class_docstr: Applies Spectral Normalization to all parameters in a tree.
  
  This is isomorphic to EMAParamsTree in moving_averages.py.
class_docstr_tok: ["Applies","Spectral","Normalization","to","all","parameters","in","a","tree",".","This","is","isomorphic","to","EMAParamsTree","in","moving_averages.py","."]
docstr: Initializes an SNParamsTree module.
  
  Args:
    eps: The constant used for numerical stability.
    n_steps: How many steps of power iteration to perform to approximate the
      singular value of the input.
    ignore_regex: A string. Any parameter in the tree whose name matches this
      regex will not have spectral normalization applied to it. The empty
      string means this module applies to all parameters.
    name: The name of the module.
docstr_tok: ["Initializes","an","SNParamsTree","module",".","Args",":","eps",":","The","constant","used","for","numerical","stability",".","n_steps",":","How","many","steps","of","power","iteration","to","perform","to","approximate","the","singular","value","of","the","input",".","ignore_regex",":","A","string",".","Any","parameter","in","the","tree","whose","name","matches","this","regex","will","not","have","spectral","normalization","applied","to","it",".","The","empty","string","means","this","module","applies","to","all","parameters",".","name",":","The","name","of","the","module","."]
code: def __init__(
      self,
      eps: float = 1e-4,
      n_steps: int = 1,
      ignore_regex: str = "",
      name: Optional[str] = None,
  ):
      """Initializes an SNParamsTree module.
  
      Args:
        eps: The constant used for numerical stability.
        n_steps: How many steps of power iteration to perform to approximate the
          singular value of the input.
        ignore_regex: A string. Any parameter in the tree whose name matches this
          regex will not have spectral normalization applied to it. The empty
          string means this module applies to all parameters.
        name: The name of the module.
      """
      super().__init__(name=name)
      self.eps = eps
      self.n_steps = n_steps
      self.ignore_regex = ignore_regex
  
imports: import re
  from typing import Optional
  from haiku._src import base
  from haiku._src import data_structures
  from haiku._src import initializers
  from haiku._src import module
  import jax
  import jax.lax
  import jax.numpy
label_desc: Use image node_id 1 to create a new SNParamsTree object from inherited base classes: hk with example: obj = SNParamsTree(eps, n_steps, ignore_regex, name)