code: def forward(self, x):
      x = [s.chunk(2, axis=1) for s in x]
      x1 = [s[0] for s in x]
      x2 = [s[1] for s in x]
  
      x2 = self.cross_resolution_weighting(x2)
      x2 = [dw(s) for s, dw in zip(x2, self.depthwise_convs)]
      x2 = [sw(s) for s, sw in zip(x2, self.spatial_weighting)]
  
      out = [paddle.concat([s1, s2], axis=1) for s1, s2 in zip(x1, x2)]
      out = [channel_shuffle(s, groups=2) for s in out]
      return out
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from numbers import Integral
  from paddle import ParamAttr
  from paddle.regularizer import L2Decay
  from paddle.nn.initializer import Normal, Constant
  from ppdet.core.workspace import register
  from ppdet.modeling.shape_spec import ShapeSpec
  from ppdet.modeling.ops import channel_shuffle
  from ..None import layers
label_desc: Use image node_id 2 for calling the ConditionalChannelWeightingBlock obj's underlying member method code with example usage: obj.forward(x) and returns: out