def Recurrent()

in torchmoji/lstm.py [0:0]

• 12 lines of code
• 5 McCabe index (conditional complexity)

def Recurrent(inner, reverse=False):
    def forward(input, hidden, weight):
        output = []
        steps = range(input.size(0) - 1, -1, -1) if reverse else range(input.size(0))
        for i in steps:
            hidden = inner(input[i], hidden, *weight)
            # hack to handle LSTM
            output.append(hidden[0] if isinstance(hidden, tuple) else hidden)

        if reverse:
            output.reverse()
        output = torch.cat(output, 0).view(input.size(0), *output[0].size())

        return hidden, output

    return forward