ai.djl.modality.nlp.embedding

Interface WordEmbedding

All Known Implementing Classes:

TrainableWordEmbedding

public interface WordEmbedding

A class to manage 1-D NDArray representations of words.

A word embedding maps words to a NDArray that attempts to represent the key ideas in the words. Each of the values in the dimension can represent different pieces of meaning such as young-old, object-living, etc.

These word embeddings can be used in two different ways in models. First, they can be used purely for preprocessing the model. In this case, it is a requirement for most models that use text as an input. The model is not trained. For this use case, use embedWord(NDManager, String).

In the second option, the embedding can be trained using the standard deep learning techniques to better handle the current dataset. For this case, you need two methods. First, call preprocessWordToEmbed(String) within your dataset. Then, the first step in your model should be to call embedWord(NDManager, long).

Method Summary

Modifier and Type	Method and Description
NDArray	embedWord(NDArray index) Embeds the word after preprocessed using preprocessWordToEmbed(String).
default NDArray	embedWord(NDManager manager, long index) Embeds the word after preprocessed using preprocessWordToEmbed(String).
default NDArray	embedWord(NDManager manager, java.lang.String word) Embeds a word.
long	preprocessWordToEmbed(java.lang.String word) Pre-processes the word to embed into an array to pass into the model.
java.lang.String	unembedWord(NDArray word) Returns the closest matching word for the given index.
boolean	vocabularyContains(java.lang.String word) Returns whether an embedding exists for a word.

Method Detail

vocabularyContains

boolean vocabularyContains(java.lang.String word)

Returns whether an embedding exists for a word.

Parameters:

word - the word to check

Returns:

true if an embedding exists

preprocessWordToEmbed

long preprocessWordToEmbed(java.lang.String word)

Pre-processes the word to embed into an array to pass into the model.

Make sure to call embedWord(NDManager, long) after this.

Parameters:

word - the word to embed

Returns:

the word that is ready to embed

embedWord

default NDArray embedWord(NDManager manager,
                          java.lang.String word)
                   throws EmbeddingException

Embeds a word.

Parameters:

manager - the manager for the embedding array

word - the word to embed

Returns:

the embedded word

Throws:

EmbeddingException - if there is an error while trying to embed

embedWord

default NDArray embedWord(NDManager manager,
                          long index)
                   throws EmbeddingException

Embeds the word after preprocessed using preprocessWordToEmbed(String).

Parameters:

manager - the manager for the embedding array

index - the index of the word to embed

Returns:

the embedded word

Throws:

EmbeddingException - if there is an error while trying to embed

embedWord

NDArray embedWord(NDArray index)
           throws EmbeddingException

Embeds the word after preprocessed using preprocessWordToEmbed(String).

Parameters:

index - the index of the word to embed

Returns:

the embedded word

Throws:

EmbeddingException - if there is an error while trying to embed

unembedWord

java.lang.String unembedWord(NDArray word)

Returns the closest matching word for the given index.

Parameters:

word - the word embedding to find the matching string word for.

Returns:

a word similar to the passed in embedding