Changelog¶
v0.1.4 (2018-02-18)¶
Fixed¶
Bugs due to use of int32s instead of int64s on Windows (thanks to Roman Yurchak).
Other¶
Added Appveyor for Windows CI (thanks to Roman Yurchak).
v0.1.3 (2017-12-14)¶
Added¶
Goodbooks dataset.
Mixture-of-tastes representations.
Changed¶
Raise ValueError if loss becomes NaN or 0.
Updated to work with PyTorch 0.3.0.
v0.1.2 (2017-09-10)¶
Added¶
spotlight.layers.BloomEmbedding: bloom embedding layers that reduce the number of parameters required by hashing embedding indices into some fixed smaller dimensionality, following Serrà, Joan, and Alexandros Karatzoglou. “Getting deep recommenders fit: Bloom embeddings for sparse binary input/output networks.”sequence_mrr_scorenow accepts an option that excludes previously seen items from scoring.
Changed¶
optimizerarguments is nowoptimizer_func. It accepts a function that takes a single argument (list of model parameters) and return a PyTorch optimizer (thanks to Ethan Rosenthal).fitcalls will resume from previous model state when called repeatedly (Ethan Rosenthal).Updated to work with PyTorch v0.2.0.
Fixed¶
Factorization predict APIs now work as advertised in the documentation.