Set a new boolean flag to words in the vocabulary. The flag_getter function
will be called over the words currently in the vocab, and then applied to new
words as they occur. You’ll then be able to access the flag value on each token,
A function that takes the lexeme text and returns the boolean flag value. Callable[[str],bool]
An integer between 1 and 63 (inclusive), specifying the bit at which the flag will be stored. If -1, the lowest available bit will be chosen. int
The integer ID by which the flag value can be checked. int
Reduce the current vector table to nr_row unique entries. Words mapped to the
discarded vectors will be remapped to the closest vector among those remaining.
For example, suppose the original table had vectors for the words:
['sat', 'cat', 'feline', 'reclined']. If we prune the vector table to, two
rows, we would discard the vectors for “feline” and “reclined”. These words
would then be remapped to the closest remaining vector – so “feline” would have
the same vector as “cat”, and “reclined” would have the same vector as “sat”.
The similarities are judged by cosine. The original vectors may be large, so the
cosines are calculated in minibatches to reduce memory usage.
The number of rows to keep in the vector table. int
Batch of vectors for calculating the similarities. Larger batch sizes might be faster, while temporarily requiring more memory. int
A dictionary keyed by removed words mapped to (string, score) tuples, where string is the entry the removed word was mapped to, and score the similarity score between the two words. Dict[str, Tuple[str,float]]
Retrieve a vector for a word in the vocabulary. Words can be looked up by string
or hash value. If no vectors data is loaded, a ValueError is raised. If minn
is defined, then the resulting vector uses FastText’s
subword features by average over n-grams of orth (introduced in spaCy v2.1).
The hash value of a word, or its unicode string. Union[int,str]
Minimum n-gram length used for FastText’s n-gram computation. Defaults to the length of orth. int
Maximum n-gram length used for FastText’s n-gram computation. Defaults to the length of orth. int
A word vector. Size and shape are determined by the Vocab.vectors instance. numpy.ndarray[ndim=1, dtype=float32]
During serialization, spaCy will export several data fields used to restore
different aspects of the object. If needed, you can exclude them from
serialization by passing in the string names via the exclude argument.