class_docstr: Compute the 2d image patch embedding ready to pass to transformer encoder.
code: def _compute_feats_dims(
      self, image_size: Tuple[int, int, int]
  ) -> Tuple[int, int]:
      out = self.backbone(torch.zeros(1, *image_size)).detach()
      return out.shape[-3], out.shape[-2] * out.shape[-1]
  
imports: from typing import Any, Callable, Dict, List, Optional, Tuple
  import torch
  from torch import nn
  from kornia.core import Module, Tensor
label_desc: Use image node_id 2 for calling the PatchEmbedding obj's underlying member method code with example usage: obj._compute_feats_dims(image_size) and returns: out,  unknown