five

thuerey-group/apebench-scraped

收藏
Hugging Face2024-11-06 更新2025-04-12 收录
下载链接:
https://hf-mirror.com/datasets/thuerey-group/apebench-scraped
下载链接
链接失效反馈
官方服务:
资源简介:
--- license: mit --- # APEBench Scraped A representative subset of datasets created using the [APEBench benchmark suite](https://github.com/tum-pbs/apebench) using version `0.1.0`. ⚠️ Note that [APEBench](https://github.com/tum-pbs/apebench) is designed to procedurally generate all its training and test data. This allows for advanced features like benchmarking approaches with differentiable physics. Hence, there is no need to download this dataset as it can be easily re-generated using APEBench which can be installed via `pip install apebench`. See also [here](https://tum-pbs.github.io/apebench/examples/scrape_datasets/) for how to scrape datasets. ## Download Download without large files ```bash GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:datasets/thuerey-group/apebench-scraped ``` Afterwards, you can inspect the repository and download the files you need. For example, for `1d_diff_adv`: ```bash git lfs install git lfs pull -I "data/1d_diff_adv*" ``` Alternatively, you can download the entire repository with large files (~30GB): ```bash git lfs install git clone git@hf.co:datasets/thuerey-group/apebench-scraped ``` ## Reproduction Obtained via: ```bash conda create -n apebench python=3.12 -y conda activate apebench pip install -U "jax[cuda12]" pip install apebench==0.1.0 ``` Alternatively, you can use the provided `environment.yml` file: ```bash conda env create -f environment.yml conda activate apebench ``` And then executed the following script (also found under `reproduce.py`): ```python import apebench from tqdm import tqdm import os DATA_PATH = "data" os.makedirs(DATA_PATH, exist_ok=True) for config in tqdm(apebench.scraper.CURATION_APEBENCH_V1): apebench.scraper.scrape_data_and_metadata(DATA_PATH, **config) ``` ⚠️ Small️️er variations of the generated data can occur due to different JAX versions, backends (CPU, GPU, TPU), drivers, etc. This might be especially pronounced for the chaotic problems (like KS or Kolmogorov flow). - nvidia driver version: 535.183.01 - cuda version: 12.2 - GPU: RTX 3060
提供机构:
thuerey-group
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作