class_docstr: Image to Patch Embedding
      
class_docstr_tok: ["Image","to","Patch","Embedding"]
code: def forward(self, x, **kwargs):
      B, C, H, W = x.shape
      # FIXME look at relaxing size constraints
      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]})."
      x = self.proj(x).flatten(2).transpose(1, 2)
      return x
  
imports: import math
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from timm.models.layers import drop_path, to_2tuple, trunc_normal_
  from timm.models.registry import register_model
  from transformers import CLIPImageProcessor, CLIPVisionConfig
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