Moved kron to slinalg and added deprecation_warning.

theano/sandbox/linalg/kron.py

 from theano import tensor
+from theano.tensor.slinalg import kron
 
+def deprecation_warning():
+    # Make sure the warning is displayed only once.
+    if deprecation_warning.already_displayed:
+        return
 
-def kron(a, b):
-    """ Kronecker product
-
-    Same as scipy.linalg.kron(a, b).
-
+    warnings.warn(
+            "theano modules are deprecated and will be removed in release 0.7",
+            stacklevel=3)
+    deprecation_warning.already_displayed = True
\ No newline at end of file
-    :note: numpy.kron(a, b) != scipy.linalg.kron(a, b)!
-        They don't have the same shape and order when
-        a.ndim != b.ndim != 2.
-
-    :param a: array_like
-    :param b: array_like
-    :return: array_like with a.ndim + b.ndim - 2 dimensions.
-
-    """
-    a = tensor.as_tensor_variable(a)
-    b = tensor.as_tensor_variable(b)
-    if (a.ndim + b.ndim <= 2):
-        raise TypeError('kron: inputs dimensions must sum to 3 or more. '
-                        'You passed %d and %d.' % (a.ndim, b.ndim))
-    o = tensor.outer(a, b)
-    o = o.reshape(tensor.concatenate((a.shape, b.shape)),
-                  a.ndim + b.ndim)
-    shf = o.dimshuffle(0, 2, 1, * range(3, o.ndim))
-    if shf.ndim == 3:
-        shf = o.dimshuffle(1, 0, 2)
-        o = shf.flatten()
-    else:
-        o = shf.reshape((o.shape[0] * o.shape[2],
-                         o.shape[1] * o.shape[3]) +
-                        tuple([o.shape[i] for i in range(4, o.ndim)]))
-    return o