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* Simplify extras_require * Rm gym-robotics ; gym -> gymnasium * Python 3.10 * new extra dependency in CI * `import gym` -> `import gymnasium as gym` * render.modes -> render_modes * reset returns info * black and isort * Fix CI extra requires * Remove SB3 and numpgw extra dependency * obs or state -> observation * black * replavec done by trun and term when appeled * black * gym -> gymnasium * Step return trunc and term * compute_reward returns float32, is_success returns bool * float64 -> float32 * fix typing * black * Allow return tuple documentation * Fix doc * Remove unused import * panda_tasks in a single file * black * fix pip install notebook * improve save_restore documentation * documentation save and restore state * Python version in CI: 3.X to '3.X' * profile black to isort * typo * fix reset arg and dtype * Fix CI because pytype can't be installed on windows * v3 * Clean notebook
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,157 +1,116 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": { | ||
| "colab_type": "text", | ||
| "id": "view-in-github" | ||
| }, | ||
| "source": [ | ||
| "<a href=\"https://colab.research.google.com/github/qgallouedec/panda-gym/blob/colab/PickAndPlace.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": { | ||
| "id": "TFFVaHq_7fSe" | ||
| }, | ||
| "source": [ | ||
| "# `panda-gym` code example\n", | ||
| "\n", | ||
| "## Install `panda-gym`" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "colab": { | ||
| "base_uri": "https://localhost:8080/" | ||
| }, | ||
| "id": "gvS3_Wp_6rqE", | ||
| "outputId": "0c25d21e-d823-4b4c-88bd-6eb1a0425acd" | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "!pip install panda-gym" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": { | ||
| "id": "qE8atPQm870Q" | ||
| }, | ||
| "source": [ | ||
| "## Interract" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "id": "gLQSKOE_8_kB" | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import gym\n", | ||
| "import panda_gym\n", | ||
| "\n", | ||
| "env = gym.make('PandaPickAndPlace-v2', render=True)\n", | ||
| "state = env.reset()\n", | ||
| "\n", | ||
| "done = False\n", | ||
| "images = [env.render('rgb_array')]\n", | ||
| "while not done:\n", | ||
| " action = env.action_space.sample()\n", | ||
| " state, reward, done, info = env.step(action)\n", | ||
| " images.append(env.render('rgb_array'))\n", | ||
| "\n", | ||
| "env.close()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": { | ||
| "id": "Nkl-EtEZ_EQH" | ||
| }, | ||
| "source": [ | ||
| "## Convert into animation\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "colab": { | ||
| "base_uri": "https://localhost:8080/" | ||
| }, | ||
| "id": "E2eWDjPZsQc5", | ||
| "outputId": "83bb407d-ea87-49a3-e61d-291f7db7f824" | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "!pip3 install numpngw\n", | ||
| "from numpngw import write_apng\n", | ||
| "\n", | ||
| "write_apng('anim.png', images, delay=40) # real-time rendering = 40 ms between frames" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": { | ||
| "id": "dFadL1ne_NG8" | ||
| }, | ||
| "source": [ | ||
| "## Show animation" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "colab": { | ||
| "base_uri": "https://localhost:8080/", | ||
| "height": 737 | ||
| }, | ||
| "id": "5mJ2AQYN-22E", | ||
| "outputId": "620d7be1-13cf-4c60-a934-a1806e1bc4a9" | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from IPython.display import Image\n", | ||
| "\n", | ||
| "Image(filename=\"anim.png\")" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "colab": { | ||
| "authorship_tag": "ABX9TyPoojQ0oWlcLJWd6nANAzj6", | ||
| "collapsed_sections": [], | ||
| "include_colab_link": true, | ||
| "name": "PickAndPlace.ipynb", | ||
| "provenance": [] | ||
| }, | ||
| "interpreter": { | ||
| "hash": "8e193b2e5d21c2e374c02529de74b36a677b513007ad2ca2b9715beb5c35b2ac" | ||
| }, | ||
| "kernelspec": { | ||
| "display_name": "Python 3.7.5 64-bit ('env': venv)", | ||
| "name": "python3" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.8.9" | ||
| } | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": { | ||
| "colab_type": "text", | ||
| "id": "view-in-github" | ||
| }, | ||
| "source": [ | ||
| "<a href=\"https://colab.research.google.com/github/qgallouedec/panda-gym/blob/colab/PickAndPlace.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | ||
| ] | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 0 | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": { | ||
| "id": "TFFVaHq_7fSe" | ||
| }, | ||
| "source": [ | ||
| "# `panda-gym` code example\n", | ||
| "\n", | ||
| "## Install `panda-gym`" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "%pip install panda-gym" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": { | ||
| "id": "qE8atPQm870Q" | ||
| }, | ||
| "source": [ | ||
| "## Interract" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import gymnasium as gym\n", | ||
| "import panda_gym\n", | ||
| "\n", | ||
| "env = gym.make(\"PandaPickAndPlace-v3\", render=True)\n", | ||
| "observation, info = env.reset()\n", | ||
| "\n", | ||
| "images = [env.render(\"rgb_array\")]\n", | ||
| "for _ in range(1000):\n", | ||
| " action = env.action_space.sample()\n", | ||
| " observation, reward, terminated, truncated, info = env.step(action)\n", | ||
| " images.append(env.render(\"rgb_array\"))\n", | ||
| "\n", | ||
| " if terminated or truncated:\n", | ||
| " observation, info = env.reset()\n", | ||
| " images.append(env.render(\"rgb_array\"))\n", | ||
| "\n", | ||
| "env.close()" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": { | ||
| "id": "Nkl-EtEZ_EQH" | ||
| }, | ||
| "source": [ | ||
| "## Convert into animation\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "%pip3 install numpngw\n", | ||
| "from numpngw import write_apng\n", | ||
| "\n", | ||
| "write_apng(\"anim.png\", images, delay=40) # real-time rendering = 40 ms between frames" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": { | ||
| "id": "dFadL1ne_NG8" | ||
| }, | ||
| "source": [ | ||
| "## Show animation" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from IPython.display import Image\n", | ||
| "\n", | ||
| "Image(filename=\"anim.png\")" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "language_info": { | ||
| "name": "python" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 0 | ||
| } |
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