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
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: analytics-zoo/pyzoo/zoo/pipeline/api/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)