v0.4.1

Added

• New function ReleaseMatrix to packages mat32 and mat64.
• New methods to Matrix interface, from mat32 and mat64: Minimum, Maximum, MulT, Inverse, DoNonZero. However, the implementation on sparse matrices is not implemented yet (it always panics).

Changed

• Prefer handling Matrix interface values over specific Dense or Sparse matrices, also avoiding unnecessary type casts. Relevant changes to the public API are listed below.
  • mat(32|64).Stack function's arguments and returned value are now Matrix interfaces, instead of explicit Dense matrices.
  • Dense.Minimum and Dense.Maximum, from packages mat32 and mat64, return a Matrix interface, instead of a specific Dense type.
  • The return values of fofe.EncodeDense, fofe.Encode, and fofe.BiEncode are slices of Matrix values, instead of Dense or Sparse.
  • The z argument of the function fofe.Decode is of type Matrix, instead of Dense.
  • ml.optimizers.de (Differential Evolution optimizer) API was changed handling Matrix values, instead of specific Dense matrices. Changes include: Member.TargetVector, Member.DonorVector, ScoredVector.Vector, the vector argument of NewMember function, the solution argument of score and validate functions passed to NewOptimizer.
  • PositionalEncoder.Cache and AxialPositionalEncoder.Cache are slices of Matrix, instead of slices of Dense.
  • AxialPositionalEncoder.EncodingAt returns a Matrix value, instead of Dense.
  • nn.DumpParamsVector returns a Matrix value, instead of Dense.
  • The vector argument of the function nn.LoadParamsVector is a Matrix, instead of Dense.
  • The value argument of the method embeddings.Model.SetEmbedding is of type Matrix, instead of Dense.
  • The type of the struct field evolvingembeddings.WordVectorPair.Vector is Matrix, instead of Dense.