def METHOD_NAME(self, inputs):
    normal_hardwts = nn.functional.softmax(self.arch_normal_parameters, dim=-1)
    reduce_hardwts = nn.functional.softmax(self.arch_reduce_parameters, dim=-1)
    s0 = s1 = self.stem(inputs)
    for i, cell in enumerate(self.cells):
        # [TODO]
        raise NotImplementedError
        if cell.reduction:
            hardwts, index = reduce_hardwts, reduce_index
        else:
            hardwts, index = normal_hardwts, normal_index
        s0, s1 = s1, cell.forward_gdas(s0, s1, hardwts, index)
    out = self.lastact(s1)
    out = self.global_pooling(out)
    out = out.view(out.size(0), -1)
    logits = self.classifier(out)
    return out, logits