scikit

Vectors
class
v2.0 This feature is new and was introduced in spaCy v2.0
Store, save and load word vectors.

Vectors data is kept in the Vectors.data attribute, which should be an instance of numpy.ndarray (for CPU vectors) or cupy.ndarray (for GPU vectors). Multiple keys can be mapped to the same vector, and not all of the rows in the table need to be assigned – so vectors.n_keys may be greater or smaller than vectors.shape[0].

Vectors.__init__
method

Create a new vector store. You can set the vector values and keys directly on initialisation, or supply a shape keyword argument to create an empty table you can add vectors to later.

NameTypeDescription
datandarray[ndim=1, dtype='float32']The vector data.
keysiterableA sequence of keys aligned with the data.
shapetuple Size of the table as (n_entries, n_columns), the number of entries and number of columns. Not required if you're initialising the object with data and keys.
returnsVectorsThe newly created object.

Vectors.__getitem__
method

Get a vector by key. If the key is not found in the table, a KeyError is raised.

NameTypeDescription
keyintThe key to get the vector for.
returnsndarray[ndim=1, dtype='float32']The vector for the key.

Vectors.__setitem__
method

Set a vector for the given key.

NameTypeDescription
keyintThe key to set the vector for.
vectorndarray[ndim=1, dtype='float32']The vector to set.

Vectors.__iter__
method

Iterate over the keys in the table.

NameTypeDescription
yieldsintA key in the table.

Vectors.__len__
method

Return the number of vectors in the table.

NameTypeDescription
returnsintThe number of vectors in the table.

Vectors.__contains__
method

Check whether a key has been mapped to a vector entry in the table.

NameTypeDescription
keyintThe key to check.
returnsboolWhether the key has a vector entry.

Vectors.add
method

Add a key to the table, optionally setting a vector value as well. Keys can be mapped to an existing vector by setting row, or a new vector can be added. When adding unicode keys, keep in mind that the Vectors class itself has no StringStore , so you have to store the hash-to-string mapping separately. If you need to manage the strings, you should use the Vectors via the Vocab class, e.g. vocab.vectors.

NameTypeDescription
keyunicode / intThe key to add.
vectorndarray[ndim=1, dtype='float32']An optional vector to add for the key.
rowintAn optional row number of a vector to map the key to.
returnsintThe row the vector was added to.

Vectors.resize
method

Resize the underlying vectors array. If inplace=True, the memory is reallocated. This may cause other references to the data to become invalid, so only use inplace=True if you're sure that's what you want. If the number of vectors is reduced, keys mapped to rows that have been deleted are removed. These removed items are returned as a list of (key, row) tuples.

NameTypeDescription
shapetuple A (rows, dims) tuple describing the number of rows and dimensions.
inplaceboolReallocate the memory.
returnslistThe removed items as a list of (key, row) tuples.

Vectors.keys
method

A sequence of the keys in the table.

NameTypeDescription
returnsiterableThe keys.

Vectors.values
method

Iterate over vectors that have been assigned to at least one key. Note that some vectors may be unassigned, so the number of vectors returned may be less than the length of the vectors table.

NameTypeDescription
yieldsndarray[ndim=1, dtype='float32']A vector in the table.

Vectors.items
method

Iterate over (key, vector) pairs, in order.

NameTypeDescription
yieldstuple(key, vector) pairs, in order.

Vectors.shape
property

Get (rows, dims) tuples of number of rows and number of dimensions in the vector table.

NameTypeDescription
returnstupleA (rows, dims) pair.

Vectors.size
property

The vector size, i.e. rows * dims.

NameTypeDescription
returnsintThe vector size.

Vectors.is_full
property

Whether the vectors table is full and has no slots are available for new keys. If a table is full, it can be resized using Vectors.resize .

NameTypeDescription
returnsboolWhether the vectors table is full.

Vectors.n_keys
property

Get the number of keys in the table. Note that this is the number of all keys, not just unique vectors. If several keys are mapped are mapped to the same vectors, they will be counted individually.

NameTypeDescription
returnsintThe number of all keys in the table.

Vectors.from_glove
method

Load GloVe vectors from a directory. Assumes binary format, that the vocab is in a vocab.txt, and that vectors are named vectors.{size}.[fd].bin, e.g. vectors.128.f.bin for 128d float32 vectors, vectors.300.d.bin for 300d float64 (double) vectors, etc. By default GloVe outputs 64-bit vectors.

NameTypeDescription
pathunicode / PathThe path to load the GloVe vectors from.

Vectors.to_disk
method

Save the current state to a directory.

NameTypeDescription
pathunicode / Path A path to a directory, which will be created if it doesn't exist. Paths may be either strings or Path-like objects.
**exclude-Named attributes to prevent from being saved.

Vectors.from_disk
method

Loads state from a directory. Modifies the object in place and returns it.

NameTypeDescription
pathunicode / Path A path to a directory. Paths may be either strings or Path-like objects.
returnsVectorsThe modified Vectors object.

Vectors.to_bytes
method

Serialize the current state to a binary string.

NameTypeDescription
**exclude-Named attributes to prevent from being serialized.
returnsbytesThe serialized form of the Vectors object.

Vectors.from_bytes
method

Load state from a binary string.

NameTypeDescription
databytesThe data to load from.
**exclude-Named attributes to prevent from being loaded.
returnsVectorsThe Vectors object.

Attributes

NameTypeDescription
datandarray[ndim=1, dtype='float32'] Stored vectors data. numpy is used for CPU vectors, cupy for GPU vectors.
key2rowdict Dictionary mapping word hashes to rows in the Vectors.data table.
keysndarray[ndim=1, dtype='float32'] Array keeping the keys in order, such that keys[vectors.key2row[key]] == key