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import torch
import torch.nn as nn
from tencentpretrain.utils.misc import pooling
class ClsTarget(nn.Module):
"""
Classification Target
"""
def __init__(self, args, vocab_size):
super(ClsTarget, self).__init__()
self.vocab_size = vocab_size
self.hidden_size = args.hidden_size
self.pooling_type = args.pooling
self.linear_1 = nn.Linear(args.hidden_size, args.hidden_size)
self.linear_2 = nn.Linear(args.hidden_size, args.labels_num)
self.softmax = nn.LogSoftmax(dim=-1)
self.criterion = nn.NLLLoss()
def forward(self, memory_bank, tgt, seg):
"""
Args:
memory_bank: [batch_size x seq_length x hidden_size]
tgt: [batch_size]
Returns:
loss: Classification loss.
correct: Number of sentences that are predicted correctly.
"""
output = pooling(memory_bank, seg, self.pooling_type)
output = torch.tanh(self.linear_1(output))
logits = self.linear_2(output)
loss = self.criterion(self.softmax(logits), tgt)
correct = self.softmax(logits).argmax(dim=-1).eq(tgt).sum()
return loss, correct
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