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import torch |
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import torch.nn as nn |
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import torch.nn.functional as F |
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from model.head.abstract_head import AbstractHead |
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from data.parser.to_mrp.sequential_parser import SequentialParser |
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from utility.cross_entropy import cross_entropy |
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class SequentialHead(AbstractHead): |
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def __init__(self, dataset, args, initialize): |
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config = { |
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"label": True, |
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"edge presence": False, |
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"edge label": False, |
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"anchor": True, |
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"source_anchor": True, |
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"target_anchor": True |
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} |
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super(SequentialHead, self).__init__(dataset, args, config, initialize) |
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self.parser = SequentialParser(dataset) |
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