class_docstr: DownSamples
class_docstr_tok: ["DownSamples"]
code: def __init__(self, in_channels, out_channels):
      super().__init__()
      self.proj = nn.Conv2d(
          in_channels, out_channels, kernel_size=3, stride=2, padding=1
      )
      self.norm = nn.LayerNorm(out_channels)
      self.apply(init_vit_weights)
  
imports: import torch
  from torch import nn
  from timm.models.layers import DropPath
  import numpy
  from towhee.models.wave_vit.wave_vit_utils import DWT2D, IDWT2D
  from towhee.models.utils.init_vit_weights import init_vit_weights
  from towhee.models.layers.mlp import Mlp
label_desc: Use image node_id 1 to create a new DownSamples object from inherited base classes: nn with example: obj = DownSamples(in_channels, out_channels)