def VariableRecurrentReverse()

in torchmoji/lstm.py [0:0]

• 30 lines of code
• 8 McCabe index (conditional complexity)

def VariableRecurrentReverse(batch_sizes, inner):
    def forward(input, hidden, weight):
        output = []
        input_offset = input.size(0)
        last_batch_size = batch_sizes[-1]
        initial_hidden = hidden
        flat_hidden = not isinstance(hidden, tuple)
        if flat_hidden:
            hidden = (hidden,)
            initial_hidden = (initial_hidden,)
        hidden = tuple(h[:batch_sizes[-1]] for h in hidden)
        for batch_size in reversed(batch_sizes):
            inc = batch_size - last_batch_size
            if inc > 0:
                hidden = tuple(torch.cat((h, ih[last_batch_size:batch_size]), 0)
                               for h, ih in zip(hidden, initial_hidden))
            last_batch_size = batch_size
            step_input = input[input_offset - batch_size:input_offset]
            input_offset -= batch_size

            if flat_hidden:
                hidden = (inner(step_input, hidden[0], *weight),)
            else:
                hidden = inner(step_input, hidden, *weight)
            output.append(hidden[0])

        output.reverse()
        output = torch.cat(output, 0)
        if flat_hidden:
            hidden = hidden[0]
        return hidden, output

    return forward