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- 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.
- For parametric activation, please read the layer APIs.
-
- The shortcut of ``tensorlayer.activation`` is ``tensorlayer.act``.
-
- Your activation
- -------------------
-
- Customizes activation function in TensorLayer is very easy.
- The following example implements an activation that multiplies its input by 2.
- For more complex activation, TensorFlow API will be required.
-
- .. code-block:: python
-
- def double_activation(x):
- return x * 2
-
- double_activation = lambda x: x * 2
-
- .. automodule:: tensorlayer.activation
-
- .. autosummary::
-
- leaky_relu
- leaky_relu6
- leaky_twice_relu6
- ramp
- swish
- sign
- hard_tanh
- pixel_wise_softmax
-
- Ramp
- ------
- .. autofunction:: ramp
-
- Leaky ReLU
- ------------
- .. autofunction:: leaky_relu
-
- Leaky ReLU6
- ------------
- .. autofunction:: leaky_relu6
-
- Twice Leaky ReLU6
- -----------------
- .. autofunction:: leaky_twice_relu6
-
- Swish
- ------------
- .. autofunction:: swish
-
- Sign
- ---------------------
- .. autofunction:: sign
-
- Hard Tanh
- ---------------------
- .. autofunction:: hard_tanh
-
- Pixel-wise softmax
- --------------------
- .. autofunction:: pixel_wise_softmax
-
- Parametric activation
- ------------------------------
- See ``tensorlayer.layers``.
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