Initialization

Embedding weight initialization routines.

Functions

xavier_uniform_(tensor[, gain])	Initialize weights of the tensor similarly to Glorot/Xavier initialization.
xavier_normal_(tensor[, gain])	Initialize weights of the tensor similarly to Glorot/Xavier initialization.
init_phases(x)	Generate random phases between 0 and \(2\pi\).

Classes

PretrainedInitializer(tensor)	Initialize tensor with pretrained weights.
LabelBasedInitializer(labels[, encoder, ...])	An initializer using pretrained models from the transformers library to encode labels.
WeisfeilerLehmanInitializer(*[, ...])	An initializer based on an encoding of categorical colors from the Weisfeiler-Lehman algorithm.
RandomWalkPositionalEncodingInitializer(*[, ...])	Initialize nodes via random-walk positional encoding.

Variables

xavier_uniform_norm_	A class representing the composition of several functions.
xavier_normal_norm_	A class representing the composition of several functions.
uniform_norm_	A class representing the composition of several functions.
uniform_norm_p1_	A class representing the composition of several functions.
normal_norm_	A class representing the composition of several functions.
initializer_resolver	A resolver for initializers, including elements from pykeen.nn.init

Class Inheritance Diagram