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24 lines
660 B
24 lines
660 B
import numpy
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try:
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from cupy import get_array_module
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except ImportError:
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def get_array_module(*a, **k):
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return numpy
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def categorical_crossentropy(scores, labels):
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xp = get_array_module(scores)
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target = xp.zeros(scores.shape, dtype='float32')
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loss = 0.
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for i in range(len(labels)):
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target[i, int(labels[i])] = 1.
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loss += (1.0-scores[i, int(labels[i])])**2
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return scores - target, loss
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def L1_distance(vec1, vec2, labels, margin=0.2):
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xp = get_array_module(vec1)
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dist = xp.abs(vec1 - vec2).sum(axis=1)
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loss = (dist > margin) - labels
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return (sent1-sent2) * loss, (sent2-sent1) * loss, loss
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