Graph Based Spatio-Temporal Attention Models For Demand Forecasting
Project description
GraphSTAM
Graph Based Spatio-Temporal Attention Models
Note: The current implementation works for GPU (CUDA) enabled machines. To run on CPU, install the following dependencies manually:
pip install torch --index-url https://download.pytorch.org/whl/cpu
pip install torch-geometric
# for latest PyG version, install from master: pip install git+https://github.com/pyg-team/pytorch_geometric.git
pip install torch_scatter torch_sparse -f https://data.pyg.org/whl/torch-2.0.0+cpu.html
For usage guide, run:
import graphstam
graphstam.usage()
Project details
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
GraphSTAM-1.1.tar.gz
(208.8 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
GraphSTAM-1.1-py3-none-any.whl
(216.1 kB
view details)
File details
Details for the file GraphSTAM-1.1.tar.gz.
File metadata
- Download URL: GraphSTAM-1.1.tar.gz
- Upload date:
- Size: 208.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
6428e67f1dd5fc385178e3011ba2bb4dac734dacfcbca5e2ee2fbd85d273e2f0
|
|
| MD5 |
1b1200e417288d98e40cb6366531f53c
|
|
| BLAKE2b-256 |
109cea3d347baa5c3ae7d7f83fe8141bed570e43b2984c2943dd95cd7375f939
|
File details
Details for the file GraphSTAM-1.1-py3-none-any.whl.
File metadata
- Download URL: GraphSTAM-1.1-py3-none-any.whl
- Upload date:
- Size: 216.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a1d355d4556773d377d13286c6086f5c8ba9c8c9f34f6651b1235cf389d5028c
|
|
| MD5 |
cdf7cb32a9deb04aa9c0d66ab6c2bf81
|
|
| BLAKE2b-256 |
2958e7a7409079be0d0721a70596cfe74a4ee0565d8427b8006dcb1cf2c3dc62
|