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28 lines
743 B
Python
28 lines
743 B
Python
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import numpy
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from thinc.api import Model, Unserializable
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def SpacyVectors(vectors) -> Model:
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attrs = {"vectors": Unserializable(vectors)}
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model = Model("spacy_vectors", forward, attrs=attrs)
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return model
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def forward(model, docs, is_train: bool):
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batch = []
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vectors = model.attrs["vectors"].obj
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for doc in docs:
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indices = numpy.zeros((len(doc),), dtype="i")
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for i, word in enumerate(doc):
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if word.orth in vectors.key2row:
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indices[i] = vectors.key2row[word.orth]
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else:
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indices[i] = 0
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batch_vectors = vectors.data[indices]
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batch.append(batch_vectors)
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def backprop(dY):
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return None
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return batch, backprop
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