torchhd.embeddings

Empty(num_embeddings, embedding_dim[, vsa, ...])	Embedding wrapper around empty().
Identity(num_embeddings, embedding_dim[, ...])	Embedding wrapper around identity().
Random(num_embeddings, embedding_dim[, vsa, ...])	Embedding wrapper around random().
Level(num_embeddings, embedding_dim[, vsa, ...])	Embedding wrapper around level().
Thermometer(num_embeddings, embedding_dim[, ...])	Embedding wrapper around thermometer().
Circular(num_embeddings, embedding_dim[, ...])	Embedding wrapper around circular().
Projection(in_features, out_features[, vsa, ...])	Embedding using a random projection matrix.
Sinusoid(in_features, out_features[, vsa, ...])	Embedding using a nonlinear random projection
Density(in_features, out_features[, vsa, ...])	Performs the transformation of input data into hypervectors according to the intRVFL model.
FractionalPower(in_features, out_features[, ...])	Class for fractional power encoding (FPE) method that forms hypervectors for given values, kernel shape, bandwidth, and dimensionality.