get_alexnet scale error

[calugo]

Hello,
When running the Jupyter notebook, I cannot start alexnet at all, I always get the set of errors atached:

Subtensor{int64}.0, Elemwise{add,no_inplace}.0, Elemwise{add,no_inplace}.0, Subtensor{int64}.0)
(Subtensor{int64}.0, Elemwise{add,no_inplace}.0, Elemwise{add,no_inplace}.0, Subtensor{int64}.0)
(Subtensor{int64}.0, Elemwise{add,no_inplace}.0, Elemwise{add,no_inplace}.0, Subtensor{int64}.0)
(Subtensor{int64}.0, Elemwise{add,no_inplace}.0, Elemwise{add,no_inplace}.0, Subtensor{int64}.0)

ValueError Traceback (most recent call last)
in ()
----> 1 alexnet = get_alexnet(input_size,nb_classes,mean_flag)
2
3 #print alexnet.summary()

/home/carlos/alexnet/AlexNet-Experiments-Keras/Code/alexnet_base.pyc in get_alexnet(input_shape, nb_classes, mean_flag)
63
64 dense_1 = Flatten(name="flatten")(dense_1)
---> 65 dense_1 = Dense(4096, activation='relu',name='dense_1',init='he_normal')(dense_1)
66 dense_2 = Dropout(0.5)(dense_1)
67 dense_2 = Dense(4096, activation='relu',name='dense_2',init='he_normal')(dense_2)

/home/carlos/.conda/envs/ipykernel_py2/lib/python2.7/site-packages/keras/engine/topology.pyc in call(self, x, mask)
541 'layer.build(batch_input_shape)')
542 if len(input_shapes) == 1:
--> 543 self.build(input_shapes[0])
544 else:
545 self.build(input_shapes)

/home/carlos/.conda/envs/ipykernel_py2/lib/python2.7/site-packages/keras/layers/core.pyc in build(self, input_shape)
750 name='{}_W'.format(self.name),
751 regularizer=self.W_regularizer,
--> 752 constraint=self.W_constraint)
753 if self.bias:
754 self.b = self.add_weight((self.output_dim,),

/home/carlos/.conda/envs/ipykernel_py2/lib/python2.7/site-packages/keras/engine/topology.pyc in add_weight(self, shape, initializer, name, trainable, regularizer, constraint)
413 '''
414 initializer = initializations.get(initializer)
--> 415 weight = initializer(shape, name=name)
416 if regularizer is not None:
417 self.add_loss(regularizer(weight))

/home/carlos/.conda/envs/ipykernel_py2/lib/python2.7/site-packages/keras/initializations.pyc in he_normal(shape, name, dim_ordering)
66 fan_in, fan_out = get_fans(shape, dim_ordering=dim_ordering)
67 s = np.sqrt(2. / fan_in)
---> 68 return normal(shape, s, name=name)
69
70

/home/carlos/.conda/envs/ipykernel_py2/lib/python2.7/site-packages/keras/initializations.pyc in normal(shape, scale, name)
35
36 def normal(shape, scale=0.05, name=None):
---> 37 return K.random_normal_variable(shape, 0.0, scale, name=name)
38
39

/home/carlos/.conda/envs/ipykernel_py2/lib/python2.7/site-packages/keras/backend/theano_backend.pyc in random_normal_variable(shape, mean, scale, dtype, name)
181
182 def random_normal_variable(shape, mean, scale, dtype=None, name=None):
--> 183 return variable(np.random.normal(loc=0.0, scale=scale, size=shape),
184 dtype=dtype, name=name)
18

mtrand.pyx in mtrand.RandomState.normal()

ValueError: scale < 0

Which seem to be ultimately related to the function random_normal_variable(), my question is how is the scale parameter calculated as it is always taking negative values. Is this a known bug?

Thanks in advance.

Carlos