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Update Vectors API docs
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@ -5,46 +5,47 @@ include ../_includes/_mixins
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p
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| Vectors data is kept in the #[code Vectors.data] attribute, which should
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| be an instance of #[code numpy.ndarray] (for CPU vectors) or
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| #[code cupy.ndarray] (for GPU vectors).
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| #[code cupy.ndarray] (for GPU vectors). Multiple keys can be mapped to
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| the same vector, and not all of the rows in the table need to be
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| assigned – so #[code vectors.n_keys] may be greater or smaller than
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| #[code vectors.shape[0]].
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+h(2, "init") Vectors.__init__
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+tag method
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p
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| Create a new vector store. To keep the vector table empty, pass
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| #[code width=0]. You can also create the vector table and add
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| vectors one by one, or set the vector values directly on initialisation.
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| Create a new vector store. You can set the vector values and keys
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| directly on initialisation, or supply a #[code shape] keyword argument
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| to create an empty table you can add vectors to later.
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+aside-code("Example").
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from spacy.vectors import Vectors
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from spacy.strings import StringStore
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empty_vectors = Vectors(StringStore())
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empty_vectors = Vectors(shape=(10000, 300))
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vectors = Vectors([u'cat'], width=300)
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vectors[u'cat'] = numpy.random.uniform(-1, 1, (300,))
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vector_table = numpy.zeros((3, 300), dtype='f')
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vectors = Vectors(StringStore(), data=vector_table)
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data = numpy.zeros((3, 300), dtype='f')
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keys = [u'cat', u'dog', u'rat']
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vectors = Vectors(data=data, keys=keys)
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code strings]
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+cell #[code StringStore] or list
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+cell
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| List of strings, or a #[+api("stringstore") #[code StringStore]]
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| that maps strings to hash values, and vice versa.
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+row
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+cell #[code width]
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+cell int
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+cell Number of dimensions.
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+row
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+cell #[code data]
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+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
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+cell #[code.u-break ndarray[ndim=1, dtype='float32']]
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+cell The vector data.
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+row
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+cell #[code keys]
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+cell iterable
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+cell A sequence of keys aligned with the data.
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+row
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+cell #[code shape]
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+cell tuple
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+cell
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| Size of the table as #[code (n_entries, n_columns)], the number
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| of entries and number of columns. Not required if you're
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| initialising the object with #[code data] and #[code keys].
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+row("foot")
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+cell returns
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+cell #[code Vectors]
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@ -54,97 +55,92 @@ p
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+tag method
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p
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| Get a vector by key. If key is a string, it is hashed to an integer ID
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| using the #[code Vectors.strings] table. If the integer key is not found
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| in the table, a #[code KeyError] is raised.
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| Get a vector by key. If the key is not found in the table, a
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| #[code KeyError] is raised.
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+aside-code("Example").
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vectors = Vectors(StringStore(), 300)
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vectors.add(u'cat', numpy.random.uniform(-1, 1, (300,)))
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cat_vector = vectors[u'cat']
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cat_id = nlp.vocab.strings[u'cat']
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cat_vector = nlp.vocab.vectors[cat_id]
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assert cat_vector == nlp.vocab[u'cat'].vector
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code key]
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+cell unicode / int
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+cell int
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+cell The key to get the vector for.
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+row
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+cell returns
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+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
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+cell #[code.u-break ndarray[ndim=1, dtype='float32']]
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+cell The vector for the key.
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+h(2, "setitem") Vectors.__setitem__
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+tag method
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p
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| Set a vector for the given key. If key is a string, it is hashed to an
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| integer ID using the #[code Vectors.strings] table.
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| Set a vector for the given key.
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+aside-code("Example").
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vectors = Vectors(StringStore(), 300)
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vectors[u'cat'] = numpy.random.uniform(-1, 1, (300,))
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cat_id = nlp.vocab.strings[u'cat']
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vector = numpy.random.uniform(-1, 1, (300,))
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nlp.vocab.vectors[cat_id] = vector
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code key]
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+cell unicode / int
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+cell int
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+cell The key to set the vector for.
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+row
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+cell #[code vector]
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+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
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+cell #[code.u-break ndarray[ndim=1, dtype='float32']]
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+cell The vector to set.
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+h(2, "iter") Vectors.__iter__
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+tag method
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p Yield vectors from the table.
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p Iterate over the keys in the table.
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+aside-code("Example").
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vector_table = numpy.zeros((3, 300), dtype='f')
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vectors = Vectors(StringStore(), vector_table)
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for vector in vectors:
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print(vector)
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for key in nlp.vocab.vectors:
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print(key, nlp.vocab.strings[key])
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+table(["Name", "Type", "Description"])
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+row("foot")
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+cell yields
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+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
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+cell A vector from the table.
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+cell int
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+cell A key in the table.
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+h(2, "len") Vectors.__len__
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+tag method
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p Return the number of vectors that have been assigned.
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p Return the number of vectors in the table.
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+aside-code("Example").
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vector_table = numpy.zeros((3, 300), dtype='f')
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vectors = Vectors(StringStore(), vector_table)
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vectors = Vectors(shape=(3, 300))
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assert len(vectors) == 3
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+table(["Name", "Type", "Description"])
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+row("foot")
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+cell returns
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+cell int
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+cell The number of vectors in the data.
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+cell The number of vectors in the table.
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+h(2, "contains") Vectors.__contains__
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+tag method
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p
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| Check whether a key has a vector entry in the table. If key is a string,
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| it is hashed to an integer ID using the #[code Vectors.strings] table.
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| Check whether a key has been mapped to a vector entry in the table.
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+aside-code("Example").
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vectors = Vectors(StringStore(), 300)
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vectors.add(u'cat', numpy.random.uniform(-1, 1, (300,)))
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assert u'cat' in vectors
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cat_id = nlp.vocab.strings[u'cat']
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nlp.vectors.add(cat_id, numpy.random.uniform(-1, 1, (300,)))
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assert cat_id in vectors
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code key]
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+cell unicode / int
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+cell int
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+cell The key to check.
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+row("foot")
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@ -156,13 +152,20 @@ p
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+tag method
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p
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| Add a key to the table, optionally setting a vector value as well. If
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| key is a string, it is hashed to an integer ID using the
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| #[code Vectors.strings] table.
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| Add a key to the table, optionally setting a vector value as well. Keys
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| can be mapped to an existing vector by setting #[code row], or a new
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| vector can be added. When adding unicode keys, keep in mind that the
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| #[code Vectors] class itself has no
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| #[+api("stringstore") #[code StringStore]], so you have to store the
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| hash-to-string mapping separately. If you need to manage the strings,
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| you should use the #[code Vectors] via the
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| #[+api("vocab") #[code Vocab]] class, e.g. #[code vocab.vectors].
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+aside-code("Example").
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vectors = Vectors(StringStore(), 300)
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vectors.add(u'cat', numpy.random.uniform(-1, 1, (300,)))
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vector = numpy.random.uniform(-1, 1, (300,))
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cat_id = nlp.vocab.strings[u'cat']
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nlp.vocab.vectors.add(cat_id, vector=vector)
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nlp.vocab.vectors.add(u'dog', row=0)
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+table(["Name", "Type", "Description"])
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+row
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@ -172,25 +175,66 @@ p
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+row
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+cell #[code vector]
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+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
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+cell An optional vector to add.
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+cell #[code.u-break ndarray[ndim=1, dtype='float32']]
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+cell An optional vector to add for the key.
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+row
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+cell #[code row]
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+cell int
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+cell An optional row number of a vector to map the key to.
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+row("foot")
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+cell returns
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+cell int
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+cell The row the vector was added to.
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+h(2, "keys") Vectors.keys
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+tag method
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p A sequence of the keys in the table.
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+aside-code("Example").
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for key in nlp.vocab.vectors.keys():
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print(key, nlp.vocab.strings[key])
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+table(["Name", "Type", "Description"])
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+row("foot")
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+cell returns
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+cell iterable
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+cell The keys.
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+h(2, "values") Vectors.values
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+tag method
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p
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| Iterate over vectors that have been assigned to at least one key. Note
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| that some vectors may be unassigned, so the number of vectors returned
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| may be less than the length of the vectors table.
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+aside-code("Example").
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for vector in nlp.vocab.vectors.values():
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print(vector)
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+table(["Name", "Type", "Description"])
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+row("foot")
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+cell yields
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+cell #[code.u-break ndarray[ndim=1, dtype='float32']]
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+cell A vector in the table.
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+h(2, "items") Vectors.items
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+tag method
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p Iterate over #[code (string key, vector)] pairs, in order.
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p Iterate over #[code (key, vector)] pairs, in order.
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+aside-code("Example").
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vectors = Vectors(StringStore(), 300)
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vectors.add(u'cat', numpy.random.uniform(-1, 1, (300,)))
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for key, vector in vectors.items():
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print(key, vector)
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for key, vector in nlp.vocab.vectors.items():
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print(key, nlp.vocab.strings[key], vector)
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+table(["Name", "Type", "Description"])
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+row("foot")
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+cell yields
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+cell tuple
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+cell #[code (string key, vector)] pairs, in order.
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+cell #[code (key, vector)] pairs, in order.
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+h(2, "shape") Vectors.shape
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+tag property
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@ -200,7 +244,7 @@ p
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| dimensions in the vector table.
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+aside-code("Example").
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vectors = Vectors(StringStore(), 300)
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vectors = Vectors(shape(1, 300))
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vectors.add(u'cat', numpy.random.uniform(-1, 1, (300,)))
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rows, dims = vectors.shape
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assert rows == 1
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@ -212,6 +256,59 @@ p
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+cell tuple
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+cell A #[code (rows, dims)] pair.
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+h(2, "size") Vectors.size
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+tag property
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p The vector size, i.e. #[code rows * dims].
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+aside-code("Example").
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vectors = Vectors(shape=(500, 300))
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assert vectors.size == 150000
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+table(["Name", "Type", "Description"])
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+row("foot")
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+cell returns
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+cell int
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+cell The vector size.
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+h(2, "is_full") Vectors.is_full
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+tag property
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p
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| Whether the vectors table is full and has no slots are available for new
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| keys. If a table is full, it can be resized using
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| #[+api("vectors#resize") #[code Vectors.resize]].
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+aside-code("Example").
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vectors = Vectors(shape=(1, 300))
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vectors.add(u'cat', numpy.random.uniform(-1, 1, (300,)))
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assert vectors.is_full
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+table(["Name", "Type", "Description"])
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+row("foot")
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+cell returns
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+cell bool
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+cell Whether the vectors table is full.
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+h(2, "n_keys") Vectors.n_keys
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+tag property
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p
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| Get the number of keys in the table. Note that this is the number of
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| #[em all] keys, not just unique vectors. If several keys are mapped
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| are mapped to the same vectors, they will be counted individually.
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+aside-code("Example").
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vectors = Vectors(shape=(10, 300))
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assert len(vectors) == 10
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assert vectors.n_keys == 0
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+table(["Name", "Type", "Description"])
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+row("foot")
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+cell returns
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+cell int
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+cell The number of all keys in the table.
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+h(2, "from_glove") Vectors.from_glove
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+tag method
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| float32 vectors, #[code vectors.300.d.bin] for 300d float64 (double)
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| vectors, etc. By default GloVe outputs 64-bit vectors.
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+aside-code("Example").
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vectors = Vectors()
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vectors.from_glove('/path/to/glove_vectors')
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code path]
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@ -323,7 +424,7 @@ p Load state from a binary string.
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code data]
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+cell #[code numpy.ndarray] / #[code cupy.ndarray]
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+cell #[code.u-break ndarray[ndim=1, dtype='float32']]
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+cell
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| Stored vectors data. #[code numpy] is used for CPU vectors,
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| #[code cupy] for GPU vectors.
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@ -337,7 +438,7 @@ p Load state from a binary string.
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+row
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+cell #[code keys]
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+cell #[code numpy.ndarray]
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+cell #[code.u-break ndarray[ndim=1, dtype='float32']]
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+cell
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| Array keeping the keys in order, such that
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| #[code keys[vectors.key2row[key]] == key]
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