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Comments (7)

arnicas avatar arnicas commented on July 17, 2024 5

Agreed, it's opaque how to use this for new documents after training, which went great. Any chance of some more insight into how to apply it?

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duongkstn avatar duongkstn commented on July 17, 2024

Same question !

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kingomalek avatar kingomalek commented on July 17, 2024

That would be Very helpful, I hope you can provide us with such functions

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yilunzhao avatar yilunzhao commented on July 17, 2024

Same question

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Shiro-LK avatar Shiro-LK commented on July 17, 2024

any update ? I have the same question

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460176980 avatar 460176980 commented on July 17, 2024

Same question!

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ydennisy avatar ydennisy commented on July 17, 2024

I am on the same issue - there are various places where you can get a return value which is the size of your topics, which is what you want, from looking at the eval script I have this:

NUM_TOPICS = 128

def predict(normd_bow):
    thetaAvg = torch.zeros(1, NUM_TOPICS)
    sums = normd_bow.sum(1).unsqueeze(1)
    thetaWeightedAvg = torch.zeros(1, NUM_TOPICS)
    theta, _ = model.get_theta(normd_bow)
    thetaAvg += theta.sum(0).unsqueeze(0) / normd_bow.shape[0]
    weighed_theta = sums * theta
    thetaWeightedAvg += weighed_theta.sum(0).unsqueeze(0)
    return thetaWeightedAvg

Created from this code.

EDIT: I have no idea if this is correct!

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