TensorFlow 1 version
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View source on GitHub
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Applies the rectified linear unit activation function.
tf.keras.activations.relu(
x, alpha=0.0, max_value=None, threshold=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.
For example:
foo = tf.constant([-10, -5, 0.0, 5, 10], dtype = tf.float32) tf.keras.activations.relu(foo).numpy() array([ 0., 0., 0., 5., 10.], dtype=float32) tf.keras.activations.relu(foo, alpha=0.5).numpy() array([-5. , -2.5, 0. , 5. , 10. ], dtype=float32) tf.keras.activations.relu(foo, max_value=5).numpy() array([0., 0., 0., 5., 5.], dtype=float32) tf.keras.activations.relu(foo, threshold=5).numpy() array([-0., -0., 0., 0., 10.], dtype=float32)
Arguments | |
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x
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Input tensor or variable.
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alpha
|
A float that governs the slope for values lower than the
threshold.
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max_value
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A float that sets the saturation threshold (the largest value
the function will return).
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threshold
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A float giving the threshold value of the activation function
below which values will be damped or set to zero.
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Returns | |
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A Tensor representing the input tensor,
transformed by the relu activation function.
Tensor will be of the same shape and dtype of input x.
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