Update utils.py
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utils.py
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import torch
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import config
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def categorical_accuracy(preds, y):
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"""
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Returns accuracy per batch, i.e. if you get 8/10 right, this returns 0.8, NOT 8
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"""
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max_preds = preds.argmax(
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dim=1, keepdim=True) # get the index of the max probability
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correct = max_preds.squeeze(1).eq(y)
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return correct.sum() / torch.FloatTensor([y.shape[0]])
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def label_encoder(x):
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label_vec = {"0": 0, "1": 1, "-1": 2}
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return label_vec[x.replace("__label__", "")]
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def label_decoder(x):
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label_vec = { 0:"U", 1:"P", 2:"N"}
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return label_vec[x]
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def label_full_decoder(x):
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label_vec = { 0:"Neutral", 1:"Positive", 2:"Negative"}
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return label_vec[x]
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