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-0.1.6.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-0.1.6-py3-none-any.whl
(183.2 kB
view details)
File details
Details for the file GraphSTAM-0.1.6.tar.gz.
File metadata
- Download URL: GraphSTAM-0.1.6.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 |
e21adf07d0e4e8d684756297f347bffe7bd8b65437cfc56aa1828b39d65433eb
|
|
| MD5 |
df5ebbadff1a4de490422a436b08b853
|
|
| BLAKE2b-256 |
2ca523d62f82e1930f4abe7e00f44931578281e527694087d0290fd050f74855
|
File details
Details for the file GraphSTAM-0.1.6-py3-none-any.whl.
File metadata
- Download URL: GraphSTAM-0.1.6-py3-none-any.whl
- Upload date:
- Size: 183.2 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 |
58da3b56fb763eac5c6c6e890b7dc1ed6f3dcba1eaefd8200bebf945b6355a8a
|
|
| MD5 |
8e8fce0e5e504b3ef25701842a5c2dd8
|
|
| BLAKE2b-256 |
84e1259f8c006510913054991aefe356a45980ae053d09e158a3aa4439012571
|