Differentiable PDE solving framework for machine learning
Project description
PhiFlow
Homepage
Documentation
API
Demos
PhiFlow is an open-source simulation toolkit built for optimization and machine learning applications. It is written mostly in Python and can be used with NumPy, TensorFlow or PyTorch. The close integration with machine learning frameworks allows it to leverage their automatic differentiation functionality, making it easy to build end-to-end differentiable functions involving both learning models and physics simulations.
Installation
See the installation Instructions. To install the latest stable version of PhiFlow:
$ pip install phiflow dash plotly imageio
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file phiflow-2.0.1.tar.gz.
File metadata
- Download URL: phiflow-2.0.1.tar.gz
- Upload date:
- Size: 2.8 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.24.0 setuptools/49.6.0.post20200814 requests-toolbelt/0.9.1 tqdm/4.57.0 CPython/3.8.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8de4a365b00c642d3b333a971e436d3a6c829ac3b80f11aa64e5e8173c70b2be
|
|
| MD5 |
865fc0269fe01949426671a9cdd5bda4
|
|
| BLAKE2b-256 |
869d2e3f9413a210fc9d98d240061dacfe89c5113d9b1da0c3b1860ee0aa7adc
|
