class_docstr: Thresholded Rectified Linear Unit.
  It follows:
  f(x) = x for x > theta,
  f(x) = 0 otherwise.
  
  When you use this layer as the first layer of a model, you need to provide the argument
  input_shape (a shape tuple, does not include the batch dimension).
  
  # Arguments
  theta: Float >= 0. Threshold location of activation. Default is 1.0.
  input_shape: A shape tuple, not including batch.
  name: String to set the name of the layer.
        If not specified, its name will by default to be a generated string.
  
  >>> thresholdedrelu = ThresholdedReLU(input_shape=(10, 12))
  creating: createZooKerasThresholdedReLU
class_docstr_tok: ["Thresholded","Rectified","Linear","Unit",".","It","follows",":","f","(","x",")","=","x","for","x",">","theta",",","f","(","x",")","=","0","otherwise",".","When","you","use","this","layer","as","the","first","layer","of","a","model",",","you","need","to","provide","the","argument","input_shape","(","a","shape","tuple",",","does","not","include","the","batch","dimension",")",".","#","Arguments","theta",":","Float",">","=","0",".","Threshold","location","of","activation",".","Default","is","1.0.","input_shape",":","A","shape","tuple",",","not","including","batch",".","name",":","String","to","set","the","name","of","the","layer",".","If","not","specified",",","its","name","will","by","default","to","be","a","generated","string",".",">",">",">","thresholdedrelu","=","ThresholdedReLU","(","input_shape=","(","10",",","12",")",")","creating",":","createZooKerasThresholdedReLU"]
code: def __init__(self, theta=1.0, input_shape=None, **kwargs):
      super(ThresholdedReLU, self).__init__(
          None,
          float(theta),
          list(input_shape) if input_shape else None,
          **kwargs,
      )
  
file_path: BigDL/python/dllib/src/bigdl/dllib/keras/layers/advanced_activations.py
imports: import sys
  from ..engine.topology import ZooKerasLayer
label_desc: Use image node_id 1 to create a new ThresholdedReLU object from inherited base classes: ZooKerasLayer with example: obj = ThresholdedReLU(theta, input_shape)