API - Activations¶
To make TensorLayer simple, we minimize the number of activation functions as much as
we can. So we encourage you to use TensorFlow’s function. TensorFlow provides
tf.nn.relu
, tf.nn.relu6
, tf.nn.elu
, tf.nn.softplus
,
tf.nn.softsign
and so on. More TensorFlow official activation functions can be found
here.
Creating custom activation¶
To implement a custom activation function in TensorLayer is very easy.
The following is an example implementation of an activation that multiplies its input by 2. For more complex activation, TensorFlow API will be required.
def double_activation(x):
return x * 2
identity (x) |
The identity activation function |
ramp ([x, v_min, v_max, name]) |
The ramp activation function. |
Activation functions¶
-
tensorlayer.activation.
identity
(x)[source]¶ The identity activation function
Parameters: - x : a tensor input
input(s)
-
tensorlayer.activation.
ramp
(x=None, v_min=0, v_max=1, name=None)[source]¶ The ramp activation function.
Parameters: - x : a tensor input
input(s)
- v_min : float
if input(s) smaller than v_min, change inputs to v_min
- v_max : float
if input(s) greater than v_max, change inputs to v_max
- name : a string or None
An optional name to attach to this activation function.