tf.keras.activations.relu

Applies the rectified linear unit activation function.

tf.keras.activations.relu(
    x, negative_slope=0.0, max_value=None, threshold=0.0
)

With default values, this returns the standard ReLU activation: max(x, 0), the element-wise maximum of 0 and the input tensor.

Modifying default parameters allows you to use non-zero thresholds, change the max value of the activation, and to use a non-zero multiple of the input for values below the threshold.

Examples:

x = [-10, -5, 0.0, 5, 10]
keras.activations.relu(x)
[ 0.,  0.,  0.,  5., 10.]
keras.activations.relu(x, negative_slope=0.5)
[-5. , -2.5,  0. ,  5. , 10. ]
keras.activations.relu(x, max_value=5.)
[0., 0., 0., 5., 5.]
keras.activations.relu(x, threshold=5.)
[-0., -0.,  0.,  0., 10.]

x Input tensor.
negative_slope A float that controls the slope for values lower than the threshold.
max_value A float that sets the saturation threshold (the largest value the function will return).
threshold A float giving the threshold value of the activation function below which values will be damped or set to zero.

A tensor with the same shape and dtype as input x.