X = T.fmatrix('X')
y = T.fmatrix('y')

cosines = theano.shared(cosine_sims.astype('float32'))

indx1 = theano.shared(indx1.astype('float32'))
indx2 = theano.shared(indx2.astype('float32'))

w = theano.shared(np.random.uniform(-1./m, 1./m, size=(m, n)).astype('float32'))
b = theano.shared(np.zeros(shape=n,).astype('float32'))

p = T.nnet.softmax(X.dot(w) + b[None, :])

L1 = T.mean(-T.sum(y * T.log(p)))
L2 = T.sum(w**2)
L3 = T.sum((w[indx1, :] - w[indx2, :]) ** 2)

#L3 = T.mean(((w[:, None, :] - w[None, :, :])**2) * cosines[:, :, None])

alpha1 = T.fscalar()
alpha2 = T.fscalar()

L = L1 + alpha1*L2 + alpha2*L3

TypeErrorTraceback (most recent call last)
<ipython-input-38-b3aea550ace2> in <module>()
     14 L1 = T.mean(-T.sum(y * T.log(p)))
     15 L2 = T.sum(w**2)
---> 16 L3 = T.sum((w[indx1, :] - w[indx2, :]) ** 2)
     17
     18 #L3 = T.mean(((w[:, None, :] - w[None, :, :])**2) * cosines[:, :, None])

/opt/jupyter-notebook/.local/lib/python2.7/site-packages/theano/tensor/var.pyc in __getitem__(self, args)
    501                             TensorVariable, TensorConstant,
    502                             theano.tensor.sharedvar.TensorSharedVariable))):
--> 503                 return self.take(args[axis], axis)
    504             else:
    505                 return theano.tensor.subtensor.advanced_subtensor(self, *args)

/opt/jupyter-notebook/.local/lib/python2.7/site-packages/theano/tensor/var.pyc in take(self, indices, axis, mode)
    533
    534     def take(self, indices, axis=None, mode='raise'):
--> 535         return theano.tensor.subtensor.take(self, indices, axis, mode)
    536
    537     # COPYING

/opt/jupyter-notebook/.local/lib/python2.7/site-packages/theano/tensor/subtensor.pyc in take(a, indices, axis, mode)
   2368             return advanced_subtensor1(a.flatten(), indices)
   2369         elif axis == 0:
-> 2370             return advanced_subtensor1(a, indices)
   2371         else:
   2372             if axis < 0:

/opt/jupyter-notebook/.local/lib/python2.7/site-packages/theano/gof/op.pyc in __call__(self, *inputs, **kwargs)
    609         """
    610         return_list = kwargs.pop('return_list', False)
--> 611         node = self.make_node(*inputs, **kwargs)
    612
    613         if config.compute_test_value != 'off':

/opt/jupyter-notebook/.local/lib/python2.7/site-packages/theano/tensor/subtensor.pyc in make_node(self, x, ilist)
   1685         ilist_ = theano.tensor.as_tensor_variable(ilist)
   1686         if ilist_.type.dtype[:3] not in ('int', 'uin'):
-> 1687             raise TypeError('index must be integers')
   1688         if ilist_.type.ndim != 1:
   1689             raise TypeError('index must be vector')

TypeError: index must be integers