Skip to main content

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


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

GraphSTAM-1.2.tar.gz (210.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

GraphSTAM-1.2-py3-none-any.whl (217.9 kB view details)

Uploaded Python 3

File details

Details for the file GraphSTAM-1.2.tar.gz.

File metadata

  • Download URL: GraphSTAM-1.2.tar.gz
  • Upload date:
  • Size: 210.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for GraphSTAM-1.2.tar.gz
Algorithm Hash digest
SHA256 ecddc22c164af2a243a87bc5785643f2fbb61d85965d6f3b7bb3de9c1ab7b5cf
MD5 4ae2a7b570e4b9b949d525affb21f8a9
BLAKE2b-256 92dbee937f0ee5435beebd99b16b610eedaa810e558d79fb0e81133f84b7b7e6

See more details on using hashes here.

File details

Details for the file GraphSTAM-1.2-py3-none-any.whl.

File metadata

  • Download URL: GraphSTAM-1.2-py3-none-any.whl
  • Upload date:
  • Size: 217.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for GraphSTAM-1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 ad4f5ffec10e88fbfeb193766d83d3b750a21b204e0397082a9854620ae66134
MD5 2adb9e5a9c9334728090c28fd180e3e4
BLAKE2b-256 377d7e08c1307402d60e40594dfd5932bfde88eb58eb332aec8f40c507bcc772

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page