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Ashutosh-Adhikari
650882fb6e
* Add Reuters option in common.dataset * Add Reuters option in common.dataset * Add HAN model * Add XML-CNN * Add HAN * Add Hierarchical tokenization for Reuters * Add README for HAN * Add XML Readme * Update HAN Readme
29 lines
1.1 KiB
Python
Executable File
29 lines
1.1 KiB
Python
Executable File
import torch
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import torch.nn as nn
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from torch.autograd import Variable
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#from utils import
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import torch.nn.functional as F
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from han.sent_level_rnn import SentLevelRNN
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from han.word_level_rnn import WordLevelRNN
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class HAN(nn.Module):
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def __init__(self, config):
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super(HAN, self).__init__()
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self.dataset = config.dataset
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self.mode = config.mode
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self.word_attention_rnn = WordLevelRNN(config)
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self.sentence_attention_rnn = SentLevelRNN(config)
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def forward(self,x):
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x = x.permute(1,2,0) ## Expected : #sentences, #words, batch size
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num_sentences = x.size()[0]
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word_attentions = None
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for i in range(num_sentences):
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_word_attention = self.word_attention_rnn(x[i,:,:])
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if word_attentions is None:
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word_attentions = _word_attention
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else:
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word_attentions = torch.cat((word_attentions, _word_attention),0)
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return self.sentence_attention_rnn(word_attentions)
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