TensorFlow 1 version
|
View source on GitHub
|
Rectified Linear Unit activation function.
Inherits From: Layer
tf.keras.layers.ReLU(
max_value=None, negative_slope=0, threshold=0, **kwargs
)
With default values, it returns element-wise max(x, 0).
Otherwise, it follows:
f(x) = max_value for x >= max_value,
f(x) = x for threshold <= x < max_value,
f(x) = negative_slope * (x - threshold) otherwise.
Input shape:
Arbitrary. Use the keyword argument input_shape
(tuple of integers, does not include the samples axis)
when using this layer as the first layer in a model.
Output shape:
Same shape as the input.
Arguments | |
|---|---|
max_value
|
Float >= 0. Maximum activation value. |
negative_slope
|
Float >= 0. Negative slope coefficient. |
threshold
|
Float. Threshold value for thresholded activation. |