class_docstr: Task decomposition module in task-aligned predictor of TOOD.
  
  Args:
      feat_channels (int): Number of feature channels in TOOD head.
      stacked_convs (int): Number of conv layers in TOOD head.
      la_down_rate (int): Downsample rate of layer attention.
          Defaults to 8.
      conv_cfg (:obj:`ConfigDict` or dict, optional): Config dict for
          convolution layer. Defaults to None.
      norm_cfg (:obj:`ConfigDict` or dict, optional):  Config dict for
      normalization layer. Defaults to None.
class_docstr_tok: ["Task","decomposition","module","in","task-aligned","predictor","of","TOOD",".","Args",":","feat_channels","(","int",")",":","Number","of","feature","channels","in","TOOD","head",".","stacked_convs","(","int",")",":","Number","of","conv","layers","in","TOOD","head",".","la_down_rate","(","int",")",":","Downsample","rate","of","layer","attention",".","Defaults","to","8.","conv_cfg","(",":","obj",":","`","ConfigDict","`","or","dict",",","optional",")",":","Config","dict","for","convolution","layer",".","Defaults","to","None",".","norm_cfg","(",":","obj",":","`","ConfigDict","`","or","dict",",","optional",")",":","Config","dict","for","normalization","layer",".","Defaults","to","None","."]
docstr: Initialize the parameters.
docstr_tok: ["Initialize","the","parameters","."]
code: def init_weights(self) -> None:
      """Initialize the parameters."""
      for m in self.layer_attention.modules():
          if isinstance(m, nn.Conv2d):
              normal_init(m, std=0.001)
      normal_init(self.reduction_conv.conv, std=0.01)
  
imports: from typing import List, Optional, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from mmcv.cnn import ConvModule, Scale
  from mmcv.ops import deform_conv2d
  from mmengine import MessageHub
  from mmengine.config import ConfigDict
  from mmengine.model import bias_init_with_prob, normal_init
  from mmengine.structures import InstanceData
  from torch import Tensor
  from mmdet.registry import MODELS, TASK_UTILS
  from mmdet.structures.bbox import distance2bbox
  from mmdet.utils import ConfigType, InstanceList, OptConfigType, OptInstanceList, reduce_mean
  from ..task_modules.prior_generators import anchor_inside_flags
  from ..utils import filter_scores_and_topk, images_to_levels, multi_apply, sigmoid_geometric_mean, unmap
  from .atss_head import ATSSHead
label_desc: Use image node_id 2 for calling the TaskDecomposition obj's underlying member method code with example usage: obj.init_weights() without return types