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Add new python venv for ML-Agents & Colab compatibility

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2025-01-18 14:50:31 +05:30
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notebooks/bonus-unit1/bonus-unit1.ipynb
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@@ -3,8 +3,8 @@
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
"colab_type": "text",
"id": "view-in-github"
},
"source": [
"<a href=\"https://colab.research.google.com/github/huggingface/deep-rl-class/blob/main/notebooks/bonus-unit1/bonus-unit1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
@@ -21,31 +21,34 @@
},
{
"cell_type": "markdown",
"metadata": {
"id": "FMYrDriDujzX"
},
"source": [
"<img src=\"https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit2/thumbnail.png\" alt=\"Bonus Unit 1Thumbnail\">\n",
"\n",
"In this notebook, we'll reinforce what we learned in the first Unit by **teaching Huggy the Dog to fetch the stick and then play with it directly in your browser**\n",
"\n",
"⬇️ Here is an example of what **you will achieve at the end of the unit.** ⬇️ (launch ▶ to see)"
],
"metadata": {
"id": "FMYrDriDujzX"
}
]
},
{
"cell_type": "code",
"source": [
"%%html\n",
"<video controls autoplay><source src=\"https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/notebooks/unit-bonus1/huggy.mp4\" type=\"video/mp4\"></video>"
],
"execution_count": null,
"metadata": {
"id": "PnVhs1yYNyUF"
},
"execution_count": null,
"outputs": []
"outputs": [],
"source": [
"%%html\n",
"<video controls autoplay><source src=\"https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/notebooks/unit-bonus1/huggy.mp4\" type=\"video/mp4\"></video>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "x7oR6R-ZIbeS"
},
"source": [
"### The environment 🎮\n",
"\n",
@@ -54,22 +57,22 @@
"### The library used 📚\n",
"\n",
"- [MLAgents](https://github.com/Unity-Technologies/ml-agents)"
],
"metadata": {
"id": "x7oR6R-ZIbeS"
}
]
},
{
"cell_type": "markdown",
"source": [
"We're constantly trying to improve our tutorials, so **if you find some issues in this notebook**, please [open an issue on the Github Repo](https://github.com/huggingface/deep-rl-class/issues)."
],
"metadata": {
"id": "60yACvZwO0Cy"
}
},
"source": [
"We're constantly trying to improve our tutorials, so **if you find some issues in this notebook**, please [open an issue on the Github Repo](https://github.com/huggingface/deep-rl-class/issues)."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Oks-ETYdO2Dc"
},
"source": [
"## Objectives of this notebook 🏆\n",
"\n",
@@ -80,23 +83,23 @@
"- Be able to play **with your trained Huggy directly in your browser**.\n",
"\n",
"\n"
],
"metadata": {
"id": "Oks-ETYdO2Dc"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "mUlVrqnBv2o1"
},
"source": [
"## This notebook is from Deep Reinforcement Learning Course\n",
"<img src=\"https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/notebooks/deep-rl-course-illustration.jpg\" alt=\"Deep RL Course illustration\"/>"
],
"metadata": {
"id": "mUlVrqnBv2o1"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "pAMjaQpHwB_s"
},
"source": [
"In this free course, you will:\n",
"\n",
@@ -110,13 +113,13 @@
"\n",
"\n",
"The best way to keep in touch is to join our discord server to exchange with the community and with us 👉🏻 https://discord.gg/ydHrjt3WP5"
],
"metadata": {
"id": "pAMjaQpHwB_s"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "6r7Hl0uywFSO"
},
"source": [
"## Prerequisites 🏗️\n",
"\n",
@@ -125,33 +128,30 @@
"🔲 📚 **Develop an understanding of the foundations of Reinforcement learning** (MC, TD, Rewards hypothesis...) by doing Unit 1\n",
"\n",
"🔲 📚 **Read the introduction to Huggy** by doing Bonus Unit 1"
],
"metadata": {
"id": "6r7Hl0uywFSO"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "DssdIjk_8vZE"
},
"source": [
"## Set the GPU 💪\n",
"- To **accelerate the agent's training, we'll use a GPU**. To do that, go to `Runtime > Change Runtime type`\n",
"\n",
"<img src=\"https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/notebooks/gpu-step1.jpg\" alt=\"GPU Step 1\">"
],
"metadata": {
"id": "DssdIjk_8vZE"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "sTfCXHy68xBv"
},
"source": [
"- `Hardware Accelerator > GPU`\n",
"\n",
"<img src=\"https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/notebooks/gpu-step2.jpg\" alt=\"GPU Step 2\">"
],
"metadata": {
"id": "sTfCXHy68xBv"
}
]
},
{
"cell_type": "markdown",
@@ -159,7 +159,7 @@
"id": "an3ByrXYQ4iK"
},
"source": [
"## Clone the repository and install the dependencies 🔽\n",
"## Clone the repository 🔽\n",
"\n",
"- We need to clone the repository, that contains **ML-Agents.**"
]
@@ -177,6 +177,77 @@
"!git clone --depth 1 https://github.com/Unity-Technologies/ml-agents"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Setup the Virtual Environment 🔽\n",
"- In order for the **ML-Agents** to run successfully in Colab, Colab's Python version must meet the library's Python requirements.\n",
"\n",
"- We can check for the supported Python version under the `python_requires` parameter in the `setup.py` files. These files are required to set up the **ML-Agents** library for use and can be found in the following locations:\n",
" - `/content/ml-agents/ml-agents/setup.py`\n",
" - `/content/ml-agents/ml-agents-envs/setup.py`\n",
"\n",
"- Colab's Current Python version(can be checked using `!python --version`) doesn't match the library's `python_requires` parameter, as a result installation may silently fail and lead to errors like these, when executing the same commands later:\n",
" - `/bin/bash: line 1: mlagents-learn: command not found`\n",
" - `/bin/bash: line 1: mlagents-push-to-hf: command not found`\n",
"\n",
"- To resolve this, we'll create a virtual environment with a Python version compatible with the **ML-Agents** library.\n",
"\n",
"`Note:` *For future compatibility, always check the `python_requires` parameter in the installation files and set your virtual environment to the maximum supported Python version in the given below script if the Colab's Python version is not compatible*"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Colab's Current Python Version (Incompatible with ML-Agents)\n",
"!python --version"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Install virtualenv and create a virtual environment\n",
"!pip install virtualenv\n",
"!virtualenv myenv\n",
"\n",
"# Download and install Miniconda\n",
"!wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\n",
"!chmod +x Miniconda3-latest-Linux-x86_64.sh\n",
"!./Miniconda3-latest-Linux-x86_64.sh -b -f -p /usr/local\n",
"\n",
"# Activate Miniconda and install Python ver 3.10.12\n",
"!source /usr/local/bin/activate\n",
"!conda install -q -y --prefix /usr/local python=3.10.12 ujson # Specify the version here\n",
"\n",
"# Set environment variables for Python and conda paths\n",
"!export PYTHONPATH=/usr/local/lib/python3.10/site-packages/\n",
"!export CONDA_PREFIX=/usr/local/envs/myenv"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Python Version in New Virtual Environment (Compatible with ML-Agents)\n",
"!python --version"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Installing the dependencies 🔽"
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -218,23 +289,23 @@
},
{
"cell_type": "markdown",
"source": [
"We downloaded the file Huggy.zip from https://github.com/huggingface/Huggy using `wget`"
],
"metadata": {
"id": "IHh_LXsRrrbM"
}
},
"source": [
"We downloaded the file Huggy.zip from https://github.com/huggingface/Huggy using `wget`"
]
},
{
"cell_type": "code",
"source": [
"!wget \"https://github.com/huggingface/Huggy/raw/main/Huggy.zip\" -O ./trained-envs-executables/linux/Huggy.zip"
],
"execution_count": null,
"metadata": {
"id": "8xNAD1tRpy0_"
},
"execution_count": null,
"outputs": []
"outputs": [],
"source": [
"!wget \"https://github.com/huggingface/Huggy/raw/main/Huggy.zip\" -O ./trained-envs-executables/linux/Huggy.zip"
]
},
{
"cell_type": "code",
@@ -270,6 +341,9 @@
},
{
"cell_type": "markdown",
"metadata": {
"id": "dYKVj8yUvj55"
},
"source": [
"## Let's recap how this environment works\n",
"\n",
@@ -307,13 +381,13 @@
"- *Time penalty*: a fixed-time penalty given at every action to **force him to get to the stick as fast as possible**.\n",
"- *Rotation penalty*: we penalize Huggy if **he spins too much and turns too quickly**.\n",
"- *Getting to the target reward*: we reward Huggy for **reaching the target**."
],
"metadata": {
"id": "dYKVj8yUvj55"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "NAuEq32Mwvtz"
},
"source": [
"## Create the Huggy config file\n",
"\n",
@@ -333,13 +407,15 @@
" <img src=\"https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit1/create-huggy.png\" alt=\"Create huggy.yaml\" width=\"20%\">\n",
"\n",
"- Copy and paste the content below 🔽"
],
"metadata": {
"id": "NAuEq32Mwvtz"
}
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "loQ0N5jhXW71"
},
"outputs": [],
"source": [
"behaviors:\n",
" Huggy:\n",
@@ -367,24 +443,22 @@
" max_steps: 2e6\n",
" time_horizon: 1000\n",
" summary_freq: 50000"
],
"metadata": {
"id": "loQ0N5jhXW71"
},
"execution_count": null,
"outputs": []
]
},
{
"cell_type": "markdown",
"source": [
"- Don't forget to save the file!"
],
"metadata": {
"id": "oakN7UHwXdCX"
}
},
"source": [
"- Don't forget to save the file!"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "r9wv5NYGw-05"
},
"source": [
"- **In the case you want to modify the hyperparameters**, in Google Colab notebook, you can click here to open the config.yaml: `/content/ml-agents/config/ppo/Huggy.yaml`\n",
"\n",
@@ -394,10 +468,7 @@
"\n",
"=> Just keep in mind that **decreasing the `checkpoint_interval` means more models to upload to the Hub and so a longer uploading time**\n",
"We’re now ready to train our agent 🔥."
],
"metadata": {
"id": "r9wv5NYGw-05"
}
]
},
{
"cell_type": "markdown",
@@ -426,12 +497,12 @@
},
{
"cell_type": "markdown",
"source": [
"The training will take 30 to 45min depending on your machine (don't forget to **set up a GPU**), go take a ☕️you deserve it 🤗."
],
"metadata": {
"id": "lN32oWF8zPjs"
}
},
"source": [
"The training will take 30 to 45min depending on your machine (don't forget to **set up a GPU**), go take a ☕️you deserve it 🤗."
]
},
{
"cell_type": "code",
@@ -457,6 +528,9 @@
},
{
"cell_type": "markdown",
"metadata": {
"id": "izT6FpgNzZ6R"
},
"source": [
"To be able to share your model with the community there are three more steps to follow:\n",
"\n",
@@ -469,10 +543,7 @@
"\n",
"- Copy the token\n",
"- Run the cell below and paste the token"
],
"metadata": {
"id": "izT6FpgNzZ6R"
}
]
},
{
"cell_type": "code",
@@ -488,12 +559,12 @@
},
{
"cell_type": "markdown",
"source": [
"If you don't want to use a Google Colab or a Jupyter Notebook, you need to use this command instead: `huggingface-cli login`"
],
"metadata": {
"id": "ew59mK19zjtN"
}
},
"source": [
"If you don't want to use a Google Colab or a Jupyter Notebook, you need to use this command instead: `huggingface-cli login`"
]
},
{
"cell_type": "markdown",
@@ -508,6 +579,9 @@
},
{
"cell_type": "markdown",
"metadata": {
"id": "KK4fPfnczunT"
},
"source": [
"And we define 4 parameters:\n",
"\n",
@@ -516,10 +590,7 @@
"3. `--repo-id`: the name of the Hugging Face repo you want to create or update. It’s always <your huggingface username>/<the repo name>\n",
"If the repo does not exist **it will be created automatically**\n",
"4. `--commit-message`: since HF repos are git repository you need to define a commit message."
],
"metadata": {
"id": "KK4fPfnczunT"
}
]
},
{
"cell_type": "code",
@@ -534,6 +605,9 @@
},
{
"cell_type": "markdown",
"metadata": {
"id": "yborB0850FTM"
},
"source": [
"Else, if everything worked you should have this at the end of the process(but with a different url 😆) :\n",
"\n",
@@ -546,22 +620,22 @@
"It’s the link to your model repository. The repository contains a model card that explains how to use the model, your Tensorboard logs and your config file. **What’s awesome is that it’s a git repository, which means you can have different commits, update your repository with a new push, open Pull Requests, etc.**\n",
"\n",
"<img src=\"https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/notebooks/unit-bonus1/modelcard.png\" alt=\"ml learn function\" width=\"100%\">"
],
"metadata": {
"id": "yborB0850FTM"
}
]
},
{
"cell_type": "markdown",
"source": [
"But now comes the best: **being able to play with Huggy online 👀.**"
],
"metadata": {
"id": "5Uaon2cg0NrL"
}
},
"source": [
"But now comes the best: **being able to play with Huggy online 👀.**"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "VMc4oOsE0QiZ"
},
"source": [
"## Play with your Huggy 🐕\n",
"\n",
@@ -572,30 +646,30 @@
"- Click on Play with my Huggy model\n",
"\n",
"<img src=\"https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/notebooks/unit-bonus1/load-huggy.jpg\" alt=\"load-huggy\" width=\"100%\">"
],
"metadata": {
"id": "VMc4oOsE0QiZ"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Djs8c5rR0Z8a"
},
"source": [
"1. In step 1, type your username (your username is case sensitive: for instance, my username is ThomasSimonini not thomassimonini or ThOmasImoNInI) and click on the search button.",
"1. In step 1, type your username (your username is case sensitive: for instance, my username is ThomasSimonini not thomassimonini or ThOmasImoNInI) and click on the search button.\n",
"\n",
"2. In step 2, select your model repository.",
"2. In step 2, select your model repository.\n",
"\n",
"3. In step 3, **choose which model you want to replay**:",
"3. In step 3, **choose which model you want to replay**:\n",
" - I have multiple ones, since we saved a model every 500000 timesteps.\n",
" - But since I want the more recent, I choose `Huggy.onnx`\n",
"\n",
"👉 What’s nice **is to try with different models steps to see the improvement of the agent.**"
],
"metadata": {
"id": "Djs8c5rR0Z8a"
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "PI6dPWmh064H"
},
"source": [
"Congrats on finishing this bonus unit!\n",
"\n",
@@ -605,18 +679,15 @@
"\n",
"\n",
"## Keep Learning, Stay awesome 🤗"
],
"metadata": {
"id": "PI6dPWmh064H"
}
]
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"provenance": [],
"include_colab_link": true,
"private_outputs": true,
"include_colab_link": true
"provenance": []
},
"gpuClass": "standard",
"kernelspec": {