docstr: Initialize Siren uniform for the first layer.
  
  It draws values from a uniform distribution `[-limit, limit]`
  where `limit=fan_in` where `fan_in` is the number of input
  features.
docstr_tok: ["Initialize","Siren","uniform","for","the","first","layer",".","It","draws","values","from","a","uniform","distribution","`","[","-limit",",","limit","]","`","where","`","limit=fan_in","`","where","`","fan_in","`","is","the","number","of","input","features","."]
code: def __init__(self):
      """Initialize Siren uniform for the first layer.
  
      It draws values from a uniform distribution `[-limit, limit]`
      where `limit=fan_in` where `fan_in` is the number of input
      features.
      """
      super().__init__(numerator=1, fan_mode="fan_in", power=1, gain=1)
  
imports: from typing import Tuple, Union, Optional
  import abc
  import ivy
  from ivy.functional.ivy.gradients import _variable
label_desc: Use image node_id 1 to create a new FirstLayerSiren object from inherited base classes: Uniform with example: obj = FirstLayerSiren()