_mean | -2.34 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 31500 |\n",
+ "| time_elapsed | 736 |\n",
+ "| total_timesteps | 157500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 31499 |\n",
+ "| policy_loss | -0.867 |\n",
+ "| std | 0.909 |\n",
+ "| value_loss | 0.022 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 22.4 |\n",
+ "| ep_rew_mean | -2.54 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 31600 |\n",
+ "| time_elapsed | 738 |\n",
+ "| total_timesteps | 158000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.17 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 31599 |\n",
+ "| policy_loss | -2.59 |\n",
+ "| std | 0.908 |\n",
+ "| value_loss | 0.109 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 24.5 |\n",
+ "| ep_rew_mean | -2.79 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 31700 |\n",
+ "| time_elapsed | 741 |\n",
+ "| total_timesteps | 158500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.18 |\n",
+ "| explained_variance | -0.925 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 31699 |\n",
+ "| policy_loss | 0.322 |\n",
+ "| std | 0.909 |\n",
+ "| value_loss | 0.00291 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 27.6 |\n",
+ "| ep_rew_mean | -3.16 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 31800 |\n",
+ "| time_elapsed | 743 |\n",
+ "| total_timesteps | 159000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
+ "| explained_variance | -6.1 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 31799 |\n",
+ "| policy_loss | -0.185 |\n",
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+ "| value_loss | 0.000914 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 30 |\n",
+ "| ep_rew_mean | -3.45 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 31900 |\n",
+ "| time_elapsed | 745 |\n",
+ "| total_timesteps | 159500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.21 |\n",
+ "| explained_variance | 0.627 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 31899 |\n",
+ "| policy_loss | -0.0331 |\n",
+ "| std | 0.913 |\n",
+ "| value_loss | 0.00058 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 32.4 |\n",
+ "| ep_rew_mean | -3.76 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 32000 |\n",
+ "| time_elapsed | 748 |\n",
+ "| total_timesteps | 160000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.2 |\n",
+ "| explained_variance | -0.0635 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 31999 |\n",
+ "| policy_loss | 0.838 |\n",
+ "| std | 0.912 |\n",
+ "| value_loss | 0.0116 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 31.7 |\n",
+ "| ep_rew_mean | -3.63 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 32100 |\n",
+ "| time_elapsed | 751 |\n",
+ "| total_timesteps | 160500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
+ "| explained_variance | -27.1 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 32099 |\n",
+ "| policy_loss | 0.601 |\n",
+ "| std | 0.91 |\n",
+ "| value_loss | 0.00816 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 30.5 |\n",
+ "| ep_rew_mean | -3.28 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 32200 |\n",
+ "| time_elapsed | 753 |\n",
+ "| total_timesteps | 161000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.21 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 32199 |\n",
+ "| policy_loss | 0.0595 |\n",
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+ "| value_loss | 0.00292 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 27.8 |\n",
+ "| ep_rew_mean | -2.87 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 32300 |\n",
+ "| time_elapsed | 755 |\n",
+ "| total_timesteps | 161500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 32299 |\n",
+ "| policy_loss | -1.53 |\n",
+ "| std | 0.912 |\n",
+ "| value_loss | 0.0333 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 20.1 |\n",
+ "| ep_rew_mean | -1.95 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 32400 |\n",
+ "| time_elapsed | 757 |\n",
+ "| total_timesteps | 162000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.17 |\n",
+ "| explained_variance | -5.1 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 32399 |\n",
+ "| policy_loss | -1.26 |\n",
+ "| std | 0.91 |\n",
+ "| value_loss | 0.0261 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 19.5 |\n",
+ "| ep_rew_mean | -1.91 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 32500 |\n",
+ "| time_elapsed | 760 |\n",
+ "| total_timesteps | 162500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.18 |\n",
+ "| explained_variance | -3.01 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 32499 |\n",
+ "| policy_loss | 0.0395 |\n",
+ "| std | 0.911 |\n",
+ "| value_loss | 0.00248 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 20.7 |\n",
+ "| ep_rew_mean | -2.18 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 32600 |\n",
+ "| time_elapsed | 762 |\n",
+ "| total_timesteps | 163000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.18 |\n",
+ "| explained_variance | -84.7 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 32599 |\n",
+ "| policy_loss | -1.51 |\n",
+ "| std | 0.911 |\n",
+ "| value_loss | 0.0319 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.5 |\n",
+ "| ep_rew_mean | -2.35 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 32700 |\n",
+ "| time_elapsed | 765 |\n",
+ "| total_timesteps | 163500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.14 |\n",
+ "| explained_variance | -1.32 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 32699 |\n",
+ "| policy_loss | -1.37 |\n",
+ "| std | 0.907 |\n",
+ "| value_loss | 0.0274 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.8 |\n",
+ "| ep_rew_mean | -2.44 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 32800 |\n",
+ "| time_elapsed | 767 |\n",
+ "| total_timesteps | 164000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.15 |\n",
+ "| explained_variance | -63.2 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 32799 |\n",
+ "| policy_loss | 1.64 |\n",
+ "| std | 0.907 |\n",
+ "| value_loss | 0.0403 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 23.6 |\n",
+ "| ep_rew_mean | -2.65 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 32900 |\n",
+ "| time_elapsed | 769 |\n",
+ "| total_timesteps | 164500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.15 |\n",
+ "| explained_variance | -0.602 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 32899 |\n",
+ "| policy_loss | 65.8 |\n",
+ "| std | 0.907 |\n",
+ "| value_loss | 56.5 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 24.2 |\n",
+ "| ep_rew_mean | -2.65 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 33000 |\n",
+ "| time_elapsed | 771 |\n",
+ "| total_timesteps | 165000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.15 |\n",
+ "| explained_variance | 0.499 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 32999 |\n",
+ "| policy_loss | 58.8 |\n",
+ "| std | 0.907 |\n",
+ "| value_loss | 39.9 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.6 |\n",
+ "| ep_rew_mean | -2.2 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 33100 |\n",
+ "| time_elapsed | 773 |\n",
+ "| total_timesteps | 165500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
+ "| explained_variance | -0.745 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 33099 |\n",
+ "| policy_loss | -2.53 |\n",
+ "| std | 0.913 |\n",
+ "| value_loss | 0.0953 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.6 |\n",
+ "| ep_rew_mean | -2.16 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 33200 |\n",
+ "| time_elapsed | 776 |\n",
+ "| total_timesteps | 166000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
+ "| explained_variance | -3.39 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 33199 |\n",
+ "| policy_loss | 0.465 |\n",
+ "| std | 0.914 |\n",
+ "| value_loss | 0.00348 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 22.1 |\n",
+ "| ep_rew_mean | -2.26 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 33300 |\n",
+ "| time_elapsed | 778 |\n",
+ "| total_timesteps | 166500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
+ "| explained_variance | -4.91 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 33299 |\n",
+ "| policy_loss | 0.256 |\n",
+ "| std | 0.914 |\n",
+ "| value_loss | 0.00234 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.9 |\n",
+ "| ep_rew_mean | -2.3 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 33400 |\n",
+ "| time_elapsed | 780 |\n",
+ "| total_timesteps | 167000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.2 |\n",
+ "| explained_variance | -56.7 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 33399 |\n",
+ "| policy_loss | -0.6 |\n",
+ "| std | 0.915 |\n",
+ "| value_loss | 0.023 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.4 |\n",
+ "| ep_rew_mean | -2.33 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 33500 |\n",
+ "| time_elapsed | 782 |\n",
+ "| total_timesteps | 167500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.14 |\n",
+ "| explained_variance | -0.972 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 33499 |\n",
+ "| policy_loss | -1.6 |\n",
+ "| std | 0.908 |\n",
+ "| value_loss | 0.033 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 23.3 |\n",
+ "| ep_rew_mean | -2.62 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 33600 |\n",
+ "| time_elapsed | 784 |\n",
+ "| total_timesteps | 168000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.17 |\n",
+ "| explained_variance | -0.332 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 33599 |\n",
+ "| policy_loss | -3.35 |\n",
+ "| std | 0.911 |\n",
+ "| value_loss | 0.155 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 22.5 |\n",
+ "| ep_rew_mean | -2.61 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 33700 |\n",
+ "| time_elapsed | 787 |\n",
+ "| total_timesteps | 168500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.2 |\n",
+ "| explained_variance | 0.0505 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 33699 |\n",
+ "| policy_loss | 27.6 |\n",
+ "| std | 0.916 |\n",
+ "| value_loss | 24.1 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.4 |\n",
+ "| ep_rew_mean | -2.46 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 33800 |\n",
+ "| time_elapsed | 789 |\n",
+ "| total_timesteps | 169000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.18 |\n",
+ "| explained_variance | 0.133 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 33799 |\n",
+ "| policy_loss | -1.41 |\n",
+ "| std | 0.912 |\n",
+ "| value_loss | 0.0282 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 20.7 |\n",
+ "| ep_rew_mean | -2.35 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 33900 |\n",
+ "| time_elapsed | 792 |\n",
+ "| total_timesteps | 169500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.18 |\n",
+ "| explained_variance | -0.0856 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 33899 |\n",
+ "| policy_loss | -0.339 |\n",
+ "| std | 0.913 |\n",
+ "| value_loss | 0.00213 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 17.7 |\n",
+ "| ep_rew_mean | -1.91 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 34000 |\n",
+ "| time_elapsed | 794 |\n",
+ "| total_timesteps | 170000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.19 |\n",
+ "| explained_variance | 0.412 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 33999 |\n",
+ "| policy_loss | -2.75 |\n",
+ "| std | 0.914 |\n",
+ "| value_loss | 0.101 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 16.7 |\n",
+ "| ep_rew_mean | -1.71 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 34100 |\n",
+ "| time_elapsed | 796 |\n",
+ "| total_timesteps | 170500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.16 |\n",
+ "| explained_variance | -0.268 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 34099 |\n",
+ "| policy_loss | 30.5 |\n",
+ "| std | 0.91 |\n",
+ "| value_loss | 24.9 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 12.1 |\n",
+ "| ep_rew_mean | -1.17 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 34200 |\n",
+ "| time_elapsed | 798 |\n",
+ "| total_timesteps | 171000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.13 |\n",
+ "| explained_variance | -0.133 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 34199 |\n",
+ "| policy_loss | 18.1 |\n",
+ "| std | 0.908 |\n",
+ "| value_loss | 6.21 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 11.1 |\n",
+ "| ep_rew_mean | -1.04 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 34300 |\n",
+ "| time_elapsed | 801 |\n",
+ "| total_timesteps | 171500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.11 |\n",
+ "| explained_variance | 0.0785 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 34299 |\n",
+ "| policy_loss | 19.5 |\n",
+ "| std | 0.904 |\n",
+ "| value_loss | 19.1 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 12.2 |\n",
+ "| ep_rew_mean | -1.14 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 34400 |\n",
+ "| time_elapsed | 803 |\n",
+ "| total_timesteps | 172000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.09 |\n",
+ "| explained_variance | -0.0422 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 34399 |\n",
+ "| policy_loss | 37.4 |\n",
+ "| std | 0.902 |\n",
+ "| value_loss | 27.1 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 11.9 |\n",
+ "| ep_rew_mean | -1.1 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 34500 |\n",
+ "| time_elapsed | 805 |\n",
+ "| total_timesteps | 172500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.07 |\n",
+ "| explained_variance | -7.39 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 34499 |\n",
+ "| policy_loss | -1.71 |\n",
+ "| std | 0.898 |\n",
+ "| value_loss | 0.0466 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 10.7 |\n",
+ "| ep_rew_mean | -0.966 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 34600 |\n",
+ "| time_elapsed | 807 |\n",
+ "| total_timesteps | 173000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.06 |\n",
+ "| explained_variance | 0.215 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 34599 |\n",
+ "| policy_loss | 10.6 |\n",
+ "| std | 0.897 |\n",
+ "| value_loss | 6.51 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 9.18 |\n",
+ "| ep_rew_mean | -0.818 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 34700 |\n",
+ "| time_elapsed | 810 |\n",
+ "| total_timesteps | 173500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.03 |\n",
+ "| explained_variance | -3.54 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 34699 |\n",
+ "| policy_loss | 17.6 |\n",
+ "| std | 0.892 |\n",
+ "| value_loss | 5.16 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 8.39 |\n",
+ "| ep_rew_mean | -0.726 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 34800 |\n",
+ "| time_elapsed | 812 |\n",
+ "| total_timesteps | 174000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -9.01 |\n",
+ "| explained_variance | 0.0827 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 34799 |\n",
+ "| policy_loss | 12.8 |\n",
+ "| std | 0.891 |\n",
+ "| value_loss | 2.64 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 8.82 |\n",
+ "| ep_rew_mean | -0.773 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 34900 |\n",
+ "| time_elapsed | 815 |\n",
+ "| total_timesteps | 174500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.98 |\n",
+ "| explained_variance | -0.858 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 34899 |\n",
+ "| policy_loss | -3.64 |\n",
+ "| std | 0.888 |\n",
+ "| value_loss | 0.237 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 9.03 |\n",
+ "| ep_rew_mean | -0.823 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 35000 |\n",
+ "| time_elapsed | 817 |\n",
+ "| total_timesteps | 175000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.94 |\n",
+ "| explained_variance | -9.09 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 34999 |\n",
+ "| policy_loss | -1.61 |\n",
+ "| std | 0.883 |\n",
+ "| value_loss | 0.0613 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 8.99 |\n",
+ "| ep_rew_mean | -0.794 |\n",
+ "| time/ | |\n",
+ "| fps | 214 |\n",
+ "| iterations | 35100 |\n",
+ "| time_elapsed | 819 |\n",
+ "| total_timesteps | 175500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.93 |\n",
+ "| explained_variance | 0.0769 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 35099 |\n",
+ "| policy_loss | -0.339 |\n",
+ "| std | 0.883 |\n",
+ "| value_loss | 0.0132 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 8.18 |\n",
+ "| ep_rew_mean | -0.696 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 35200 |\n",
+ "| time_elapsed | 822 |\n",
+ "| total_timesteps | 176000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.92 |\n",
+ "| explained_variance | 0.591 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 35199 |\n",
+ "| policy_loss | 6.37 |\n",
+ "| std | 0.881 |\n",
+ "| value_loss | 1.99 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 8.56 |\n",
+ "| ep_rew_mean | -0.749 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 35300 |\n",
+ "| time_elapsed | 825 |\n",
+ "| total_timesteps | 176500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.9 |\n",
+ "| explained_variance | 0.67 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 35299 |\n",
+ "| policy_loss | 0.123 |\n",
+ "| std | 0.879 |\n",
+ "| value_loss | 0.000809 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 9.49 |\n",
+ "| ep_rew_mean | -0.878 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 35400 |\n",
+ "| time_elapsed | 828 |\n",
+ "| total_timesteps | 177000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.9 |\n",
+ "| explained_variance | -1.04 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 35399 |\n",
+ "| policy_loss | 39.2 |\n",
+ "| std | 0.878 |\n",
+ "| value_loss | 25.5 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 9.72 |\n",
+ "| ep_rew_mean | -0.906 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 35500 |\n",
+ "| time_elapsed | 830 |\n",
+ "| total_timesteps | 177500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.9 |\n",
+ "| explained_variance | -0.813 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 35499 |\n",
+ "| policy_loss | 18.4 |\n",
+ "| std | 0.878 |\n",
+ "| value_loss | 13.8 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 11.4 |\n",
+ "| ep_rew_mean | -1.05 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 35600 |\n",
+ "| time_elapsed | 832 |\n",
+ "| total_timesteps | 178000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.87 |\n",
+ "| explained_variance | -7.13 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 35599 |\n",
+ "| policy_loss | -1 |\n",
+ "| std | 0.873 |\n",
+ "| value_loss | 0.0155 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 14.7 |\n",
+ "| ep_rew_mean | -1.42 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 35700 |\n",
+ "| time_elapsed | 834 |\n",
+ "| total_timesteps | 178500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.88 |\n",
+ "| explained_variance | -7.62 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 35699 |\n",
+ "| policy_loss | -0.701 |\n",
+ "| std | 0.876 |\n",
+ "| value_loss | 0.00857 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 16.3 |\n",
+ "| ep_rew_mean | -1.65 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 35800 |\n",
+ "| time_elapsed | 836 |\n",
+ "| total_timesteps | 179000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.88 |\n",
+ "| explained_variance | -12.1 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 35799 |\n",
+ "| policy_loss | 2.78 |\n",
+ "| std | 0.876 |\n",
+ "| value_loss | 0.124 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 16.1 |\n",
+ "| ep_rew_mean | -1.65 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 35900 |\n",
+ "| time_elapsed | 839 |\n",
+ "| total_timesteps | 179500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.87 |\n",
+ "| explained_variance | 0.203 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 35899 |\n",
+ "| policy_loss | -2.93 |\n",
+ "| std | 0.875 |\n",
+ "| value_loss | 0.133 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 15.9 |\n",
+ "| ep_rew_mean | -1.6 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 36000 |\n",
+ "| time_elapsed | 841 |\n",
+ "| total_timesteps | 180000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.86 |\n",
+ "| explained_variance | -56.9 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 35999 |\n",
+ "| policy_loss | -1.15 |\n",
+ "| std | 0.874 |\n",
+ "| value_loss | 0.0208 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 18.4 |\n",
+ "| ep_rew_mean | -1.85 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 36100 |\n",
+ "| time_elapsed | 844 |\n",
+ "| total_timesteps | 180500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.85 |\n",
+ "| explained_variance | -2.69 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 36099 |\n",
+ "| policy_loss | 0.122 |\n",
+ "| std | 0.872 |\n",
+ "| value_loss | 0.00112 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 22.1 |\n",
+ "| ep_rew_mean | -2.24 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 36200 |\n",
+ "| time_elapsed | 846 |\n",
+ "| total_timesteps | 181000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.85 |\n",
+ "| explained_variance | -0.413 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 36199 |\n",
+ "| policy_loss | 0.17 |\n",
+ "| std | 0.873 |\n",
+ "| value_loss | 0.00142 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.7 |\n",
+ "| ep_rew_mean | -2.19 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 36300 |\n",
+ "| time_elapsed | 848 |\n",
+ "| total_timesteps | 181500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.85 |\n",
+ "| explained_variance | -0.618 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 36299 |\n",
+ "| policy_loss | 34.1 |\n",
+ "| std | 0.872 |\n",
+ "| value_loss | 20.6 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 17.8 |\n",
+ "| ep_rew_mean | -1.82 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 36400 |\n",
+ "| time_elapsed | 851 |\n",
+ "| total_timesteps | 182000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.86 |\n",
+ "| explained_variance | -0.0238 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 36399 |\n",
+ "| policy_loss | -2.26 |\n",
+ "| std | 0.872 |\n",
+ "| value_loss | 0.0614 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 11.5 |\n",
+ "| ep_rew_mean | -1.08 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 36500 |\n",
+ "| time_elapsed | 853 |\n",
+ "| total_timesteps | 182500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.84 |\n",
+ "| explained_variance | -9.32 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 36499 |\n",
+ "| policy_loss | 33 |\n",
+ "| std | 0.871 |\n",
+ "| value_loss | 19.1 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 10.1 |\n",
+ "| ep_rew_mean | -0.943 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 36600 |\n",
+ "| time_elapsed | 856 |\n",
+ "| total_timesteps | 183000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.84 |\n",
+ "| explained_variance | -2.44 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 36599 |\n",
+ "| policy_loss | -1.35 |\n",
+ "| std | 0.87 |\n",
+ "| value_loss | 0.0543 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 8.22 |\n",
+ "| ep_rew_mean | -0.707 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 36700 |\n",
+ "| time_elapsed | 858 |\n",
+ "| total_timesteps | 183500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.79 |\n",
+ "| explained_variance | 0.118 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 36699 |\n",
+ "| policy_loss | 7.84 |\n",
+ "| std | 0.864 |\n",
+ "| value_loss | 1.45 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 7.5 |\n",
+ "| ep_rew_mean | -0.65 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 36800 |\n",
+ "| time_elapsed | 860 |\n",
+ "| total_timesteps | 184000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.8 |\n",
+ "| explained_variance | 0.974 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 36799 |\n",
+ "| policy_loss | 34.6 |\n",
+ "| std | 0.866 |\n",
+ "| value_loss | 15.5 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 8.05 |\n",
+ "| ep_rew_mean | -0.718 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 36900 |\n",
+ "| time_elapsed | 862 |\n",
+ "| total_timesteps | 184500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.77 |\n",
+ "| explained_variance | -2.59 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 36899 |\n",
+ "| policy_loss | -0.682 |\n",
+ "| std | 0.862 |\n",
+ "| value_loss | 0.0374 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 7.38 |\n",
+ "| ep_rew_mean | -0.632 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 37000 |\n",
+ "| time_elapsed | 865 |\n",
+ "| total_timesteps | 185000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.76 |\n",
+ "| explained_variance | -3.99 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 36999 |\n",
+ "| policy_loss | 2.48 |\n",
+ "| std | 0.861 |\n",
+ "| value_loss | 1.02 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.84 |\n",
+ "| ep_rew_mean | -0.57 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 37100 |\n",
+ "| time_elapsed | 868 |\n",
+ "| total_timesteps | 185500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.74 |\n",
+ "| explained_variance | -0.648 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 37099 |\n",
+ "| policy_loss | -0.939 |\n",
+ "| std | 0.86 |\n",
+ "| value_loss | 0.028 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 7.16 |\n",
+ "| ep_rew_mean | -0.607 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 37200 |\n",
+ "| time_elapsed | 871 |\n",
+ "| total_timesteps | 186000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.71 |\n",
+ "| explained_variance | -0.928 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 37199 |\n",
+ "| policy_loss | -2.97 |\n",
+ "| std | 0.857 |\n",
+ "| value_loss | 0.156 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.12 |\n",
+ "| ep_rew_mean | -0.537 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 37300 |\n",
+ "| time_elapsed | 873 |\n",
+ "| total_timesteps | 186500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.73 |\n",
+ "| explained_variance | -24.5 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 37299 |\n",
+ "| policy_loss | 8.62 |\n",
+ "| std | 0.859 |\n",
+ "| value_loss | 1.4 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.33 |\n",
+ "| ep_rew_mean | -0.552 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 37400 |\n",
+ "| time_elapsed | 875 |\n",
+ "| total_timesteps | 187000 |\n",
+ "| train/ | |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 37399 |\n",
+ "| policy_loss | -0.707 |\n",
+ "| std | 0.857 |\n",
+ "| value_loss | 0.0155 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.49 |\n",
+ "| ep_rew_mean | -0.577 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 37500 |\n",
+ "| time_elapsed | 878 |\n",
+ "| total_timesteps | 187500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.69 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 37499 |\n",
+ "| policy_loss | 5.95 |\n",
+ "| std | 0.854 |\n",
+ "| value_loss | 0.698 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.37 |\n",
+ "| ep_rew_mean | -0.555 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 37600 |\n",
+ "| time_elapsed | 880 |\n",
+ "| total_timesteps | 188000 |\n",
+ "| train/ | |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 37599 |\n",
+ "| policy_loss | 0.693 |\n",
+ "| std | 0.853 |\n",
+ "| value_loss | 0.129 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.37 |\n",
+ "| ep_rew_mean | -0.542 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 37700 |\n",
+ "| time_elapsed | 883 |\n",
+ "| total_timesteps | 188500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.68 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 37699 |\n",
+ "| policy_loss | -2.09 |\n",
+ "| std | 0.853 |\n",
+ "| value_loss | 0.0667 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 7.17 |\n",
+ "| ep_rew_mean | -0.611 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 37800 |\n",
+ "| time_elapsed | 885 |\n",
+ "| total_timesteps | 189000 |\n",
+ "| train/ | |\n",
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+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | -1.87 |\n",
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+ "| value_loss | 0.0522 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 7.19 |\n",
+ "| ep_rew_mean | -0.625 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 37900 |\n",
+ "| time_elapsed | 887 |\n",
+ "| total_timesteps | 189500 |\n",
+ "| train/ | |\n",
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+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | 5.17 |\n",
+ "| std | 0.848 |\n",
+ "| value_loss | 0.386 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.54 |\n",
+ "| ep_rew_mean | -0.557 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 38000 |\n",
+ "| time_elapsed | 890 |\n",
+ "| total_timesteps | 190000 |\n",
+ "| train/ | |\n",
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+ "| policy_loss | 1.16 |\n",
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+ "| value_loss | 0.0336 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.48 |\n",
+ "| ep_rew_mean | -0.553 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 38100 |\n",
+ "| time_elapsed | 892 |\n",
+ "| total_timesteps | 190500 |\n",
+ "| train/ | |\n",
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+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | -1.62 |\n",
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+ "| value_loss | 0.062 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.13 |\n",
+ "| ep_rew_mean | -0.539 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 38200 |\n",
+ "| time_elapsed | 894 |\n",
+ "| total_timesteps | 191000 |\n",
+ "| train/ | |\n",
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+ "| policy_loss | 5.95 |\n",
+ "| std | 0.842 |\n",
+ "| value_loss | 1.93 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 7.32 |\n",
+ "| ep_rew_mean | -0.713 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 38300 |\n",
+ "| time_elapsed | 896 |\n",
+ "| total_timesteps | 191500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.58 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 38299 |\n",
+ "| policy_loss | -1.45 |\n",
+ "| std | 0.842 |\n",
+ "| value_loss | 0.0577 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 9.37 |\n",
+ "| ep_rew_mean | -0.952 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 38400 |\n",
+ "| time_elapsed | 899 |\n",
+ "| total_timesteps | 192000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.59 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 38399 |\n",
+ "| policy_loss | -4.58 |\n",
+ "| std | 0.842 |\n",
+ "| value_loss | 0.306 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.36 |\n",
+ "| ep_rew_mean | -0.545 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 38500 |\n",
+ "| time_elapsed | 901 |\n",
+ "| total_timesteps | 192500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.58 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 38499 |\n",
+ "| policy_loss | -0.731 |\n",
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+ "| value_loss | 0.0341 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 5.75 |\n",
+ "| ep_rew_mean | -0.496 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 38600 |\n",
+ "| time_elapsed | 904 |\n",
+ "| total_timesteps | 193000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.59 |\n",
+ "| explained_variance | -25.8 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 38599 |\n",
+ "| policy_loss | 5.09 |\n",
+ "| std | 0.84 |\n",
+ "| value_loss | 0.549 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 5.99 |\n",
+ "| ep_rew_mean | -0.514 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 38700 |\n",
+ "| time_elapsed | 906 |\n",
+ "| total_timesteps | 193500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.59 |\n",
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+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | -1.23 |\n",
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+ "| value_loss | 0.0226 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.44 |\n",
+ "| ep_rew_mean | -0.608 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 38800 |\n",
+ "| time_elapsed | 908 |\n",
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+ "| train/ | |\n",
+ "| entropy_loss | -8.57 |\n",
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+ "| policy_loss | -1.68 |\n",
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+ "| value_loss | 0.037 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
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+ "| ep_rew_mean | -0.626 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 38900 |\n",
+ "| time_elapsed | 910 |\n",
+ "| total_timesteps | 194500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.55 |\n",
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+ "| n_updates | 38899 |\n",
+ "| policy_loss | -1.68 |\n",
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+ "| value_loss | 0.0596 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 7.39 |\n",
+ "| ep_rew_mean | -0.694 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 39000 |\n",
+ "| time_elapsed | 912 |\n",
+ "| total_timesteps | 195000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.54 |\n",
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+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | 15 |\n",
+ "| std | 0.836 |\n",
+ "| value_loss | 3.82 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 7.82 |\n",
+ "| ep_rew_mean | -0.791 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 39100 |\n",
+ "| time_elapsed | 915 |\n",
+ "| total_timesteps | 195500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.55 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 39099 |\n",
+ "| policy_loss | -2.78 |\n",
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+ "| value_loss | 0.112 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
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+ "| ep_rew_mean | -0.523 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 39200 |\n",
+ "| time_elapsed | 918 |\n",
+ "| total_timesteps | 196000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.53 |\n",
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+ "| policy_loss | -0.999 |\n",
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+ "| value_loss | 0.0289 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.81 |\n",
+ "| ep_rew_mean | -0.627 |\n",
+ "| time/ | |\n",
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+ "| iterations | 39300 |\n",
+ "| time_elapsed | 920 |\n",
+ "| total_timesteps | 196500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.53 |\n",
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+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | -4.89 |\n",
+ "| std | 0.834 |\n",
+ "| value_loss | 0.411 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 8.18 |\n",
+ "| ep_rew_mean | -0.826 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 39400 |\n",
+ "| time_elapsed | 922 |\n",
+ "| total_timesteps | 197000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.54 |\n",
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+ "| policy_loss | 0.375 |\n",
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+ "| value_loss | 0.0048 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 8.39 |\n",
+ "| ep_rew_mean | -0.778 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 39500 |\n",
+ "| time_elapsed | 924 |\n",
+ "| total_timesteps | 197500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.53 |\n",
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+ "| policy_loss | 4.76 |\n",
+ "| std | 0.834 |\n",
+ "| value_loss | 0.424 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.32 |\n",
+ "| ep_rew_mean | -0.54 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 39600 |\n",
+ "| time_elapsed | 926 |\n",
+ "| total_timesteps | 198000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.48 |\n",
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+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | 1.18 |\n",
+ "| std | 0.827 |\n",
+ "| value_loss | 0.0633 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 7.89 |\n",
+ "| ep_rew_mean | -0.732 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 39700 |\n",
+ "| time_elapsed | 929 |\n",
+ "| total_timesteps | 198500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.49 |\n",
+ "| explained_variance | -6.55 |\n",
+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | -2.89 |\n",
+ "| std | 0.829 |\n",
+ "| value_loss | 0.168 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 8.49 |\n",
+ "| ep_rew_mean | -0.869 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 39800 |\n",
+ "| time_elapsed | 932 |\n",
+ "| total_timesteps | 199000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.51 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 39799 |\n",
+ "| policy_loss | 5.14 |\n",
+ "| std | 0.832 |\n",
+ "| value_loss | 2.83 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.86 |\n",
+ "| ep_rew_mean | -0.724 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 39900 |\n",
+ "| time_elapsed | 934 |\n",
+ "| total_timesteps | 199500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.51 |\n",
+ "| explained_variance | -3.38 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 39899 |\n",
+ "| policy_loss | -3.47 |\n",
+ "| std | 0.832 |\n",
+ "| value_loss | 0.298 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.14 |\n",
+ "| ep_rew_mean | -0.574 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 40000 |\n",
+ "| time_elapsed | 936 |\n",
+ "| total_timesteps | 200000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.52 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 39999 |\n",
+ "| policy_loss | 14 |\n",
+ "| std | 0.832 |\n",
+ "| value_loss | 4.51 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 8.41 |\n",
+ "| ep_rew_mean | -0.915 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 40100 |\n",
+ "| time_elapsed | 938 |\n",
+ "| total_timesteps | 200500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.53 |\n",
+ "| explained_variance | -28.2 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 40099 |\n",
+ "| policy_loss | -3.72 |\n",
+ "| std | 0.834 |\n",
+ "| value_loss | 0.278 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 11.4 |\n",
+ "| ep_rew_mean | -1.29 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 40200 |\n",
+ "| time_elapsed | 941 |\n",
+ "| total_timesteps | 201000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.55 |\n",
+ "| explained_variance | -0.554 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 40199 |\n",
+ "| policy_loss | -5.26 |\n",
+ "| std | 0.835 |\n",
+ "| value_loss | 0.394 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 5.78 |\n",
+ "| ep_rew_mean | -0.538 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 40300 |\n",
+ "| time_elapsed | 943 |\n",
+ "| total_timesteps | 201500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.52 |\n",
+ "| explained_variance | -0.486 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 40299 |\n",
+ "| policy_loss | -1.59 |\n",
+ "| std | 0.83 |\n",
+ "| value_loss | 0.0358 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 8.09 |\n",
+ "| ep_rew_mean | -0.79 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 40400 |\n",
+ "| time_elapsed | 946 |\n",
+ "| total_timesteps | 202000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.5 |\n",
+ "| explained_variance | -136 |\n",
+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | 49.3 |\n",
+ "| std | 0.828 |\n",
+ "| value_loss | 28.1 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 4.38 |\n",
+ "| ep_rew_mean | -0.373 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 40500 |\n",
+ "| time_elapsed | 948 |\n",
+ "| total_timesteps | 202500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.49 |\n",
+ "| explained_variance | -21.8 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 40499 |\n",
+ "| policy_loss | 4.35 |\n",
+ "| std | 0.828 |\n",
+ "| value_loss | 0.355 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 4.42 |\n",
+ "| ep_rew_mean | -0.347 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 40600 |\n",
+ "| time_elapsed | 950 |\n",
+ "| total_timesteps | 203000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.5 |\n",
+ "| explained_variance | -32.4 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 40599 |\n",
+ "| policy_loss | 11.8 |\n",
+ "| std | 0.829 |\n",
+ "| value_loss | 1.94 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 5.23 |\n",
+ "| ep_rew_mean | -0.454 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 40700 |\n",
+ "| time_elapsed | 953 |\n",
+ "| total_timesteps | 203500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.49 |\n",
+ "| explained_variance | -2.9 |\n",
+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | 1.51 |\n",
+ "| std | 0.828 |\n",
+ "| value_loss | 0.17 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 5.48 |\n",
+ "| ep_rew_mean | -0.45 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 40800 |\n",
+ "| time_elapsed | 956 |\n",
+ "| total_timesteps | 204000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.49 |\n",
+ "| explained_variance | -0.871 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 40799 |\n",
+ "| policy_loss | 2.14 |\n",
+ "| std | 0.829 |\n",
+ "| value_loss | 0.0793 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 4.78 |\n",
+ "| ep_rew_mean | -0.403 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 40900 |\n",
+ "| time_elapsed | 958 |\n",
+ "| total_timesteps | 204500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.5 |\n",
+ "| explained_variance | -5.88 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 40899 |\n",
+ "| policy_loss | 9.99 |\n",
+ "| std | 0.83 |\n",
+ "| value_loss | 1.3 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 7.02 |\n",
+ "| ep_rew_mean | -0.747 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 41000 |\n",
+ "| time_elapsed | 960 |\n",
+ "| total_timesteps | 205000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.52 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 40999 |\n",
+ "| policy_loss | 3.54 |\n",
+ "| std | 0.832 |\n",
+ "| value_loss | 0.124 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 8.78 |\n",
+ "| ep_rew_mean | -0.913 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 41100 |\n",
+ "| time_elapsed | 962 |\n",
+ "| total_timesteps | 205500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.55 |\n",
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+ "| n_updates | 41099 |\n",
+ "| policy_loss | 4.36 |\n",
+ "| std | 0.836 |\n",
+ "| value_loss | 0.973 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 5.42 |\n",
+ "| ep_rew_mean | -0.468 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 41200 |\n",
+ "| time_elapsed | 964 |\n",
+ "| total_timesteps | 206000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.56 |\n",
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+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | -1.56 |\n",
+ "| std | 0.838 |\n",
+ "| value_loss | 0.0493 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 5.15 |\n",
+ "| ep_rew_mean | -0.436 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 41300 |\n",
+ "| time_elapsed | 967 |\n",
+ "| total_timesteps | 206500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.57 |\n",
+ "| explained_variance | 0.53 |\n",
+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | 1.25 |\n",
+ "| std | 0.838 |\n",
+ "| value_loss | 0.0425 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.46 |\n",
+ "| ep_rew_mean | -0.6 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 41400 |\n",
+ "| time_elapsed | 970 |\n",
+ "| total_timesteps | 207000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.57 |\n",
+ "| explained_variance | 1 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 41399 |\n",
+ "| policy_loss | 0.223 |\n",
+ "| std | 0.838 |\n",
+ "| value_loss | 0.0114 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 7.51 |\n",
+ "| ep_rew_mean | -0.677 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 41500 |\n",
+ "| time_elapsed | 972 |\n",
+ "| total_timesteps | 207500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.54 |\n",
+ "| explained_variance | -2.53 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 41499 |\n",
+ "| policy_loss | 8.54 |\n",
+ "| std | 0.835 |\n",
+ "| value_loss | 2.33 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.46 |\n",
+ "| ep_rew_mean | -0.563 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 41600 |\n",
+ "| time_elapsed | 974 |\n",
+ "| total_timesteps | 208000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.53 |\n",
+ "| explained_variance | -125 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 41599 |\n",
+ "| policy_loss | -3.69 |\n",
+ "| std | 0.834 |\n",
+ "| value_loss | 0.958 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 7.05 |\n",
+ "| ep_rew_mean | -0.648 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 41700 |\n",
+ "| time_elapsed | 976 |\n",
+ "| total_timesteps | 208500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.55 |\n",
+ "| explained_variance | -4.36 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 41699 |\n",
+ "| policy_loss | 3.82 |\n",
+ "| std | 0.836 |\n",
+ "| value_loss | 0.415 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 5.47 |\n",
+ "| ep_rew_mean | -0.475 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 41800 |\n",
+ "| time_elapsed | 979 |\n",
+ "| total_timesteps | 209000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.54 |\n",
+ "| explained_variance | -0.948 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 41799 |\n",
+ "| policy_loss | -0.0613 |\n",
+ "| std | 0.835 |\n",
+ "| value_loss | 0.0169 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 6.86 |\n",
+ "| ep_rew_mean | -0.648 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 41900 |\n",
+ "| time_elapsed | 981 |\n",
+ "| total_timesteps | 209500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.52 |\n",
+ "| explained_variance | 0.497 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 41899 |\n",
+ "| policy_loss | 7.1 |\n",
+ "| std | 0.831 |\n",
+ "| value_loss | 1.63 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 9.13 |\n",
+ "| ep_rew_mean | -0.994 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 42000 |\n",
+ "| time_elapsed | 983 |\n",
+ "| total_timesteps | 210000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.55 |\n",
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+ "| learning_rate | 0.0007 |\n",
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+ "| policy_loss | 12.6 |\n",
+ "| std | 0.834 |\n",
+ "| value_loss | 9.03 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 10 |\n",
+ "| ep_rew_mean | -1.08 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 42100 |\n",
+ "| time_elapsed | 986 |\n",
+ "| total_timesteps | 210500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.55 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 42099 |\n",
+ "| policy_loss | -5.63 |\n",
+ "| std | 0.834 |\n",
+ "| value_loss | 5.27 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 9.87 |\n",
+ "| ep_rew_mean | -1.07 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 42200 |\n",
+ "| time_elapsed | 988 |\n",
+ "| total_timesteps | 211000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.53 |\n",
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+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 42199 |\n",
+ "| policy_loss | -1.47 |\n",
+ "| std | 0.832 |\n",
+ "| value_loss | 0.1 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 13.8 |\n",
+ "| ep_rew_mean | -1.54 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 42300 |\n",
+ "| time_elapsed | 990 |\n",
+ "| total_timesteps | 211500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.55 |\n",
+ "| explained_variance | -3.37 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 42299 |\n",
+ "| policy_loss | 2.2 |\n",
+ "| std | 0.834 |\n",
+ "| value_loss | 0.156 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 17.5 |\n",
+ "| ep_rew_mean | -2.22 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 42400 |\n",
+ "| time_elapsed | 993 |\n",
+ "| total_timesteps | 212000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.5 |\n",
+ "| explained_variance | -4.49 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 42399 |\n",
+ "| policy_loss | -0.857 |\n",
+ "| std | 0.829 |\n",
+ "| value_loss | 0.0175 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 20.9 |\n",
+ "| ep_rew_mean | -2.95 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 42500 |\n",
+ "| time_elapsed | 996 |\n",
+ "| total_timesteps | 212500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.51 |\n",
+ "| explained_variance | -40 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 42499 |\n",
+ "| policy_loss | 1.06 |\n",
+ "| std | 0.83 |\n",
+ "| value_loss | 0.0349 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 24.9 |\n",
+ "| ep_rew_mean | -3.75 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 42600 |\n",
+ "| time_elapsed | 998 |\n",
+ "| total_timesteps | 213000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.51 |\n",
+ "| explained_variance | -131 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 42599 |\n",
+ "| policy_loss | 1.74 |\n",
+ "| std | 0.83 |\n",
+ "| value_loss | 0.0545 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 28.6 |\n",
+ "| ep_rew_mean | -4.32 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 42700 |\n",
+ "| time_elapsed | 1000 |\n",
+ "| total_timesteps | 213500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.5 |\n",
+ "| explained_variance | -2.8 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 42699 |\n",
+ "| policy_loss | 0.485 |\n",
+ "| std | 0.829 |\n",
+ "| value_loss | 0.0148 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 30.5 |\n",
+ "| ep_rew_mean | -4.6 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 42800 |\n",
+ "| time_elapsed | 1002 |\n",
+ "| total_timesteps | 214000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.51 |\n",
+ "| explained_variance | -52.7 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 42799 |\n",
+ "| policy_loss | -0.654 |\n",
+ "| std | 0.83 |\n",
+ "| value_loss | 0.0313 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 34.6 |\n",
+ "| ep_rew_mean | -5.2 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 42900 |\n",
+ "| time_elapsed | 1005 |\n",
+ "| total_timesteps | 214500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.52 |\n",
+ "| explained_variance | -3.73 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 42899 |\n",
+ "| policy_loss | -1.45 |\n",
+ "| std | 0.832 |\n",
+ "| value_loss | 0.0453 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 33.5 |\n",
+ "| ep_rew_mean | -5.03 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 43000 |\n",
+ "| time_elapsed | 1008 |\n",
+ "| total_timesteps | 215000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.51 |\n",
+ "| explained_variance | -82.8 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 42999 |\n",
+ "| policy_loss | -1.39 |\n",
+ "| std | 0.83 |\n",
+ "| value_loss | 0.0641 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 31.9 |\n",
+ "| ep_rew_mean | -4.61 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 43100 |\n",
+ "| time_elapsed | 1010 |\n",
+ "| total_timesteps | 215500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.49 |\n",
+ "| explained_variance | -4.37 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 43099 |\n",
+ "| policy_loss | 2.73 |\n",
+ "| std | 0.828 |\n",
+ "| value_loss | 0.115 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 25.4 |\n",
+ "| ep_rew_mean | -3.24 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 43200 |\n",
+ "| time_elapsed | 1013 |\n",
+ "| total_timesteps | 216000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.49 |\n",
+ "| explained_variance | -53.1 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 43199 |\n",
+ "| policy_loss | -2.6 |\n",
+ "| std | 0.827 |\n",
+ "| value_loss | 0.21 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.4 |\n",
+ "| ep_rew_mean | -2.64 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 43300 |\n",
+ "| time_elapsed | 1015 |\n",
+ "| total_timesteps | 216500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.51 |\n",
+ "| explained_variance | -15.7 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 43299 |\n",
+ "| policy_loss | -3 |\n",
+ "| std | 0.83 |\n",
+ "| value_loss | 0.127 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 20 |\n",
+ "| ep_rew_mean | -2.49 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 43400 |\n",
+ "| time_elapsed | 1018 |\n",
+ "| total_timesteps | 217000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.51 |\n",
+ "| explained_variance | -13.3 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 43399 |\n",
+ "| policy_loss | 3.72 |\n",
+ "| std | 0.83 |\n",
+ "| value_loss | 0.114 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 17.3 |\n",
+ "| ep_rew_mean | -1.95 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 43500 |\n",
+ "| time_elapsed | 1020 |\n",
+ "| total_timesteps | 217500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.5 |\n",
+ "| explained_variance | -0.127 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 43499 |\n",
+ "| policy_loss | 47.3 |\n",
+ "| std | 0.829 |\n",
+ "| value_loss | 51.2 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 14.9 |\n",
+ "| ep_rew_mean | -1.54 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 43600 |\n",
+ "| time_elapsed | 1022 |\n",
+ "| total_timesteps | 218000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.51 |\n",
+ "| explained_variance | -0.629 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 43599 |\n",
+ "| policy_loss | -0.329 |\n",
+ "| std | 0.829 |\n",
+ "| value_loss | 0.00375 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 14.2 |\n",
+ "| ep_rew_mean | -1.44 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 43700 |\n",
+ "| time_elapsed | 1025 |\n",
+ "| total_timesteps | 218500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.52 |\n",
+ "| explained_variance | -1.74 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 43699 |\n",
+ "| policy_loss | -1.8 |\n",
+ "| std | 0.831 |\n",
+ "| value_loss | 0.066 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 15.2 |\n",
+ "| ep_rew_mean | -1.6 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 43800 |\n",
+ "| time_elapsed | 1027 |\n",
+ "| total_timesteps | 219000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.48 |\n",
+ "| explained_variance | -0.827 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 43799 |\n",
+ "| policy_loss | 0.286 |\n",
+ "| std | 0.826 |\n",
+ "| value_loss | 0.00513 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 18.1 |\n",
+ "| ep_rew_mean | -1.97 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 43900 |\n",
+ "| time_elapsed | 1029 |\n",
+ "| total_timesteps | 219500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.48 |\n",
+ "| explained_variance | 0.0961 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 43899 |\n",
+ "| policy_loss | -0.834 |\n",
+ "| std | 0.826 |\n",
+ "| value_loss | 0.0225 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 20.3 |\n",
+ "| ep_rew_mean | -2.36 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 44000 |\n",
+ "| time_elapsed | 1032 |\n",
+ "| total_timesteps | 220000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.5 |\n",
+ "| explained_variance | 0.556 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 43999 |\n",
+ "| policy_loss | 0.284 |\n",
+ "| std | 0.829 |\n",
+ "| value_loss | 0.0177 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21 |\n",
+ "| ep_rew_mean | -2.53 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 44100 |\n",
+ "| time_elapsed | 1035 |\n",
+ "| total_timesteps | 220500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.53 |\n",
+ "| explained_variance | 0.338 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 44099 |\n",
+ "| policy_loss | 66.9 |\n",
+ "| std | 0.831 |\n",
+ "| value_loss | 85.9 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.3 |\n",
+ "| ep_rew_mean | -2.75 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 44200 |\n",
+ "| time_elapsed | 1037 |\n",
+ "| total_timesteps | 221000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.53 |\n",
+ "| explained_variance | 0.392 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 44199 |\n",
+ "| policy_loss | 0.803 |\n",
+ "| std | 0.831 |\n",
+ "| value_loss | 0.0111 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 22.1 |\n",
+ "| ep_rew_mean | -2.96 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 44300 |\n",
+ "| time_elapsed | 1039 |\n",
+ "| total_timesteps | 221500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.51 |\n",
+ "| explained_variance | -4.37 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 44299 |\n",
+ "| policy_loss | 0.67 |\n",
+ "| std | 0.829 |\n",
+ "| value_loss | 0.019 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.2 |\n",
+ "| ep_rew_mean | -2.88 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 44400 |\n",
+ "| time_elapsed | 1041 |\n",
+ "| total_timesteps | 222000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.54 |\n",
+ "| explained_variance | 0.961 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 44399 |\n",
+ "| policy_loss | 0.0447 |\n",
+ "| std | 0.832 |\n",
+ "| value_loss | 0.0199 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 20.6 |\n",
+ "| ep_rew_mean | -2.72 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 44500 |\n",
+ "| time_elapsed | 1045 |\n",
+ "| total_timesteps | 222500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.52 |\n",
+ "| explained_variance | 0.564 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 44499 |\n",
+ "| policy_loss | -1.71 |\n",
+ "| std | 0.83 |\n",
+ "| value_loss | 0.0518 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 20.2 |\n",
+ "| ep_rew_mean | -2.64 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 44600 |\n",
+ "| time_elapsed | 1047 |\n",
+ "| total_timesteps | 223000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.54 |\n",
+ "| explained_variance | -1.6 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 44599 |\n",
+ "| policy_loss | -0.0737 |\n",
+ "| std | 0.831 |\n",
+ "| value_loss | 0.00317 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.5 |\n",
+ "| ep_rew_mean | -2.81 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 44700 |\n",
+ "| time_elapsed | 1049 |\n",
+ "| total_timesteps | 223500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.52 |\n",
+ "| explained_variance | -2.55 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 44699 |\n",
+ "| policy_loss | -0.534 |\n",
+ "| std | 0.83 |\n",
+ "| value_loss | 0.00457 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 22.1 |\n",
+ "| ep_rew_mean | -2.74 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 44800 |\n",
+ "| time_elapsed | 1051 |\n",
+ "| total_timesteps | 224000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.5 |\n",
+ "| explained_variance | -3.5 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 44799 |\n",
+ "| policy_loss | -0.523 |\n",
+ "| std | 0.828 |\n",
+ "| value_loss | 0.0107 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21.2 |\n",
+ "| ep_rew_mean | -2.57 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 44900 |\n",
+ "| time_elapsed | 1054 |\n",
+ "| total_timesteps | 224500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.49 |\n",
+ "| explained_variance | 0.555 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 44899 |\n",
+ "| policy_loss | -0.784 |\n",
+ "| std | 0.827 |\n",
+ "| value_loss | 0.0117 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 23.6 |\n",
+ "| ep_rew_mean | -2.77 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 45000 |\n",
+ "| time_elapsed | 1056 |\n",
+ "| total_timesteps | 225000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.49 |\n",
+ "| explained_variance | -19.5 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 44999 |\n",
+ "| policy_loss | 0.149 |\n",
+ "| std | 0.827 |\n",
+ "| value_loss | 0.00261 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 26.5 |\n",
+ "| ep_rew_mean | -3.12 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 45100 |\n",
+ "| time_elapsed | 1059 |\n",
+ "| total_timesteps | 225500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.53 |\n",
+ "| explained_variance | -5.61 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 45099 |\n",
+ "| policy_loss | 0.0418 |\n",
+ "| std | 0.832 |\n",
+ "| value_loss | 0.00496 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 28.3 |\n",
+ "| ep_rew_mean | -3.29 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 45200 |\n",
+ "| time_elapsed | 1061 |\n",
+ "| total_timesteps | 226000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.54 |\n",
+ "| explained_variance | -89.5 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 45199 |\n",
+ "| policy_loss | 0.533 |\n",
+ "| std | 0.833 |\n",
+ "| value_loss | 0.0217 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 27.6 |\n",
+ "| ep_rew_mean | -3.14 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 45300 |\n",
+ "| time_elapsed | 1063 |\n",
+ "| total_timesteps | 226500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.51 |\n",
+ "| explained_variance | -5.7 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 45299 |\n",
+ "| policy_loss | 2.17 |\n",
+ "| std | 0.83 |\n",
+ "| value_loss | 0.0799 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 28.7 |\n",
+ "| ep_rew_mean | -3.38 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 45400 |\n",
+ "| time_elapsed | 1065 |\n",
+ "| total_timesteps | 227000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.49 |\n",
+ "| explained_variance | 0.352 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 45399 |\n",
+ "| policy_loss | 32.3 |\n",
+ "| std | 0.828 |\n",
+ "| value_loss | 46.9 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 30.6 |\n",
+ "| ep_rew_mean | -3.68 |\n",
+ "| time/ | |\n",
+ "| fps | 213 |\n",
+ "| iterations | 45500 |\n",
+ "| time_elapsed | 1067 |\n",
+ "| total_timesteps | 227500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.45 |\n",
+ "| explained_variance | -23.8 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 45499 |\n",
+ "| policy_loss | 0.00402 |\n",
+ "| std | 0.824 |\n",
+ "| value_loss | 0.00125 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 30.3 |\n",
+ "| ep_rew_mean | -3.64 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 45600 |\n",
+ "| time_elapsed | 1071 |\n",
+ "| total_timesteps | 228000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.41 |\n",
+ "| explained_variance | -0.362 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 45599 |\n",
+ "| policy_loss | -0.421 |\n",
+ "| std | 0.821 |\n",
+ "| value_loss | 0.00643 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 29.5 |\n",
+ "| ep_rew_mean | -3.52 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 45700 |\n",
+ "| time_elapsed | 1073 |\n",
+ "| total_timesteps | 228500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.4 |\n",
+ "| explained_variance | 0.214 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 45699 |\n",
+ "| policy_loss | 26.4 |\n",
+ "| std | 0.819 |\n",
+ "| value_loss | 28.1 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 29.7 |\n",
+ "| ep_rew_mean | -3.56 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 45800 |\n",
+ "| time_elapsed | 1075 |\n",
+ "| total_timesteps | 229000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.38 |\n",
+ "| explained_variance | -5.01 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 45799 |\n",
+ "| policy_loss | 0.152 |\n",
+ "| std | 0.817 |\n",
+ "| value_loss | 0.0019 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 25 |\n",
+ "| ep_rew_mean | -2.94 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 45900 |\n",
+ "| time_elapsed | 1077 |\n",
+ "| total_timesteps | 229500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.38 |\n",
+ "| explained_variance | 0.584 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 45899 |\n",
+ "| policy_loss | 12 |\n",
+ "| std | 0.817 |\n",
+ "| value_loss | 7.89 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 20.9 |\n",
+ "| ep_rew_mean | -2.31 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 46000 |\n",
+ "| time_elapsed | 1079 |\n",
+ "| total_timesteps | 230000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.35 |\n",
+ "| explained_variance | 0.369 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 45999 |\n",
+ "| policy_loss | 9.14 |\n",
+ "| std | 0.814 |\n",
+ "| value_loss | 13.8 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 19.9 |\n",
+ "| ep_rew_mean | -2.18 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 46100 |\n",
+ "| time_elapsed | 1082 |\n",
+ "| total_timesteps | 230500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.32 |\n",
+ "| explained_variance | -2.14 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 46099 |\n",
+ "| policy_loss | -2.3 |\n",
+ "| std | 0.81 |\n",
+ "| value_loss | 0.0864 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 16.5 |\n",
+ "| ep_rew_mean | -1.79 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 46200 |\n",
+ "| time_elapsed | 1085 |\n",
+ "| total_timesteps | 231000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.34 |\n",
+ "| explained_variance | -1.16 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 46199 |\n",
+ "| policy_loss | 0.0412 |\n",
+ "| std | 0.813 |\n",
+ "| value_loss | 0.00237 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 18.5 |\n",
+ "| ep_rew_mean | -2.01 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 46300 |\n",
+ "| time_elapsed | 1087 |\n",
+ "| total_timesteps | 231500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.34 |\n",
+ "| explained_variance | -4.59 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 46299 |\n",
+ "| policy_loss | 0.152 |\n",
+ "| std | 0.813 |\n",
+ "| value_loss | 0.000828 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 16.9 |\n",
+ "| ep_rew_mean | -1.86 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 46400 |\n",
+ "| time_elapsed | 1089 |\n",
+ "| total_timesteps | 232000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.33 |\n",
+ "| explained_variance | -3.32 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 46399 |\n",
+ "| policy_loss | 0.712 |\n",
+ "| std | 0.811 |\n",
+ "| value_loss | 0.0174 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 17.8 |\n",
+ "| ep_rew_mean | -2.08 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 46500 |\n",
+ "| time_elapsed | 1091 |\n",
+ "| total_timesteps | 232500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.33 |\n",
+ "| explained_variance | 0.971 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 46499 |\n",
+ "| policy_loss | -0.512 |\n",
+ "| std | 0.811 |\n",
+ "| value_loss | 0.00613 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 21 |\n",
+ "| ep_rew_mean | -2.6 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 46600 |\n",
+ "| time_elapsed | 1093 |\n",
+ "| total_timesteps | 233000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.36 |\n",
+ "| explained_variance | -0.171 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 46599 |\n",
+ "| policy_loss | 0.657 |\n",
+ "| std | 0.816 |\n",
+ "| value_loss | 0.00852 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 18.4 |\n",
+ "| ep_rew_mean | -2.22 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 46700 |\n",
+ "| time_elapsed | 1097 |\n",
+ "| total_timesteps | 233500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.35 |\n",
+ "| explained_variance | -12.4 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 46699 |\n",
+ "| policy_loss | 0.196 |\n",
+ "| std | 0.814 |\n",
+ "| value_loss | 0.000866 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 17.6 |\n",
+ "| ep_rew_mean | -2 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 46800 |\n",
+ "| time_elapsed | 1099 |\n",
+ "| total_timesteps | 234000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.36 |\n",
+ "| explained_variance | 0.312 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 46799 |\n",
+ "| policy_loss | 21.9 |\n",
+ "| std | 0.815 |\n",
+ "| value_loss | 15.1 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 10.9 |\n",
+ "| ep_rew_mean | -0.988 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 46900 |\n",
+ "| time_elapsed | 1101 |\n",
+ "| total_timesteps | 234500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.36 |\n",
+ "| explained_variance | -6.13 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 46899 |\n",
+ "| policy_loss | 39.7 |\n",
+ "| std | 0.815 |\n",
+ "| value_loss | 20.4 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 10.1 |\n",
+ "| ep_rew_mean | -0.929 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 47000 |\n",
+ "| time_elapsed | 1103 |\n",
+ "| total_timesteps | 235000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.36 |\n",
+ "| explained_variance | -22 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 46999 |\n",
+ "| policy_loss | 0.883 |\n",
+ "| std | 0.814 |\n",
+ "| value_loss | 0.0223 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 10.8 |\n",
+ "| ep_rew_mean | -1.01 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 47100 |\n",
+ "| time_elapsed | 1105 |\n",
+ "| total_timesteps | 235500 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.36 |\n",
+ "| explained_variance | -0.929 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 47099 |\n",
+ "| policy_loss | 16.5 |\n",
+ "| std | 0.815 |\n",
+ "| value_loss | 12.4 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
+ "| ep_len_mean | 10.4 |\n",
+ "| ep_rew_mean | -0.942 |\n",
+ "| time/ | |\n",
+ "| fps | 212 |\n",
+ "| iterations | 47200 |\n",
+ "| time_elapsed | 1108 |\n",
+ "| total_timesteps | 236000 |\n",
+ "| train/ | |\n",
+ "| entropy_loss | -8.35 |\n",
+ "| explained_variance | -0.097 |\n",
+ "| learning_rate | 0.0007 |\n",
+ "| n_updates | 47199 |\n",
+ "| policy_loss | -0.956 |\n",
+ "| std | 0.814 |\n",
+ "| value_loss | 0.019 |\n",
+ "------------------------------------\n",
+ "------------------------------------\n",
+ "| rollout/ | |\n",
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+ "------------------------------------\n",
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+ "------------------------------------\n",
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+ "------------------------------------\n",
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+ " .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
+ " </style>\n",
+ "<div class=\"wandb-row\"><div class=\"wandb-col\"><h3>Run history:</h3><br/><table class=\"wandb\"><tr><td>global_step</td><td>▁▁▁▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███</td></tr><tr><td>rollout/ep_len_mean</td><td>███▇▇▅▄▃▃▂▅▇▆▄▃▆▅█▄▅▇▆▄▆▄▆▄▂▃▁▂▁▁▂▃▄▄▂▂▂</td></tr><tr><td>rollout/ep_rew_mean</td><td>▁▁▂▃▄▆▇▇▇▇▄▂▅▆▇▄▆▄▆▆▅▅▆▆▇▆▇█▇█████▇▆▇███</td></tr><tr><td>time/fps</td><td>▁▄▅▅▆▇▇▇███████████████▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇</td></tr><tr><td>train/entropy_loss</td><td>▂▁▁▁▁▁▂▂▃▃▃▃▃▃▃▃▃▃▃▄▄▄▄▄▄▄▄▅▅▆▆▇▇▆▇▇▇▇██</td></tr><tr><td>train/explained_variance</td><td>██████████████▇█▇▇█████▁████▇███████████</td></tr><tr><td>train/learning_rate</td><td>▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁</td></tr><tr><td>train/policy_loss</td><td>▂▂▇▂▂▆▂▂▅▂▁▂▂▂▁▂▂▂▂▂▂▂▂▂▁▂▂█▂▁▁▂▂▄▂▂▃▂▂▁</td></tr><tr><td>train/std</td><td>▇████▇▇▇▆▆▅▅▆▅▆▆▆▅▅▅▅▅▅▄▅▅▅▄▄▃▃▂▂▂▂▂▂▂▁▁</td></tr><tr><td>train/value_loss</td><td>▁▁█▁▁▃▁▁▃▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▃▁▁▁▁▁▂▁▁▂▁▁▁</td></tr></table><br/></div><div class=\"wandb-col\"><h3>Run summary:</h3><br/><table class=\"wandb\"><tr><td>global_step</td><td>250000</td></tr><tr><td>rollout/ep_len_mean</td><td>11.85</td></tr><tr><td>rollout/ep_rew_mean</td><td>-1.14974</td></tr><tr><td>time/fps</td><td>212.0</td></tr><tr><td>train/entropy_loss</td><td>-8.07425</td></tr><tr><td>train/explained_variance</td><td>0.84638</td></tr><tr><td>train/learning_rate</td><td>0.0007</td></tr><tr><td>train/policy_loss</td><td>6.47005</td></tr><tr><td>train/std</td><td>0.78183</td></tr><tr><td>train/value_loss</td><td>2.69757</td></tr></table><br/></div></div>"
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ],
+ "text/html": [
+ " View run <strong style=\"color:#cdcd00\">dashing-glitter-6</strong> at: <a href='https://wandb.ai/aiblackbelt/sb3-panda-reach/runs/ihcoeovn' target=\"_blank\">https://wandb.ai/aiblackbelt/sb3-panda-reach/runs/ihcoeovn</a><br/> View job at <a href='https://wandb.ai/aiblackbelt/sb3-panda-reach/jobs/QXJ0aWZhY3RDb2xsZWN0aW9uOjE0NTc2ODkxNg==/version_details/v3' target=\"_blank\">https://wandb.ai/aiblackbelt/sb3-panda-reach/jobs/QXJ0aWZhY3RDb2xsZWN0aW9uOjE0NTc2ODkxNg==/version_details/v3</a><br/>Synced 5 W&B file(s), 0 media file(s), 4 artifact file(s) and 3 other file(s)"
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "<IPython.core.display.HTML object>"
+ ],
+ "text/html": [
+ "Find logs at: <code>./wandb/run-20240305_210146-ihcoeovn/logs</code>"
+ ]
+ },
+ "metadata": {}
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "login(token=\"*********\")"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "chs528paf6QF",
+ "outputId": "0f7016c0-d3e9-4b4a-f358-b42b408c0448"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Token will not been saved to git credential helper. Pass `add_to_git_credential=True` if you want to set the git credential as well.\n",
+ "Token is valid (permission: write).\n",
+ "Your token has been saved to /root/.cache/huggingface/token\n",
+ "Login successful\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "# Save the trained model\n",
+ "model.save(\"ECL-TD-RL1-a2c_panda_reach.zip\")\n",
+ "\n",
+ "# Load the trained model\n",
+ "model = A2C.load(\"ECL-TD-RL1-a2c_panda_reach.zip\")\n",
+ "\n",
+ "push_to_hub(\n",
+ " repo_id=\"Karim-20/a2c_cartpole\",\n",
+ " filename=\"ECL-TD-RL1-a2c_panda_reach.zip\",\n",
+ " commit_message=\"Add PandaReachJointsDense-v2 environement, agent used to train is A2C\"\n",
+ ")\n"
+ ],
+ "metadata": {
+ "id": "Z02f1oIdRh28",
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 136,
+ "referenced_widgets": [
+ "a47211d565fb45fe95b30b99885c4dbd",
+ "df1580d505af40828061a4c042546f76",
+ "4627448bbe6d40178e356623c281803f",
+ "92339b2faa4b47c69b5457aa9631edf7",
+ "a337aa65ec8b498f87cb74caa342a6a3",
+ "c1fbb5d26065440aa5eeee238d0d1d38",
+ "0447228f33a344cd91a2e18cc73cd63e",
+ "4657c6ea689f494a9254c69d2a08dd4e",
+ "ef2b6851a3784430949ecf77410e3386",
+ "178580de1f0b4840825b70ffebaf00c2",
+ "6aeac63ed6e840c59814923109a66f58"
+ ]
+ },
+ "outputId": "694736b8-769a-42ba-dffe-41411433c2c8"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\u001b[38;5;4mℹ Pushing repo Karim-20/a2c_cartpole to the Hugging Face Hub\u001b[0m\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "text/plain": [
+ "ECL-TD-RL1-a2c_panda_reach.zip: 0%| | 0.00/110k [00:00<?, ?B/s]"
+ ],
+ "application/vnd.jupyter.widget-view+json": {
+ "version_major": 2,
+ "version_minor": 0,
+ "model_id": "a47211d565fb45fe95b30b99885c4dbd"
+ }
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "\u001b[38;5;2m✔ Your model has been uploaded to the Hub, you can find it here:\n",
+ "https://huggingface.co/Karim-20/a2c_cartpole/tree/main/\u001b[0m\n"
+ ]
+ },
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "CommitInfo(commit_url='https://huggingface.co/Karim-20/a2c_cartpole/commit/e5577037d98c688e89cbf3851fb89b09bcf9ca81', commit_message='Add PandaReachJointsDense-v2 environement, agent used to train is A2C', commit_description='', oid='e5577037d98c688e89cbf3851fb89b09bcf9ca81', pr_url=None, pr_revision=None, pr_num=None)"
+ ],
+ "application/vnd.google.colaboratory.intrinsic+json": {
+ "type": "string"
+ }
+ },
+ "metadata": {},
+ "execution_count": 19
+ }
+ ]
+ }
+ ]
+}
\ No newline at end of file
--
GitLab