add selu activation

tflearn/__init__.py

@@ -33,7 +33,7 @@
 from .optimizers import SGD, AdaGrad, Adam, RMSProp, Momentum, Ftrl, AdaDelta, \
     ProximalAdaGrad
 from .activations import linear, tanh, sigmoid, softmax, softplus, softsign,\
-    relu, relu6, leaky_relu, prelu, elu
+    relu, relu6, leaky_relu, prelu, elu, crelu, selu
 from .variables import variable, get_all_trainable_variable, \
     get_all_variables, get_layer_variables_by_name, get_layer_variables_by_scope
 from .objectives import categorical_crossentropy, binary_crossentropy, \

tflearn/activations.py

@@ -283,3 +283,24 @@ def crelu(x):
     """
 
     return tf.nn.crelu(x)
+
+
+def selu(x):
+    """ SELU.
+
+    Scaled Exponential Linear Unit.
+
+    Arguments
+        x : A `Tensor` with type `float`, `double`, `int32`, `int64`, `uint8`,
+            `int16`, or `int8`
+
+    References:
+        Self-Normalizing Neural Networks, Klambauer et al., 2017.
+
+    Links:
+        [https://arxiv.org/abs/1706.02515](https://arxiv.org/abs/1706.02515)
+
+    """
+    alpha = 1.6732632423543772848170429916717
+    scale = 1.0507009873554804934193349852946
+    return scale * tf.nn.elu(x, alpha)