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-1.0.tar.gz
(176.9 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-1.0-py3-none-any.whl
(183.1 kB
view details)
File details
Details for the file GraphSTAM-1.0.tar.gz.
File metadata
- Download URL: GraphSTAM-1.0.tar.gz
- Upload date:
- Size: 176.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.9.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
19047e14bd62ffef7ac73b52dd1f4bd4c26563ed374b77d1f35a6b68f8c1441c
|
|
| MD5 |
7b2393c31fdebf88c94aef520335f2f6
|
|
| BLAKE2b-256 |
24fd1171fbc4a05d9e2e3cbbecb60576dfa9fe8aab3230d9ed5c0bea9281dbc8
|
File details
Details for the file GraphSTAM-1.0-py3-none-any.whl.
File metadata
- Download URL: GraphSTAM-1.0-py3-none-any.whl
- Upload date:
- Size: 183.1 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 |
8496bd08703bd9601b4f127cf7c039826f97d602bba6333e358b7c0290c9e850
|
|
| MD5 |
aa626504675aa6ceeac88240406633ff
|
|
| BLAKE2b-256 |
71da5156d13c4097e5629c4196fef578f589e660eb6b983860b48cd64b7e1846
|