Update to tests

theano/tensor/basic.py

@@ -5506,7 +5506,7 @@ class AllocEmpty(gof.Op):
         sh = tuple([int(i) for i in inputs])
         if out[0] is None or out[0].shape != sh:
             # XXX: We could implement and call CudaNdarray.empty(sh) instead.
-            out[0] = numpy.empty(sh)
+            out[0] = numpy.empty(sh, dtype=self.dtype)
 
     def do_merge(self, node):
         return False

theano/tensor/tests/test_blas.py

@@ -878,25 +878,28 @@ def test_dot22scalar():
                     def check_dot22scalar(func, len_topo_scalar=-1):
                         topo = func.maker.fgraph.toposort()
                         ops = [x.op for x in topo]
+                        classes = [type(x.op) for x in topo]
                         dtype4_upcast = theano.scalar.upcast(dtype4, dtype1,
                                                              dtype2)
                         if dtype1 == dtype2 == dtype3 == dtype4_upcast:
                             if len_topo_scalar > 0:
                                 assert len(topo) == len_topo_scalar
-                            assert _dot22scalar in ops, (dtype1, dtype2,
+                            assert gemm_inplace in ops, (dtype1, dtype2,
                                                          dtype3, dtype4)
                         elif dtype1 == dtype2 == dtype4_upcast:
                             if not (len_topo_scalar > 0):
                                 assert len(topo) == len_topo_scalar
-                                assert _dot22scalar in ops, (dtype1, dtype2,
+                                assert gemm_inplace in ops, (dtype1, dtype2,
                                                              dtype3, dtype4)
+                                assert not T.Elemwise in classes, (
+                                    dtype1, dtype2, dtype3, dtype4)
                             else:
                                 # Currently there is a problem of
                                 # optimization order The constant get
                                 # upcasted to float64 before we try to
                                 # merge it with the dot22 of
                                 # float32. So this prevent the merge.
-                                assert _dot22scalar in ops or _dot22 in ops, (
+                                assert gemm_inplace in ops or _dot22 in ops, (
                                     dtype1, dtype2, dtype3, dtype4)
 
                         elif dtype1 == dtype2:
@@ -925,7 +928,7 @@ def test_dot22scalar():
                                                 cst * c * T.dot(a, b),
                                                 mode=mode_blas_opt)
                             topo = f.maker.fgraph.toposort()
-                            check_dot22scalar(f, 2)
+                            check_dot22scalar(f, 5)
 
                             f(av, bv, cv)
 
@@ -933,7 +936,7 @@ def test_dot22scalar():
                                             c * cst * T.dot(a, b),
                                             mode=mode_blas_opt)
                         topo = f.maker.fgraph.toposort()
-                        check_dot22scalar(f, 2)
+                        check_dot22scalar(f, 5)
                         f(av, bv, cv)
 
                         # Here, canonicalize also seems needed
@@ -943,7 +946,7 @@ def test_dot22scalar():
                                             cst2 * c * cst * T.dot(a, b),
                                             mode=m2)
                         topo = f.maker.fgraph.toposort()
-                        check_dot22scalar(f, 2)
+                        check_dot22scalar(f, 5)
                         f(av, bv, cv)
 
                         if dtype1 == dtype2 == dtype3:
@@ -951,7 +954,7 @@ def test_dot22scalar():
                                                 c * cst * a * T.dot(a, b),
                                                 mode=m2)
                             topo = f.maker.fgraph.toposort()
-                            check_dot22scalar(f, 2)
+                            check_dot22scalar(f, 5)
                             f(sv, sv, sv)
 
                             f = theano.function([a, b, c],
@@ -974,7 +977,7 @@ def test_dot22scalar():
                                                 c * a * cst * T.dot(a, b),
                                                 mode=m2)
                             topo = f.maker.fgraph.toposort()
-                            check_dot22scalar(f, 2)
+                            check_dot22scalar(f, 5)
                             f(sv, sv, sv)
 
                     cmp((3, 4), (4, 5), (3, 5))
@@ -994,7 +997,7 @@ def test_dot22scalar_cast():
     for scalar_int_type in T.int_dtypes:
         y = T.scalar(dtype=scalar_int_type)
         f = theano.function([A, y], T.dot(A, A) * y, mode=mode_blas_opt)
-        assert _dot22scalar in [x.op for x in f.maker.fgraph.toposort()]
+        assert gemm_inplace in [x.op for x in f.maker.fgraph.toposort()]
     A = T.fmatrix()
     for scalar_int_type in T.int_dtypes:
         y = T.scalar(dtype=scalar_int_type)
@@ -1002,7 +1005,7 @@ def test_dot22scalar_cast():
         if scalar_int_type in ['int32', 'int64']:
             assert _dot22 in [x.op for x in f.maker.fgraph.toposort()]
         else:
-            assert _dot22scalar in [x.op for x in f.maker.fgraph.toposort()]
+            assert gemm_inplace in [x.op for x in f.maker.fgraph.toposort()]
 
 
 def test_local_dot22_to_dot22scalar():