class_docstr: Leaky Clipped Linear Unit.
  
      Args:
          low (float): Lower threshold
          high (float): Lower threshold
          alpha (float) The slope of the function below low or above high.
class_docstr_tok: ["Leaky","Clipped","Linear","Unit",".","Args",":","low","(","float",")",":","Lower","threshold","high","(","float",")",":","Lower","threshold","alpha","(","float",")","The","slope","of","the","function","below","low","or","above","high","."]
code: def get_config(self):
      config = {
          "alpha": float(1 - self.gamma),
          "low": float(self.lo),
          "high": float(self.hi),
      }
      base_config = super().get_config()
      return dict(list(base_config.items()) + list(config.items()))
  
file_path: stellargraph/stellargraph/layer/link_inference.py
imports: from typing import AnyStr, Optional, List, Tuple
  import tensorflow
  from tensorflow.keras.layers import Layer, Concatenate, Dense, Lambda, Multiply, Average, Reshape, Activation
  from tensorflow.keras import backend
  import warnings
label_desc: Use image node_id 3 for calling the LeakyClippedLinear obj's underlying member method code with example usage: obj.get_config() and returns: dict