class_docstr: Rectified Linear Unit activation function layer.
  
  Formula:
  ``` python
  f(x) = max(x,0)
  f(x) = max_value if x >= max_value
  f(x) = x if threshold <= x < max_value
  f(x) = negative_slope * (x - threshold) otherwise
  ```
  
  Example:
  ``` python
  relu_layer = keras.layers.activations.ReLU(
      max_value=10,
      negative_slope=0.5,
      threshold=0,
  )
  input = np.array([-10, -5, 0.0, 5, 10])
  result = relu_layer(input)
  # result = [-5. , -2.5,  0. ,  5. , 10.]
  ```
  
  Args:
      max_value: Float >= 0. Maximum activation value. None means unlimited.
          Defaults to `None`.
      negative_slope: Float >= 0. Negative slope coefficient.
          Defaults to `0.0`.
      threshold: Float >= 0. Threshold value for thresholded activation.
          Defaults to `0.0`.
      **kwargs: Base layer keyword arguments, such as `name` and `dtype`.
code: def __init__(
      self, max_value=None, negative_slope=0.0, threshold=0.0, **kwargs
  ):
      super().__init__(**kwargs)
      if max_value is not None and max_value < 0.0:
          raise ValueError(
              "max_value of a ReLU layer cannot be a negative "
              f"value. Received: max_value={max_value}"
          )
      if negative_slope is None or negative_slope < 0.0:
          raise ValueError(
              "negative_slope of a ReLU layer cannot be a negative "
              f"value. Received: negative_slope={negative_slope}"
          )
      if threshold is None or threshold < 0.0:
          raise ValueError(
              "threshold of a ReLU layer cannot be a negative "
              f"value. Received: threshold={threshold}"
          )
  
      self.supports_masking = True
      self.max_value = max_value
      self.negative_slope = negative_slope
      self.threshold = threshold
  
file_path: keras/keras/layers/activations/relu.py
imports: from keras import activations
  from keras.api_export import keras_export
  from keras.layers.layer import Layer
label_desc: Use image node_id 1 to create a new ReLU object from inherited base classes: Layer with example: obj = ReLU(max_value, negative_slope, threshold)