class_docstr: Image to Patch Embedding using multiple convolutional layers
class_docstr_tok: ["Image","to","Patch","Embedding","using","multiple","convolutional","layers"]
code: def forward(self, x, padding_size=None):
      x = self.proj(x)
      Hp, Wp = x.shape[2], x.shape[3]
      x = x.flatten(2).transpose(1, 2)
      return x, (Hp, Wp)
  
imports: import logging
  import math
  from functools import partial
  from typing import List, Optional
  import torch
  import torch.nn
  from fairscale.nn import checkpoint_wrapper
  from vissl.config import AttrDict
  from vissl.models.model_helpers import DropPath, to_2tuple, trunc_normal_
  from vissl.models.trunks import register_model_trunk
  from vissl.models.trunks.vision_transformer import Mlp
  from vissl.utils.fsdp_utils import fsdp_wrapper
  from vissl.utils.misc import set_torch_seed
label_desc: Use image node_id 2 for calling the ConvPatchEmbed obj's underlying member method code with example usage: obj.forward(x, padding_size) and returns: x,  Hp,  Wp