code: def __init__(
      self, img_size=108, patch_size=9, in_channels=3, embed_dim=768
  ):
      super().__init__()
      img_size = to_2tuple(img_size)
      patch_size = to_2tuple(patch_size)
      num_patches = (img_size[1] // patch_size[1]) * (
          img_size[0] // patch_size[0]
      )
      self.img_size = img_size
      self.patch_size = patch_size
      self.num_patches = num_patches
      self.proj = nn.Conv2d(
          in_channels,
          embed_dim,
          kernel_size=patch_size,
          stride=patch_size,
      )
  
imports: import torch
  import torch.nn
  from timm.models.layers import DropPath, to_2tuple, trunc_normal_
  from typing import Optional, Callable
label_desc: Use image node_id 1 to create a new PatchEmbed object from inherited base classes: nn with example: obj = PatchEmbed(img_size, patch_size, in_channels, embed_dim)