You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
We are excited to announce the final pre-alpha release, PyGOD v0.4, which marks a major milestone in our development. Following bug fixes and minor improvements, we plan to release v1.0. Your feedback and suggestions are appreciated. ⚠️ Please note that this version is NOT forward compatible and some APIs have changed. Here are the major changes in this release:
Enhanced Base Class
Detector: base class for all detectors.
DeepDetector: base class for all deep learning based detectors.
Simplied APIs
Removed predict_proba and predict_confidence.
Use predict(return_prob=True, return_conf=True) instead.
Modularized Detectors
We now introduce multiple modules to improve the code reusability and extendibility.
nn: all base models inherit torch.nn.Module
nn.encoder:
nn.decoder:
nn.functional: loss function, etc.
Also, we changed the name of several modules to improve the clarity.
models→detector
metrics→metric
More Utility Functions
to_edge_score: edge outlier score converter
to_graph_score: graph outlier score converter
init_detector: detector initializer
init_nn: neural network initializer
Updated Requirements
PyGOD now requires Python 3.8+
PyTorch 2.0 and PyG 2.3.0 support
Enabled model compile via detector(compile_model=True) (beta)
And Many More
More comprehensive test coverage (almost 100%)
Reorganized documentation for better readability
Merge MLPAE and GCNAE to GAE
Most of the deep detectors support specifying various backbone from PyG
Retrieve learned embedding from fitted deep detectors with save_emb=True by detector.emb
This discussion was created from the release v0.4.0.
reacted with thumbs up emoji reacted with thumbs down emoji reacted with laugh emoji reacted with hooray emoji reacted with confused emoji reacted with heart emoji reacted with rocket emoji reacted with eyes emoji
-
We are excited to announce the final pre-alpha release, PyGOD v0.4, which marks a major milestone in our development. Following bug fixes and minor improvements, we plan to release v1.0. Your feedback and suggestions are appreciated.⚠️ Please note that this version is NOT forward compatible and some APIs have changed. Here are the major changes in this release:
Enhanced Base Class
Detector
: base class for all detectors.DeepDetector
: base class for all deep learning based detectors.Simplied APIs
predict_proba
andpredict_confidence
.predict(return_prob=True, return_conf=True)
instead.Modularized Detectors
We now introduce multiple modules to improve the code reusability and extendibility.
nn
: all base models inherittorch.nn.Module
nn.encoder
:nn.decoder
:nn.functional
: loss function, etc.Also, we changed the name of several modules to improve the clarity.
models
→detector
metrics
→metric
More Utility Functions
to_edge_score
: edge outlier score converterto_graph_score
: graph outlier score converterinit_detector
: detector initializerinit_nn
: neural network initializerUpdated Requirements
detector(compile_model=True)
(beta)And Many More
MLPAE
andGCNAE
toGAE
save_emb=True
bydetector.emb
This discussion was created from the release v0.4.0.
Beta Was this translation helpful? Give feedback.
All reactions