Can someone tell me why the below “Manual RNN” does not tie out to the “nn.RNN” function?
class RNN(nn.Module):
    def __init__(self, batchSize, inputSize, outputSize):
        super(RNN, self).__init__()
        self.batchSize = batchSize
        self.inputSize = inputSize
        self.hiddenSize = 10
        
        self.rnn = nn.RNN(self.inputSize, self.hiddenSize)
        self.hidden = nn.Linear(self.hiddenSize + self.inputSize, self.hiddenSize)
        self.linear = nn.Linear(self.hiddenSize, outputSize)
        self.tanh = nn.Tanh()
        
    def forward(self, x):
        #x = a single name, as one-hot encoded vector (31 possible chars)
        
        #MANUAL RNN
        hidden = torch.zeros(1, self.hiddenSize)
        for letter in x:
            letter = letter.view(1, -1)
            hidden = hidden.view(1, -1)
            combined = torch.cat( (letter, hidden), dim=1)
            hidden = self.tanh(self.hidden(combined))
        output1 = self.linear(hidden)
        
        #nn.RNN from pytorch
        hidden = torch.zeros(1, self.hiddenSize)
        x = x.view(5, 1, -1)
        hidden = hidden.view(1, 1, -1)
        output, hidden = self.rnn(x, hidden)
        hidden = hidden.view(1, -1)
        output2 = self.linear(hidden)
        
        if (output1 != output2).any():
            print(output1)
            print(output2)
            raise Exception('Manual RNN does not match nn.RNN')
        
        return output, hidden

Result:
tensor([[ 0.0006, -0.1234, -0.1572,  0.3339, -0.2149,  0.0967, -0.0302, -0.0470,
         -0.1969,  0.0827, -0.0481,  0.3200, -0.1252,  0.1596,  0.0969,  0.0946,
          0.3446, -0.1893]], grad_fn=<ThAddmmBackward>)
tensor([[-0.0289, -0.1587, -0.1367,  0.1682, -0.1722,  0.2661,  0.1075, -0.2680,
         -0.1853,  0.1767,  0.0378,  0.2075, -0.1701,  0.1740,  0.2489,  0.0971,
          0.1929, -0.2300]], grad_fn=<ThAddmmBackward>)
Exception: Manual RNN does not match nn.RNN

What am I doing wrong? I tried looking into the underlying code for nn.RNN but the interesting part disappears in their backend function.
Thanks!