dmlc--dgl
xiang song(charlie.song)
165d453806
Add noting that the PinSage model example under example/pytorch/recommendation only work with Python 3.6+ as its dataset loader depends on stanfordnlp package which work only with Python 3.6+.
PinSage model
NOTE: this version is not using NodeFlow yet.
This example only work with Python 3.6+
First, download and extract from https://dgl.ai.s3.us-east-2.amazonaws.com/dataset/ml-1m.tar.gz
One can then run the following to train PinSage on MovieLens-1M:
python3 train.py --opt Adam --lr 1e-3 --sched none --sgd-switch 25
One can also incorporate user and movie features into training:
python3 train.py --opt Adam --lr 1e-3 --sched none --sgd-switch 25 --use-feature
Currently, performance of PinSage on MovieLens-1M has the best mean reciprocal rank of 0.032298±0.048078 on validation (and 0.033695±0.051963 on test set for the same model). The Implicit Factorization Model from Spotlight has a 0.034572±0.041653 on the test set.