from __future__ import absolute_import
from . import backend as K


def softmax(x):
    ndim = K.ndim(x)
    if ndim == 2:
        return K.softmax(x)
    elif ndim == 3:
        e = K.exp(x - K.max(x, axis=-1, keepdims=True))
        s = K.sum(e, axis=-1, keepdims=True)
        return e / s
    else:
        raise Exception('Cannot apply softmax to a tensor that is not 2D or 3D. ' +
                        'Here, ndim=' + str(ndim))


def softplus(x):
    return K.softplus(x)


def softsign(x):
    return K.softsign(x)


def relu(x, alpha=0., max_value=None):
    return K.relu(x, alpha=alpha, max_value=max_value)


def tanh(x):
    return K.tanh(x)


def sigmoid(x):
    return K.sigmoid(x)


def hard_sigmoid(x):
    return K.hard_sigmoid(x)


def linear(x):
    '''
    The function returns the variable that is passed in, so all types work.
    '''
    return x


from .utils.generic_utils import get_from_module
def get(identifier):
    return get_from_module(identifier, globals(), 'activation function')

@@ -939,16 +939,65 @@
 ifier):%0A
+    if identifier is None:%0A        return linear%0A
     retu

Add support for None activations