Remove the deprecated incsubtensor and setsubtensor functions.

theano/tensor/basic.py

@@ -2978,15 +2978,6 @@ class SubtensorPrinter:
 
 pprint.assign(lambda pstate, r: r.owner and isinstance(r.owner.op, Subtensor), SubtensorPrinter())
 
-def setsubtensor(x, y, idx_list, inplace=False):
-    print >> sys.stderr, "tensor.setsubtensor is deprecated - please use set_subtensor"
-    the_op = IncSubtensor(idx_list, inplace, set_instead_of_inc=True)
-    return the_op(x, y, *Subtensor.collapse(idx_list, lambda entry: isinstance(entry, Variable)))
-def incsubtensor(x, y, idx_list, inplace=False):
-    print >> sys.stderr, "tensor.incsubtensor is deprecated - please use inc_subtensor"
-    the_op = IncSubtensor(idx_list, inplace, set_instead_of_inc=False)
-    return the_op(x, y, *Subtensor.collapse(idx_list, lambda entry: isinstance(entry, Variable)))
-
 def set_subtensor(x, y, inplace=False):
     """Return x with the given subtensor overwritten by y.
 

theano/tensor/tests/test_incsubtensor.py

-import numpy
-import unittest
-from theano.tests import unittest_tools as utt
-import theano
-import theano.tensor as T
-
-class Test_incsubtensor(unittest.TestCase):
-    """Partial testing.
-
-    What could be tested:
-    - increment vs set
-    - thing incremented: scalar, vector, matrix,
-    - increment/set: constant, scalar, vector, matrix
-    - indices: scalar vs slice, constant vs variable, out of bound, ...
-    - inplace
-    """
-    def setUp(self):
-        utt.seed_rng()
-
-    def test_simple_ok(self):
-        """Increments or sets part of a tensor by a scalar using full slice and
-        a partial slice depending on a scalar.
-        """
-        a = T.dmatrix()
-        increment = T.dscalar()
-        sl1 = slice(None)
-        sl2_end = T.lscalar()
-        sl2 = slice(sl2_end)
-
-        for do_set in [False,True]:
-
-            if do_set:
-                resut = T.setsubtensor(a, increment, [sl1, sl2])
-            else:
-                resut = T.incsubtensor(a, increment, [sl1, sl2])
-
-            f = theano.function([a, increment, sl2_end], resut)
-
-            val_a = numpy.ones((5,5))
-            val_inc = 2.3
-            val_sl2_end = 2
-
-            result = f(val_a, val_inc, val_sl2_end)
-
-            expected_result = numpy.copy(val_a)
-            if do_set:
-                expected_result[:,:val_sl2_end] = val_inc
-            else:
-                expected_result[:,:val_sl2_end] += val_inc
-
-            self.assertTrue(numpy.array_equal(result, expected_result))
-        return
-
-    def test_grad(self):
-
-
-        a = T.dvector()
-        b = T.dvector()
-
-        def inc_slice(*s):
-            def just_numeric_args(a,b):
-                return T.incsubtensor(a, b, s)
-            return just_numeric_args
-
-        # vector
-        utt.verify_grad(
-                inc_slice(slice(2,4,None)),
-                (numpy.asarray([0,1,2,3,4,5.]),
-                    numpy.asarray([9,9.]),))
-
-        # matrix
-        utt.verify_grad(
-                inc_slice(slice(1,2,None), slice(None, None, None)),
-                (numpy.asarray([[0,1],[2,3],[4,5.]]),
-                    numpy.asarray([[9,9.]]),))
-
-        #single element
-        utt.verify_grad(
-                inc_slice(2, 1),
-                (numpy.asarray([[0,1],[2,3],[4,5.]]),
-                    numpy.asarray(9.),))