From 4ec29c5d95ef3b63a756b7a8263892c2fb69cfc5 Mon Sep 17 00:00:00 2001
From: "A. Unique TensorFlower" <gardener@tensorflow.org>
Date: Mon, 31 Jul 2017 09:41:25 -0700
Subject: [PATCH] Avoid direct access to Node::def() where some other method
works.
PiperOrigin-RevId: 163704839
---
tensorflow/core/common_runtime/function.cc | 4 +++-
tensorflow/core/common_runtime/simple_placer.cc | 8 ++++----
tensorflow/core/graph/gradients.cc | 4 +++-
tensorflow/core/graph/optimizer_cse.cc | 5 +++--
tensorflow/core/kernels/hexagon/graph_transferer.cc | 12 ++++++------
5 files changed, 19 insertions(+), 14 deletions(-)
diff --git a/tensorflow/core/common_runtime/function.cc b/tensorflow/core/common_runtime/function.cc
index 395a64353f4..64c3747ce1c 100644
--- a/tensorflow/core/common_runtime/function.cc
+++ b/tensorflow/core/common_runtime/function.cc
@@ -1030,7 +1030,9 @@ void ToGraphDef(const Graph* g, GraphDef* gdef, bool pretty) {
NodeDef* ndef = gdef->add_node();
ndef->set_name(NewName(n, pretty));
ndef->set_op(n->type_string());
- *(ndef->mutable_attr()) = n->def().attr();
+ for (const auto& attr : n->attrs()) {
+ (*ndef->mutable_attr())[attr.first] = attr.second;
+ }
inputs.clear();
inputs.resize(n->num_inputs());
for (const Edge* e : n->in_edges()) {
diff --git a/tensorflow/core/common_runtime/simple_placer.cc b/tensorflow/core/common_runtime/simple_placer.cc
index 6b7c47f8fe5..5e6c3d164b1 100644
--- a/tensorflow/core/common_runtime/simple_placer.cc
+++ b/tensorflow/core/common_runtime/simple_placer.cc
@@ -147,7 +147,7 @@ class ColocationGraph {
// attribute with the calls to ColocateNodeToGroup.
bool found_spec = false;
const AttrValue* attr_value =
- AttrSlice(node->def()).Find(kColocationAttrNameStringPiece);
+ node->attrs().Find(kColocationAttrNameStringPiece);
if (attr_value != nullptr && attr_value->has_list()) {
for (const string& class_spec : attr_value->list().s()) {
StringPiece spec(class_spec);
@@ -184,7 +184,7 @@ class ColocationGraph {
// error, return it.
Status s = ColocateNodes(*node, *root_node);
if (!s.ok()) {
- return AttachDef(s, node->def());
+ return AttachDef(s, *node);
}
}
return Status::OK();
@@ -418,7 +418,7 @@ class ColocationGraph {
}
Status status = InitializeMember(*node, &members_[node->id()]);
if (!status.ok()) {
- return AttachDef(status, node->def());
+ return AttachDef(status, *node);
}
}
return Status::OK();
@@ -727,7 +727,7 @@ Status SimplePlacer::Run() {
"be on the same device), but the two nodes "
"were assigned two different devices: ",
status.error_message()),
- dst->def());
+ *dst);
}
}
}
diff --git a/tensorflow/core/graph/gradients.cc b/tensorflow/core/graph/gradients.cc
index d3e7ff781c2..6b566134703 100644
--- a/tensorflow/core/graph/gradients.cc
+++ b/tensorflow/core/graph/gradients.cc
@@ -110,7 +110,9 @@ static Node* AddSymGrad(Graph* g, Node* n, gtl::ArraySlice<NodeOut> grads) {
AddNodeAttr("Tout", n->input_types(), &ndef);
NameAttrList func;
func.set_name(n->type_string());
- *(func.mutable_attr()) = n->def().attr();
+ for (const auto& attr : n->attrs()) {
+ (*func.mutable_attr())[attr.first] = attr.second;
+ }
AddNodeAttr("f", func, &ndef);
Status s;
Node* ret = g->AddNode(ndef, &s);
diff --git a/tensorflow/core/graph/optimizer_cse.cc b/tensorflow/core/graph/optimizer_cse.cc
index 47337ce8a26..6b452a1d5dc 100644
--- a/tensorflow/core/graph/optimizer_cse.cc
+++ b/tensorflow/core/graph/optimizer_cse.cc
@@ -189,8 +189,9 @@ bool OptimizerCSE::Optimize(
if (!n->IsOp()) continue;
// Don't prune placeholder nodes.
- if (n->def().op() == "Placeholder" || n->def().op() == "PlaceholderV2" ||
- n->def().op() == "PlaceholderWithDefault") {
+ if (n->type_string() == "Placeholder" ||
+ n->type_string() == "PlaceholderV2" ||
+ n->type_string() == "PlaceholderWithDefault") {
continue;
}
diff --git a/tensorflow/core/kernels/hexagon/graph_transferer.cc b/tensorflow/core/kernels/hexagon/graph_transferer.cc
index 7768acc7714..901a41aec41 100644
--- a/tensorflow/core/kernels/hexagon/graph_transferer.cc
+++ b/tensorflow/core/kernels/hexagon/graph_transferer.cc
@@ -376,7 +376,7 @@ Status GraphTransferer::TransformGraphToAddAggregatedInputNode(
std::vector<DataType> data_types;
std::vector<TensorShape> shapes;
Status status = RemoteFusedGraphExecuteUtils::GetOutputTensorShapeType(
- original_input_node->def(), &data_types, &shapes);
+ original_input_node->attrs(), &data_types, &shapes);
if (status.ok()) {
created_node->AddAttr(
RemoteFusedGraphExecuteUtils::ATTR_OUTPUT_DATA_TYPES, data_types);
@@ -579,7 +579,7 @@ bool GraphTransferer::HasPaddingAndStrides(const Node& node) {
}
bool GraphTransferer::NeedsToAddRank(const Node& node) {
- const string& op_type = node.def().op();
+ const StringPiece op_type(node.type_string());
if (op_type == "Transpose" || op_type == "ExpandDims") {
return true;
}
@@ -587,7 +587,7 @@ bool GraphTransferer::NeedsToAddRank(const Node& node) {
}
bool GraphTransferer::IsPadNode(const Node& node) {
- const string& op_type = node.def().op();
+ const StringPiece op_type(node.type_string());
if (op_type == "Pad") {
return true;
}
@@ -678,7 +678,7 @@ void GraphTransferer::RegisterNodeWithRank(
CHECK_NOTNULL(input0_node);
std::vector<TensorShape> shapes;
Status status = RemoteFusedGraphExecuteUtils::GetOutputTensorShapeType(
- input0_node->def(), nullptr, &shapes);
+ input0_node->attrs(), nullptr, &shapes);
CHECK_EQ(1, shapes.size()) << "Output size should be 1.";
const int const_val_id =
RegisterConstScalar(DT_INT32, shapes.at(0).dims(), id, node.num_inputs());
@@ -728,7 +728,7 @@ void GraphTransferer::RegisterPadNode(
CHECK(input_node->IsConstant());
const TensorProto* tensor_proto = nullptr;
- TF_CHECK_OK(GetNodeAttr(input_node->def(), "value", &tensor_proto));
+ TF_CHECK_OK(GetNodeAttr(input_node->attrs(), "value", &tensor_proto));
CHECK_NOTNULL(tensor_proto);
Tensor const_tensor;
TF_CHECK_OK(MakeTensorFromProto(*tensor_proto, &const_tensor));
@@ -739,7 +739,7 @@ void GraphTransferer::RegisterPadNode(
} else if (const_tensor.shape().dim_size(0) < PAD_WIDTH) {
const int width = const_tensor.shape().dim_size(0);
const TensorProto* proto = nullptr;
- TF_CHECK_OK(GetNodeAttr(input_node->def(), "value", &proto));
+ TF_CHECK_OK(GetNodeAttr(input_node->attrs(), "value", &proto));
Tensor const_tensor;
TF_CHECK_OK(MakeTensorFromProto(*proto, &const_tensor));
CHECK_EQ(DT_INT32, const_tensor.dtype());