The list of every action the model can take.
Export the featurizer's internal parameters to be serialized along the model.
Turn the data returned by handleQuery into an embedding vector. This function is used to expose featurizer variables to the model optimizer for training.
Reimplementing this method is not necessary if your featurizer is not meant to be optimizable through gradient descent. In this case, just return the feature vector directly using the handleQuery method.
Let the featurizer know what action the model has taken.
Load parameters extracted from a JSON-like document.
Redefine a new value for the slot.
Generated using TypeDoc
A slot that stores a categorical value extracted using fuzzy string matching.