Little fixes to improve boolean mask indexing.

theano/tensor/subtensor.py

@@ -336,6 +336,11 @@ class Subtensor(Op):
                         theano.tensor.wscalar, theano.tensor.bscalar]
         invalid_tensor_types = [theano.tensor.fscalar, theano.tensor.dscalar,
                                 theano.tensor.cscalar, theano.tensor.zscalar]
+
+        if (isinstance(entry, (np.ndarray, theano.tensor.Variable)) and
+                hasattr(entry, 'dtype') and entry.dtype == 'bool'):
+            raise AdvancedIndexingError(Subtensor.e_indextype, entry)
+
         if (isinstance(entry, gof.Variable) and
             (entry.type in invalid_scal_types or
              entry.type in invalid_tensor_types)):
@@ -2049,8 +2054,8 @@ def as_index_variable(idx):
     if isinstance(idx, gof.Variable) and isinstance(idx.type, NoneTypeT):
         return idx
     idx = theano.tensor.as_tensor_variable(idx)
-    if idx.type.dtype not in theano.tensor.integer_dtypes and idx.type.dtype != 'bool':
-        raise TypeError('index must be integers')
+    if idx.type.dtype not in theano.tensor.discrete_dtypes:
+        raise TypeError('index must be integers or a boolean mask')
     return idx
 
 

theano/tensor/tests/test_subtensor.py

@@ -385,7 +385,7 @@ class T_subtensor(unittest.TestCase, utt.TestOptimizationMixin):
         assert_array_equal(numpy_n[np.newaxis, 1:, mask], n[np.newaxis, 1:, mask].eval())
         assert_array_equal(numpy_inc_subtensor(numpy_n, [0, mask], 1),
                            inc_subtensor(n[0, mask], 1).eval())
-        assert_array_equal(numpy_inc_subtensor(numpy_n, [Ellipsis, mask], 1),
+        assert_array_equal(numpy_inc_subtensor(numpy_n, [slice(None), mask], 1),
                            inc_subtensor(n[:, mask], 1).eval())
 
         # indexing with a boolean ndarray

theano/tensor/var.py

@@ -534,12 +534,7 @@ class _tensor_py_operators(object):
         axis = None
         for i, arg in enumerate(args):
             try:
-                if (isinstance(arg, (np.ndarray, theano.tensor.Variable)) and
-                        hasattr(arg, 'dtype') and arg.dtype == 'bool'):
-                    advanced = True
-                    axis = None
-                    break
-                elif arg is not np.newaxis:
+                if arg is not np.newaxis:
                     theano.tensor.subtensor.Subtensor.convert(arg)
             except theano.tensor.subtensor.AdvancedIndexingError:
                 if advanced:
@@ -555,6 +550,7 @@ class _tensor_py_operators(object):
                     equal_slices(a, slice(None)) for a in args[:axis]) and
                 all(isinstance(a, slice) and
                     equal_slices(a, slice(None)) for a in args[axis + 1:]) and
+                (not hasattr(args[axis], 'dtype') or args[axis].dtype != 'bool') and
                 isinstance(args[axis],
                            (np.ndarray, list,
                             TensorVariable, TensorConstant,