class_docstr: Pixel decoder with a structure like fpn.
  
  Args:
      in_channels (list[int] | tuple[int]): Number of channels in the
          input feature maps.
      feat_channels (int): Number channels for feature.
      out_channels (int): Number channels for output.
      norm_cfg (:obj:`ConfigDict` or dict): Config for normalization.
          Defaults to dict(type='GN', num_groups=32).
      act_cfg (:obj:`ConfigDict` or dict): Config for activation.
          Defaults to dict(type='ReLU').
      encoder (:obj:`ConfigDict` or dict): Config for transorformer
          encoder.Defaults to None.
      positional_encoding (:obj:`ConfigDict` or dict): Config for
          transformer encoder position encoding. Defaults to
          dict(type='SinePositionalEncoding', num_feats=128,
          normalize=True).
      init_cfg (:obj:`ConfigDict` or dict or list[:obj:`ConfigDict` or             dict], optional): Initialization config dict. Defaults to None.
class_docstr_tok: ["Pixel","decoder","with","a","structure","like","fpn",".","Args",":","in_channels","(","list","[","int","]","|","tuple","[","int","]",")",":","Number","of","channels","in","the","input","feature","maps",".","feat_channels","(","int",")",":","Number","channels","for","feature",".","out_channels","(","int",")",":","Number","channels","for","output",".","norm_cfg","(",":","obj",":","`","ConfigDict","`","or","dict",")",":","Config","for","normalization",".","Defaults","to","dict","(","type='GN","'",",","num_groups=32",")",".","act_cfg","(",":","obj",":","`","ConfigDict","`","or","dict",")",":","Config","for","activation",".","Defaults","to","dict","(","type='ReLU","'",")",".","encoder","(",":","obj",":","`","ConfigDict","`","or","dict",")",":","Config","for","transorformer","encoder.Defaults","to","None",".","positional_encoding","(",":","obj",":","`","ConfigDict","`","or","dict",")",":","Config","for","transformer","encoder","position","encoding",".","Defaults","to","dict","(","type='SinePositionalEncoding","'",",","num_feats=128",",","normalize=True",")",".","init_cfg","(",":","obj",":","`","ConfigDict","`","or","dict","or","list","[",":","obj",":","`","ConfigDict","`","or","dict","]",",","optional",")",":","Initialization","config","dict",".","Defaults","to","None","."]
docstr: Initialize weights.
docstr_tok: ["Initialize","weights","."]
code: def init_weights(self) -> None:
      """Initialize weights."""
      for i in range(0, self.num_inputs - 2):
          caffe2_xavier_init(self.lateral_convs[i].conv, bias=0)
          caffe2_xavier_init(self.output_convs[i].conv, bias=0)
  
      caffe2_xavier_init(self.mask_feature, bias=0)
      caffe2_xavier_init(self.last_feat_conv, bias=0)
  
imports: from typing import List, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from mmcv.cnn import Conv2d, ConvModule
  from mmengine.model import BaseModule, ModuleList, caffe2_xavier_init
  from torch import Tensor
  from mmdet.registry import MODELS
  from mmdet.utils import ConfigType, OptMultiConfig
  from .positional_encoding import SinePositionalEncoding
  from .transformer import DetrTransformerEncoder
label_desc: Use image node_id 2 for calling the PixelDecoder obj's underlying member method code with example usage: obj.init_weights() without return types