code: def __init__(
      self, dim: int, norm_layer=layers.LayerNormalization, name=None
  ):
      super(PatchMerging, self).__init__(name=name)
      self.dim = dim
      self.reduction = layers.Dense(
          2 * dim,
          use_bias=False,
          kernel_initializer=initializers.TruncatedNormal(stddev=0.02),
          name="reduction",
      )
      self.norm = norm_layer(epsilon=1e-6, name="norm")
  
imports: import tensorflow
  from tensorflow.keras import Model, layers, initializers
  import numpy
label_desc: Use image node_id 1 to create a new PatchMerging object from inherited base classes: layers with example: obj = PatchMerging(dim, norm_layer, name)