class_docstr: FPN-like feature fusion module in PANet.
  
  Args:
      in_channels (int): Number of input channels.
      init_cfg (dict or list[dict], optional): Initialization configs.
class_docstr_tok: ["FPN-like","feature","fusion","module","in","PANet",".","Args",":","in_channels","(","int",")",":","Number","of","input","channels",".","init_cfg","(","dict","or","list","[","dict","]",",","optional",")",":","Initialization","configs","."]
code: def _upsample_add(self, x, y):
      return F.interpolate(x, size=y.size()[2:]) + y
  
file_path: mmocr/mmocr/models/textdet/necks/fpem_ffm.py
imports: from typing import Dict, List, Optional, Tuple, Union
  import torch
  import torch.nn.functional
  from mmengine.model import BaseModule, ModuleList
  from torch import nn
  from mmocr.registry import MODELS
label_desc: Use image node_id 3 for calling the FPEM obj's underlying member method code with example usage: obj._upsample_add(x, y) and returns: unknown