Merge pull request #777 from nouiz/fix_test

theano/sandbox/cuda/opt.py

@@ -514,6 +514,8 @@ def local_gpu_ger(node):
             tensor.blas_c.CGer(destructive=False): gpu_ger_no_inplace,
             tensor.blas.Ger(destructive=True): gpu_ger_no_inplace,
             tensor.blas.Ger(destructive=False): gpu_ger_no_inplace,
+            tensor.blas_scipy.ScipyGer(destructive=True): gpu_ger_no_inplace,
+            tensor.blas_scipy.ScipyGer(destructive=False): gpu_ger_no_inplace,
             }
     if node.op == gpu_from_host:
         host_input = node.inputs[0]

theano/tensor/blas.py

@@ -1399,7 +1399,9 @@ class GemmOptimizer(Optimizer):
                             zip(node.outputs, new_outputs),
                             [old_dot22],
                             reason='GemmOptimizer',
-                            warn=not self.warned
+                            #For now we disable the warning as we know case
+                            #that we need to fix.
+                            warn=False,  # warn=not self.warned
                         )
                         did_something = True
                         nb_replacement += 1

theano/tensor/tests/test_elemwise.py

@@ -618,6 +618,13 @@ class T_sum_dtype(unittest.TestCase):
         for input_dtype in imap(str, theano.scalar.all_types):
             x = tensor.matrix(dtype=input_dtype)
             for output_dtype in imap(str, theano.scalar.all_types):
+                # If the output is a complex, the gradient of the sum will
+                # cast the complex to the input dtype. We can't call the normal
+                # cast on a complex to a not complex as this is ambiguous.
+                if (not input_dtype.startswith('complex') and
+                    output_dtype.startswith('complex')):
+                    continue
+
                 axis = axes[idx % len(axes)]
                 # If output_dtype would force a downcast, we expect a TypeError
                 # We always allow int/uint inputs with float/complex outputs.