class_docstr: 2D Image to Patch Embedding
code: def forward(self, x):
      B, C, H, W = x.shape
      assert (
          H == self.img_size[0] and W == self.img_size[1]
      ), f"Input image size ({H}*{W}) doesn't match model ({self.img_size[0]}*{self.img_size[1]})."
  
      # flatten: [B, C, H, W] -> [B, C, HW]
      # transpose: [B, C, HW] -> [B, HW, C]
      x = self.proj(x).flatten(2).transpose(1, 2)
      x = self.norm(x)
      return x
  
imports: from functools import partial
  from collections import OrderedDict
  import torch
  import torch.nn
label_desc: Use image node_id 2 for calling the PatchEmbed obj's underlying member method code with example usage: obj.forward(x) and returns: x