class_docstr: Image to Patch Embedding
  Args:
      img_size (int): Image size.  Default: 224.
      patch_size (int): Patch token size. Default: 4.
      in_chans (int): Number of input image channels. Default: 3.
      embed_dim (int): Number of linear projection output channels. Default: 96.
      norm_layer (nn.Layer, optional): Normalization layer. Default: None
class_docstr_tok: ["Image","to","Patch","Embedding","Args",":","img_size","(","int",")",":","Image","size",".","Default",":","224.","patch_size","(","int",")",":","Patch","token","size",".","Default",":","4.","in_chans","(","int",")",":","Number","of","input","image","channels",".","Default",":","3.","embed_dim","(","int",")",":","Number","of","linear","projection","output","channels",".","Default",":","96.","norm_layer","(","nn.Layer",",","optional",")",":","Normalization","layer",".","Default",":","None"]
code: def forward(self, x):
      x = x.flatten(2).transpose((0, 2, 1))  # B Ph*Pw C
      if self.norm is not None:
          x = self.norm(x)
      return x
  
imports: import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
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