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 call(self, x, mask=None):
      x_lo = K.relu(self.lo - x)
      x_hi = K.relu(x - self.hi)
      return x + self.gamma * x_lo - self.gamma * x_hi
  
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 2 for calling the LeakyClippedLinear obj's underlying member method code with example usage: obj.call(x, mask) and returns: unknown