Metadata-Version: 2.1
Name: GraphSTAM
Version: 1.0
Summary: Graph Based Spatio-Temporal Attention Models For Demand Forecasting
Author: Rahul Sinha
Author-email: rahul.sinha@unilever.com
Description-Content-Type: text/markdown

# 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()
```

