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from keras.models import Sequential

model = Sequential()


    

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from keras.layers.core import Dense, Activation

model.add(Dense(output_dim=64, input_dim=100, init="glorot_uniform"))
model.add(Activation("relu"))
model.add(Dense(output_dim=10, init="glorot_uniform"))
model.add(Activation("softmax"))


    

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model.compile(loss='categorical_crossentropy', optimizer='sgd')


    

    




---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-12-64b8ef62ead0> in <module>()
----> 1 model.compile(loss='categorical_crossentropy', optimizer='sgd')

/Users/m/anaconda/lib/python2.7/site-packages/Keras-0.2.0-py2.7.egg/keras/models.pyc in compile(self, optimizer, loss, class_mode, theano_mode)
    351         self.X_test = self.get_input(train=False)
    352 
--> 353         self.y_train = self.get_output(train=True)
    354         self.y_test = self.get_output(train=False)
    355 

/Users/m/anaconda/lib/python2.7/site-packages/Keras-0.2.0-py2.7.egg/keras/layers/containers.pyc in get_output(self, train)
     50 
     51     def get_output(self, train=False):
---> 52         return self.layers[-1].get_output(train)
     53 
     54     def set_input(self):

/Users/m/anaconda/lib/python2.7/site-packages/Keras-0.2.0-py2.7.egg/keras/layers/core.pyc in get_output(self, train)
    410 
    411     def get_output(self, train=False):
--> 412         X = self.get_input(train)
    413         return self.activation(X)
    414 

/Users/m/anaconda/lib/python2.7/site-packages/Keras-0.2.0-py2.7.egg/keras/layers/core.pyc in get_input(self, train)
     87     def get_input(self, train=False):
     88         if hasattr(self, 'previous'):
---> 89             return self.previous.get_output(train=train)
     90         elif hasattr(self, 'input'):
     91             return self.input

/Users/m/anaconda/lib/python2.7/site-packages/Keras-0.2.0-py2.7.egg/keras/layers/core.pyc in get_output(self, train)
    584 
    585     def get_output(self, train=False):
--> 586         X = self.get_input(train)
    587         output = self.activation(T.dot(X, self.W) + self.b)
    588         return output

/Users/m/anaconda/lib/python2.7/site-packages/Keras-0.2.0-py2.7.egg/keras/layers/core.pyc in get_input(self, train)
     87     def get_input(self, train=False):
     88         if hasattr(self, 'previous'):
---> 89             return self.previous.get_output(train=train)
     90         elif hasattr(self, 'input'):
     91             return self.input

/Users/m/anaconda/lib/python2.7/site-packages/Keras-0.2.0-py2.7.egg/keras/layers/core.pyc in get_output(self, train)
    411     def get_output(self, train=False):
    412         X = self.get_input(train)
--> 413         return self.activation(X)
    414 
    415     def get_config(self):

/Users/m/anaconda/lib/python2.7/site-packages/Keras-0.2.0-py2.7.egg/keras/activations.pyc in relu(x)
     18 
     19 def relu(x):
---> 20     return T.nnet.relu(x)
     21 
     22 

AttributeError: 'module' object has no attribute 'relu'

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