code: def forward(self, x):
      h = self.HW[0]
      w = self.HW[1]
      x = x.transpose([0, 2, 1]).reshape([0, self.dim, h, w])
      x = self.local_mixer(x)
      x = x.flatten(2).transpose([0, 2, 1])
      return x
  
imports: from paddle import ParamAttr
  from paddle.nn.initializer import KaimingNormal
  import numpy
  import paddle
  import paddle.nn
  from paddle.nn.initializer import TruncatedNormal, Constant, Normal
label_desc: Use image node_id 2 for calling the ConvMixer obj's underlying member method code with example usage: obj.forward(x) and returns: x