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task5困惑度计算

想问一下task5中的perplexity困惑度该如何计算啊?好像没看到代码里有这方面的计算

task3 参考目录错误

在最新的 2020/04/29 版本中, 注意力对应邱老师的<<神经网络和深度学习>>第 8 章

task 3 p_mask h_mask 定义错误

local inference

p_mask, h_mask = (p != 1).long(), (h != 1).long() # TODO: 这里是不是写错了 p != 0
m_p, m_h = self.inference(p_, h_, p_mask, h_mask) # m_p = m_h = [256,50,2400]

p_mask, h_mask = (p != 0).long(), (h != 0).long() 因为填充值默认是0

task2中评估似乎有问题吧

在task2中是不是对模型更新了,不应该将loss反向传播回去吧。如果传输回去,评估时得到的loss是已经使用了评估数据训练过的模型。

运行环境

楼主,可否把你的运行环境展示出来,方便运行代码的时候配置相应的环境

生成语句的问题

大佬你好,我想问一下你使用过邱老师提供的那个数据集吗?我使用那个数据集后,随机生成句子的时候总是生成像这种字符,请问你能给我提供一点点建议吗,非常感谢。

Small mistake in task 2

Though it may be not worth mentioning... Just for reminder, if anyone wants to run task2, just modify the line 81 in torch_train.py and DELETE THE WORD "OPTIMIZER".

task4有bug

Traceback (most recent call last):
File "main.py", line 127, in
cn.train()
File "main.py", line 71, in train
loss = model.log_likelihood(X,y)
File "/content/drive/My Drive/fudanlp/nlp-beginner-finish-master/task4/model/LSTM_CRF.py", line 40, in log_likelihood
x = x.transpose(0,1)
IndexError: Dimension out of range (expected to be in range of [-1, 0], but got 1)

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