View source on GitHub |
Rectified Linear Unit activation function layer.
Inherits From: Layer
, Operation
tf.keras.layers.ReLU(
max_value=None, negative_slope=0.0, threshold=0.0, **kwargs
)
Used in the notebooks
Used in the guide | Used in the tutorials |
---|---|
Formula:
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:
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.]
Methods
from_config
@classmethod
from_config( config )
Creates a layer from its config.
This method is the reverse of get_config
,
capable of instantiating the same layer from the config
dictionary. It does not handle layer connectivity
(handled by Network), nor weights (handled by set_weights
).
Args | |
---|---|
config
|
A Python dictionary, typically the output of get_config. |
Returns | |
---|---|
A layer instance. |
symbolic_call
symbolic_call(
*args, **kwargs
)