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Releases: maciejkula/spotlight

Upgrade to PyTorch v1.1.0

08 Sep 10:19
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Update to PyTorch v1.1.0.

Upgrade to PyTorch v0.4.0

20 May 13:32
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Merge pull request #112 from maciejkula/pytorch-v0.4.0

Upgrade to Pytorch v0.4.0

v0.1.4: Merge pull request #97 from maciejkula/bump_version

18 Feb 12:14
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v0.1.3

14 Dec 22:03
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v0.1.3 (2017-12-14)

Added

  • Goodbooks dataset.

Changed

  • Raise ValueError if loss becomes NaN or 0.
  • Updated to work with PyTorch 0.3.0.

v0.1.2

19 Sep 07:23
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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_score now accepts an option that excludes previously seen items from scoring.

Changed

  • optimizer arguments is now optimizer_func. It accepts a function that takes a single argument (list of model parameters) and return a PyTorch optimizer (thanks to Ethan Rosenthal).
  • fit calls 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.

v0.1.1: Merge pull request #19 from maciejkula/bump_0.1.1

19 Jul 22:11
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v0.1.0

28 Jun 21:23
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Remove all install_requires.