class_docstr: Image to the progressive overlapping Patch Embedding.
  
  Args:
      in_channels (int): Number of input channels. Defaults to 3.
      embed_dims (int): The dimensions of embedding. Defaults to 768.
      num_layers (int, optional): Number of Conv_BN_Layer. Defaults to 2 and
          limit to [2, 3].
      init_cfg (dict or list[dict], optional): Initialization configs.
          Defaults to None.
class_docstr_tok: ["Image","to","the","progressive","overlapping","Patch","Embedding",".","Args",":","in_channels","(","int",")",":","Number","of","input","channels",".","Defaults","to","3.","embed_dims","(","int",")",":","The","dimensions","of","embedding",".","Defaults","to","768.","num_layers","(","int",",","optional",")",":","Number","of","Conv_BN_Layer",".","Defaults","to","2","and","limit","to","[","2",",","3","]",".","init_cfg","(","dict","or","list","[","dict","]",",","optional",")",":","Initialization","configs",".","Defaults","to","None","."]
docstr: Forward function.
  
  Args:
      x (Tensor): A Tensor of shape :math:`(N, C, H, W)`.
  
  Returns:
      Tensor: A tensor of shape math:`(N, HW//16, C)`.
docstr_tok: ["Forward","function",".","Args",":","x","(","Tensor",")",":","A","Tensor","of","shape",":","math",":","`","(","N",",","C",",","H",",","W",")","`",".","Returns",":","Tensor",":","A","tensor","of","shape","math",":","`","(","N",",","HW\/\/16",",","C",")","`","."]
code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      """Forward function.
  
      Args:
          x (Tensor): A Tensor of shape :math:`(N, C, H, W)`.
  
      Returns:
          Tensor: A tensor of shape math:`(N, HW//16, C)`.
      """
      x = self.net(x).flatten(2).permute(0, 2, 1)
      return x
  
imports: from typing import Dict, List, Optional, Tuple, Union
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from mmcv.cnn import ConvModule
  from mmcv.cnn.bricks import DropPath
  from mmengine.model import BaseModule
  from mmengine.model.weight_init import trunc_normal_init
  from mmocr.registry import MODELS
  from mmocr.structures import TextRecogDataSample
label_desc: Use image node_id 2 for calling the OverlapPatchEmbed obj's underlying member method code with example usage: obj.forward(x) and returns: x