applied changes suggested by lamblin and nouiz

theano/tensor/nnet/conv3d2d.py

@@ -329,9 +329,11 @@ def make_gpu_optimizer(op, to_gpu):
                 new_inp = list(node.inputs)
                 for idx in to_gpu:
                     new_inp[idx] = cuda.gpu_from_host(new_inp[idx])
-                new_node = cuda.host_from_gpu(op()(*new_inp))
-                copy_stack_trace(node.outputs[0], new_node)
-                return [new_node]
+                result_node = op()(*new_inp)
+                copy_stack_trace(node.outputs[0], result_node)
+                transfer_node = cuda.host_from_gpu(result_node)
+                copy_stack_trace(node.outputs[0], transfer_node)
+                return [transfer_node]
         if node.op == cuda.gpu_from_host:
             # gpu_from_host(op) -> op(gpu_from_host)
             host_input = node.inputs[0]
@@ -342,7 +344,7 @@ def make_gpu_optimizer(op, to_gpu):
                 for idx in to_gpu:
                     new_inp[idx] = cuda.gpu_from_host(new_inp[idx])
                 new_node = op()(*new_inp)
-                copy_stack_trace(node.outputs[0], new_node)
+                copy_stack_trace(host_input, new_node)
                 return [new_node]
         return False
     local_to_gpu.__name__ = "local_to_gpu_" + op.__name__

theano/tensor/nnet/nnet.py

@@ -753,7 +753,7 @@ def local_logsoftmax(node):
         new_op = LogSoftmax()
         ret = new_op(inVars)
         ret .tag.values_eq_approx = values_eq_approx_remove_inf
-        copy_stack_trace(node.outputs[0], ret)
+        copy_stack_trace([node.inputs[0], node.outputs[0]], ret)
         return [ret]
 
 
@@ -867,7 +867,6 @@ def local_softmax_with_bias(node):
                 if sm_bias.type == node.outputs[0].type:
                     # This condition is not always true. See the test
                     # nnet/tests/test_nnet.py:T_SoftmaxWithBias.test_broadcast
-                    copy_stack_trace(node.outputs[0], sm_bias)
                     return [sm_bias]
 
 

theano/tensor/nnet/sigm.py

@@ -955,8 +955,12 @@ def local_inv_1_plus_exp(node):
                             sigmoid(
                                 tensor.neg(nonconsts[0].owner.inputs[0])),
                             scalar_inputs)
-                        # keep stack trace
-                        copy_stack_trace(node.outputs[0], out)
+                        # keep combined stack traces of
+                        #     exp(x):           nonconsts[0],
+                        #     1 + exp(x):       inv_arg,
+                        #     1 / (1 + exp(x)): node.outputs[0]
+                        copy_stack_trace(
+                            [nonconsts[0], inv_arg, node.outputs[0]], out)
                         return out
 
 # Registration is below, and conditional.
@@ -979,7 +983,7 @@ def local_1msigmoid(node):
                 return
             if numpy.allclose(numpy.sum(val_l), 1):
                 out = sigmoid(-sub_r.owner.inputs[0])
-                copy_stack_trace(node.outputs[0], out)
+                copy_stack_trace([sub_r, node.outputs[0]], out)
                 return [out]
 
 register_local_1msigmoid = False