This is the Linux app named Jraph whose latest release can be downloaded as v0.0.6.dev0sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Jraph with OnWorks for free.
Sundin ang mga tagubiling ito upang patakbuhin ang app na ito:
- 1. Na-download ang application na ito sa iyong PC.
- 2. Ipasok sa aming file manager https://www.onworks.net/myfiles.php?username=XXXXX kasama ang username na gusto mo.
- 3. I-upload ang application na ito sa naturang filemanager.
- 4. Simulan ang OnWorks Linux online o Windows online emulator o MACOS online emulator mula sa website na ito.
- 5. Mula sa OnWorks Linux OS na kasisimula mo pa lang, pumunta sa aming file manager https://www.onworks.net/myfiles.php?username=XXXX gamit ang username na gusto mo.
- 6. I-download ang application, i-install ito at patakbuhin ito.
MGA SCREENSHOT:
si Jraph
DESCRIPTION:
Jraph (pronounced “giraffe”) is a lightweight JAX library developed by Google DeepMind for building and experimenting with graph neural networks (GNNs). It provides an efficient and flexible framework for representing, manipulating, and training models on graph-structured data. The core of Jraph is the GraphsTuple data structure, which enables users to define graphs with arbitrary node, edge, and global attributes, and to batch variable-sized graphs efficiently for JAX’s just-in-time compilation. The library includes a comprehensive set of utilities for batching, padding, masking, and partitioning graph data, making it ideal for distributed and large-scale GNN experiments. Jraph also comes with a model zoo—a collection of forkable reference implementations of common message-passing GNN architectures, such as Graph Networks, Graph Convolutional Networks, and Graph Attention Networks.
Mga tampok
- Lightweight GraphsTuple data structure for flexible graph representation
- Distributed message-passing support for massive graphs across multiple devices
- Utilities for batching, masking, and padding to handle variable-sized graphs
- Modular model zoo of reusable graph neural network architectures
- Educational Colab tutorials and large-scale dataset examples (e.g., OGBG-MOLPCBA)
- Fully JAX-compatible for jit compilation, pmap parallelization, and scalability
Wika ng Programming
Sawa
Kategorya
This is an application that can also be fetched from https://sourceforge.net/projects/jraph.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.