From 13ec38ea00e2ed7aa97085999a23785822a14718 Mon Sep 17 00:00:00 2001
From: Filippo Luca Ferretti <102977828+flferretti@users.noreply.github.com>
Date: Wed, 15 May 2024 12:33:41 +0200
Subject: [PATCH] Remove any reference to Colab in examples
---
examples/PD_controller.ipynb | 41 -------------------------------
examples/Parallel_computing.ipynb | 18 +++-----------
examples/README.md | 14 +++--------
3 files changed, 7 insertions(+), 66 deletions(-)
diff --git a/examples/PD_controller.ipynb b/examples/PD_controller.ipynb
index 38be2edf1..d15ef59cc 100644
--- a/examples/PD_controller.ipynb
+++ b/examples/PD_controller.ipynb
@@ -6,10 +6,6 @@
"source": [
"# `JAXsim` Showcase: PD Controller\n",
"\n",
- "\n",
- " \n",
- "\n",
- "\n",
"First, we install the necessary packages and import them."
]
},
@@ -23,14 +19,6 @@
"from IPython.display import clear_output, HTML, display\n",
"import sys\n",
"\n",
- "IS_COLAB = \"google.colab\" in sys.modules\n",
- "\n",
- "# Install JAX and Gazebo\n",
- "if IS_COLAB:\n",
- " !{sys.executable} -m pip install -U -q jaxsim\n",
- " !apt -qq update && apt install -qq --no-install-recommends gazebo\n",
- " clear_output()\n",
- "\n",
"import jax\n",
"import jax.numpy as jnp\n",
"from jaxsim import logging\n",
@@ -141,35 +129,6 @@
"from jaxsim.mujoco.loaders import UrdfToMjcf\n",
"\n",
"\n",
- "if IS_COLAB:\n",
- " if subprocess.run(\"ffmpeg -version\", shell=True).returncode:\n",
- " !command -v ffmpeg >/dev/null || (apt update && apt install -y ffmpeg)\n",
- " clear_output()\n",
- "\n",
- " if subprocess.run(\"nvidia-smi\").returncode:\n",
- " raise RuntimeError(\n",
- " \"Cannot communicate with GPU. \"\n",
- " \"Make sure you are using a GPU Colab runtime. \"\n",
- " \"Go to the Runtime menu and select Choose runtime type.\"\n",
- " )\n",
- "\n",
- " # Add an ICD config so that glvnd can pick up the Nvidia EGL driver.\n",
- " # This is usually installed as part of an Nvidia driver package, but the Colab\n",
- " # kernel doesn't install its driver via APT, and as a result the ICD is missing.\n",
- " # (https://github.com/NVIDIA/libglvnd/blob/master/src/EGL/icd_enumeration.md)\n",
- " NVIDIA_ICD_CONFIG_PATH = \"/usr/share/glvnd/egl_vendor.d/10_nvidia.json\"\n",
- " if not os.path.exists(NVIDIA_ICD_CONFIG_PATH):\n",
- " with open(NVIDIA_ICD_CONFIG_PATH, \"w\") as f:\n",
- " f.write(\n",
- " \"\"\"{\n",
- " \"file_format_version\" : \"1.0.0\",\n",
- " \"ICD\" : {\n",
- " \"library_path\" : \"libEGL_nvidia.so.0\"\n",
- " }\n",
- " }\n",
- " \"\"\"\n",
- " )\n",
- "\n",
"%env MUJOCO_GL=egl\n",
"\n",
"try:\n",
diff --git a/examples/Parallel_computing.ipynb b/examples/Parallel_computing.ipynb
index d06aac3ec..a3fc2ed30 100644
--- a/examples/Parallel_computing.ipynb
+++ b/examples/Parallel_computing.ipynb
@@ -4,11 +4,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# `JAXsim` Showcase: Parallel Simulation of a free-falling body\n",
- "\n",
- "\n",
- " \n",
- ""
+ "# `JAXsim` Showcase: Parallel Simulation of a free-falling body"
]
},
{
@@ -29,16 +25,10 @@
"\n",
"from IPython.display import HTML, clear_output, display\n",
"\n",
- "IS_COLAB = \"google.colab\" in sys.modules\n",
- "\n",
"# Install JAX and Gazebo\n",
- "if IS_COLAB:\n",
- " !{sys.executable} -m pip install -U -q jaxsim\n",
- " !apt -qq update && apt install -qq --no-install-recommends gazebo\n",
- " clear_output()\n",
- "else:\n",
- " # Set environment variable to avoid GPU out of memory errors\n",
- " %env XLA_PYTHON_CLIENT_MEM_PREALLOCATE=false\n",
+ "\n",
+ "# Set environment variable to avoid GPU out of memory errors\n",
+ "%env XLA_PYTHON_CLIENT_MEM_PREALLOCATE=false\n",
"\n",
"import time\n",
"from typing import Dict, Tuple\n",
diff --git a/examples/README.md b/examples/README.md
index c71783ace..8fed061e7 100644
--- a/examples/README.md
+++ b/examples/README.md
@@ -4,23 +4,15 @@ This folder includes a Jupyter Notebook demonstrating the practical usage of JAX
### Examples
-- [PD_controller](https://colab.research.google.com/github/ami-iit/jaxsim/blob/main/examples/PD_controller.ipynb) - A simple example demonstrating the use of JAXsim to simulate a PD controller with gravity compensation for a 2-DOF cartpole.
-- [Parallel_computing](https://colab.research.google.com/github/ami-iit/jaxsim/blob/main/examples/Parallel_computing.ipynb) - An example demonstrating how to simulate vectorized models in parallel using JAXsim.
+- [PD_controller](./PD_controller.ipynb) - A simple example demonstrating the use of JAXsim to simulate a PD controller with gravity compensation for a 2-DOF cartpole.
+- [Parallel_computing](./Parallel_computing.ipynb) - An example demonstrating how to simulate vectorized models in parallel using JAXsim.
> [!TIP]
> Stay tuned for more examples!
## Running the Examples
-To execute these examples utilizing JAXsim with hardware acceleration, there are a couple of options available:
-
-### Option 1: Google Colab (Recommended)
-
-The simplest way to run the examples is by accessing the provided Google Colab notebook link mentioned above. This will enable you to execute the examples in a hosted environment.
-
-### Option 2: Local Execution with `pixi`
-
-For local execution, follow these steps:
+To execute these examples utilizing JAXsim with hardware acceleration, you can use [pixi](https://pixi.sh) to run the examples in a local environment:
1. **Install `pixi`:**