class_docstr: Normalized Linear Layer.
  
  Args:
      tempeature (float, optional): Tempeature term. Defaults to 20.
      power (int, optional): Power term. Defaults to 1.0.
      eps (float, optional): The minimal value of divisor to
           keep numerical stability. Defaults to 1e-6.
class_docstr_tok: ["Normalized","Linear","Layer",".","Args",":","tempeature","(","float",",","optional",")",":","Tempeature","term",".","Defaults","to","20.","power","(","int",",","optional",")",":","Power","term",".","Defaults","to","1.0.","eps","(","float",",","optional",")",":","The","minimal","value","of","divisor","to","keep","numerical","stability",".","Defaults","to","1e-6","."]
docstr: Initialize the weights.
docstr_tok: ["Initialize","the","weights","."]
code: def init_weights(self) -> None:
      """Initialize the weights."""
      nn.init.normal_(self.weight, mean=0, std=0.01)
      if self.bias is not None:
          nn.init.constant_(self.bias, 0)
  
file_path: mmdetection/mmdet/models/layers/normed_predictor.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from mmengine.utils import digit_version
  from torch import Tensor
  from mmdet.registry import MODELS
label_desc: Use image node_id 2 for calling the NormedLinear obj's underlying member method code with example usage: obj.init_weights() without return types