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31 lines
1.2 KiB
Plaintext
31 lines
1.2 KiB
Plaintext
//- 💫 DOCS > USAGE > VECTORS & SIMILARITY > GPU
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p
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| If you're using a GPU, it's much more efficient to keep the word vectors
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| on the device. You can do that by setting the
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| #[+api("vectors#attributes") #[code Vectors.data]] attribute to a
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| #[code cupy.ndarray] object if you're using spaCy
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| or #[+a("https://chainer.org") Chainer], or a
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| #[code torch.Tensor] object if you're using
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| #[+a("http://pytorch.org") PyTorch]. The #[code data] object just needs
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| to support #[code __iter__] and #[code __getitem__], so if you're using
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| another library such as #[+a("https://www.tensorflow.org") TensorFlow],
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| you could also create a wrapper for your vectors data.
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+code("spaCy, Thinc or Chainer").
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import cupy.cuda
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from spacy.vectors import Vectors
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vector_table = numpy.zeros((3, 300), dtype='f')
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vectors = Vectors([u'dog', u'cat', u'orange'], vector_table)
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with cupy.cuda.Device(0):
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vectors.data = cupy.asarray(vectors.data)
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+code("PyTorch").
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import torch
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from spacy.vectors import Vectors
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vector_table = numpy.zeros((3, 300), dtype='f')
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vectors = Vectors([u'dog', u'cat', u'orange'], vector_table)
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vectors.data = torch.Tensor(vectors.data).cuda(0)
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