113 lines
4.6 KiB
Markdown
113 lines
4.6 KiB
Markdown
# Setup for VAB-OmniGibson
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## Installation
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1. We have tested on Ubuntu. VAB-OmniGibson requires **11 GB NVIDIA RTX GPU** and NVIDIA GPU driver version >= 450.80.02. For more detailed requirements, please refer to [Isaac Sim 2022.2.0](https://docs.omniverse.nvidia.com/isaacsim/latest/installation/requirements.html).
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2. Besides [docker](https://www.docker.com/), install [NVIDIA container toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) on your machine.
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3. Get pre-built docker image.
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- If you have access to docker hub:
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```bash
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docker pull tianjiezhang/vab_omnigibson:latest
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```
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- Or you can download from ModelScope.
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1. Make sure `git-lfs` is installed.
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2. Download from ModelScope:
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```bash
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git lfs install
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git clone https://www.modelscope.cn/datasets/VisualAgentBench/VAB-OmniGibson-Docker.git
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```
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3. Load the docker image from ModelScope dataset.
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```bash
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docker load -i VAB-OmniGibson-Docker/vab_omnigibson.tar
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```
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4. Download datasets of OmniGibson, VAB-OmniGibson test activities, and related scene files. Note that about 25 GB data will be downloaded to `data/omnigibson`, and make sure you have access to google drive.
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```bash
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python scripts/omnigibson_download.py
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```
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## Get Started
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1. According to your hardware equipment, fill `available_ports` and `available_devices` in the task configuration file `configs/tasks/omnigibson.yaml`.
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- `available_ports`: Please fill in available ports in your machine. Each concurrent docker container requires 1 port for communication with the task server. Ensure that you provide enough ports to accommodate the expected concurrency.
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- `available_devices`: Please fill in GPU IDs and their corresponding capability of concurrency. Each concurrent docker container occupies about **11 GB** memory. Ensure that you provide enough GPU memory to accommodate the expected concurrency.
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2. It's recommended to increase the file change watcher for Linux. See [Omniverse guide](https://docs.omniverse.nvidia.com/dev-guide/latest/linux-troubleshooting.html#to-update-the-watcher-limit) for more details.
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- View the current watcher limit: `cat /proc/sys/fs/inotify/max_user_watches`.
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- Update the watcher limit:
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1. Edit `/etc/sysctl.conf` and add `fs.inotify.max_user_watches=524288` line.
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2. Load the new value: `sudo sysctl -p`.
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**Note: If you manually shut down the task server and assigner, please ensure you also stop the OmniGibson containers to free up the ports!**
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# Setup for VAB-Minecraft
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## Installation
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1. We have tested on Ubuntu. VAB-Minecraft requires at least 4 GB NVIDIA GPU and NVIDIA GPU driver version >= 530.30.02.
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2. Besides [docker](https://www.docker.com/), install [NVIDIA container toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html) on your machine.
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3. Get pre-built docker image.
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- If you have access to docker hub:
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```bash
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docker pull tianjiezhang/vab_minecraft:latest
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```
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- Or you can download from ModelScope.
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1. Make sure `git-lfs` is installed.
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2. Download from ModelScope:
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```bash
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git lfs install
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git clone https://www.modelscope.cn/datasets/VisualAgentBench/VAB-Minecraft.git
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```
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3. Load the docker image from ModelScope dataset.
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```bash
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docker load -i VAB-Minecraft/vab_minecraft.tar
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```
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4. Download weights of Steve-1 to `data/minecraft`. Please make sure you have access to google drive.
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```bash
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python scripts/minecraft_download.py
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```
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## Get Started
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According to your hardware equipment, fill `available_ports` and `available_devices` in the task configuration file `configs/tasks/minecraft.yaml`.
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- `available_ports`: Please fill in available ports in your machine. Each concurrent docker container requires 1 port for communication with the task server. Ensure that you provide enough ports to accommodate the expected concurrency.
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- `available_devices`: Please fill in GPU IDs and their corresponding capability of concurrency. Each concurrent docker container occupies about **3.3 GB** memory. Ensure that you provide enough GPU memory to accommodate the expected concurrency.
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**Note: If you manually shut down the task server and assigner, please ensure you also stop the Minecraft containers to free up the ports!**
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# Setup for VAB-CSS
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TODO |