Deep Learning with PyTorch

Creating the network

Let's look at the code and then walk through the code. You may be surprised at how similar the code looks:

class IMDBRnn(nn.Module):        def __init__(self,vocab,hidden_size,n_cat,bs=1,nl=2):        super().__init__()        self.hidden_size = hidden_size        self.bs = bs        self.nl = nl        self.e = nn.Embedding(n_vocab,hidden_size)        self.rnn = nn.LSTM(hidden_size,hidden_size,nl)        self.fc2 = nn.Linear(hidden_size,n_cat)        self.softmax = nn.LogSoftmax(dim=-1)            def forward(self,inp):        bs = inp.size()[1]        if bs != self.bs:            self.bs = bs        e_out = self.e(inp)        h0 = c0 = Variable(e_out.data.new(*(self.nl,self.bs,self.hidden_size)).zero_())        rnn_o,_ = self.rnn(e_out,(h0,c0))         rnn_o = rnn_o[-1]        fc = F.dropout(self.fc2(rnn_o),p=0.8)        return self.softmax(fc)

The