How to use the darts.model_search.MixedOp function in darts

def __init__(self, C, stride):
    super(MixedOp, self).__init__()
    self._ops = nn.ModuleList()
    for primitive in PRIMITIVES:
      op = OPS[primitive](C, stride, False)
      if 'pool' in primitive:
        op = nn.Sequential(op, nn.BatchNorm2d(C, affine=False))
      self._ops.append(op)

self.reduction = reduction

    if reduction_prev:
      self.preprocess0 = FactorizedReduce(C_prev_prev, C, affine=False)
    else:
      self.preprocess0 = ReLUConvBN(C_prev_prev, C, 1, 1, 0, affine=False)
    self.preprocess1 = ReLUConvBN(C_prev, C, 1, 1, 0, affine=False)
    self._steps = steps
    self._multiplier = multiplier

    self._ops = nn.ModuleList()
    self._bns = nn.ModuleList()
    for i in range(self._steps):
      for j in range(2+i):
        stride = 2 if reduction and j < 2 else 1
        op = MixedOp(C, stride)
        self._ops.append(op)