class_docstr: 3D Patch Merging Layer.
  Args:
      dim (`int`):
          Number of input channels.
      norm_layer (`nn.Module`):
          Normalization layer. Default: nn.LayerNorm
class_docstr_tok: ["3D","Patch","Merging","Layer",".","Args",":","dim","(","`","int","`",")",":","Number","of","input","channels",".","norm_layer","(","`","nn.Module","`",")",":","Normalization","layer",".","Default",":","nn.LayerNorm"]
code: def __init__(self, dim, norm_layer=nn.LayerNorm):
      super().__init__()
      self.dim = dim
      self.reduction = nn.Linear(4 * dim, 2 * dim, bias=False)
      self.norm = norm_layer(4 * dim)
  
file_path: towhee/towhee/models/layers/patch_merging3d.py
imports: import torch
  from torch import nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new PatchMerging3D object from inherited base classes: nn with example: obj = PatchMerging3D(dim, norm_layer)