Fix Cuda optimization for PdbBreakpoint

theano/sandbox/cuda/opt.py

@@ -1153,8 +1153,9 @@ def local_gpu_pdbbreakpoint_op(node):
         new_inputs = node.inputs[:1]
         input_transfered = []
 
-        # Propagate the transfers to gpu through the PdbBreakpoint node
-        # while leaving the PdbBreakpoint node fully on the host
+        # Go through the monitored variables, only transfering on GPU those
+        # for which the input comes from the GPU or the output will be
+        # transfered on the GPU.
         nb_monitored_vars = len(node.outputs)
         for i in range(nb_monitored_vars):
 
@@ -1163,23 +1164,22 @@ def local_gpu_pdbbreakpoint_op(node):
 
             input_is_from_gpu = (inp.owner and
                                  isinstance(inp.owner.op, HostFromGpu))
-            output_used = len(out.clients) > 0
-            output_goes_to_gpu = all([c[0] != "output" and
+            output_goes_to_gpu = any([c[0] != "output" and
                                       isinstance(c[0].op, GpuFromHost)
                                       for c in out.clients])
 
-            if input_is_from_gpu and output_used and not output_goes_to_gpu:
+            if input_is_from_gpu:
                 # The op should be applied on the GPU version of the input
                 new_inputs.append(inp.owner.inputs[0])
                 input_transfered.append(True)
 
-            elif not input_is_from_gpu and output_used and output_goes_to_gpu:
+            elif output_goes_to_gpu:
                 # The input should be transfered to the gpu
                 new_inputs.append(gpu_from_host(inp))
                 input_transfered.append(True)
 
             else:
-                # Both are on the gpu or on the host. No transfer is required.
+                # No transfer is required.
                 new_inputs.append(inp)
                 input_transfered.append(False)
 
@@ -1189,12 +1189,7 @@ def local_gpu_pdbbreakpoint_op(node):
             return False
 
         # Apply the op on the new inputs
-        new_op_outputs = node.op(*new_inputs)
-
-        # Ensure that new_op_outputs is a list of outputs (in case the op has
-        # only one output)
-        if not isinstance(new_op_outputs, list):
-            new_op_outputs = [new_op_outputs]
+        new_op_outputs = node.op(*new_inputs, return_list=True)
 
         # Propagate the transfer to the gpu through the outputs that require
         # it