Automated rollback of change 137740850

Change: 137747341

28 files changed, 714 insertions, 162 deletions

diff --git a/tensorflow/contrib/cmake/tf_python.cmake b/tensorflow/contrib/cmake/tf_python.cmake
index 8cdecf706a..907158b646 100644
--- a/tensorflow/contrib/cmake/tf_python.cmake
+++ b/tensorflow/contrib/cmake/tf_python.cmake
@@ -94,6 +94,38 @@ function(RELATIVE_PROTOBUF_GENERATE_PYTHON ROOT_DIR SRCS)
   set(${SRCS} ${${SRCS}} PARENT_SCOPE)
 endfunction()
 
+function(RELATIVE_PROTOBUF_GENERATE_CPP SRCS HDRS ROOT_DIR)
+  if(NOT ARGN)
+    message(SEND_ERROR "Error: RELATIVE_PROTOBUF_GENERATE_CPP() called without any proto files")
+    return()
+  endif()
+
+  set(${SRCS})
+  set(${HDRS})
+  foreach(FIL ${ARGN})
+    set(ABS_FIL ${ROOT_DIR}/${FIL})
+    get_filename_component(FIL_WE ${FIL} NAME_WE)
+    get_filename_component(FIL_DIR ${ABS_FIL} PATH)
+    file(RELATIVE_PATH REL_DIR ${ROOT_DIR} ${FIL_DIR})
+
+    list(APPEND ${SRCS} "${CMAKE_CURRENT_BINARY_DIR}/${REL_DIR}/${FIL_WE}.pb.cc")
+    list(APPEND ${HDRS} "${CMAKE_CURRENT_BINARY_DIR}/${REL_DIR}/${FIL_WE}.pb.h")
+
+    add_custom_command(
+      OUTPUT "${CMAKE_CURRENT_BINARY_DIR}/${REL_DIR}/${FIL_WE}.pb.cc"
+             "${CMAKE_CURRENT_BINARY_DIR}/${REL_DIR}/${FIL_WE}.pb.h"
+      COMMAND  ${PROTOBUF_PROTOC_EXECUTABLE}
+      ARGS --cpp_out  ${CMAKE_CURRENT_BINARY_DIR} -I ${ROOT_DIR} ${ABS_FIL} -I ${PROTOBUF_INCLUDE_DIRS}
+      DEPENDS ${ABS_FIL} protobuf
+      COMMENT "Running C++ protocol buffer compiler on ${FIL}"
+      VERBATIM )
+  endforeach()
+
+  set_source_files_properties(${${SRCS}} ${${HDRS}} PROPERTIES GENERATED TRUE)
+  set(${SRCS} ${${SRCS}} PARENT_SCOPE)
+  set(${HDRS} ${${HDRS}} PARENT_SCOPE)
+endfunction()
+
 file(GLOB_RECURSE tf_protos_python_srcs RELATIVE ${tensorflow_source_dir}
     "${tensorflow_source_dir}/tensorflow/core/*.proto"
     "${tensorflow_source_dir}/tensorflow/python/*.proto"
@@ -102,6 +134,12 @@ RELATIVE_PROTOBUF_GENERATE_PYTHON(
     ${tensorflow_source_dir} PYTHON_PROTO_GENFILES ${tf_protos_python_srcs}
 )
 
+RELATIVE_PROTOBUF_GENERATE_CPP(PROTO_SRCS PROTO_HDRS
+    ${tensorflow_source_dir} ${tf_protos_python_srcs}
+)
+
+add_library(tf_python_protos_cc ${PROTO_SRCS} ${PROTO_HDRS})
+
 # tf_python_touchup_modules adds empty __init__.py files to all
 # directories containing Python code, so that Python will recognize
 # them as modules.
@@ -201,6 +239,7 @@ function(GENERATE_PYTHON_OP_LIB tf_python_op_lib_name)
     )
     target_link_libraries(${tf_python_op_lib_name}_gen_python PRIVATE
         tf_protos_cc
+				tf_python_protos_cc
         ${tensorflow_EXTERNAL_LIBRARIES}
     )
 
@@ -312,6 +351,7 @@ target_link_libraries(pywrap_tensorflow
     ${tf_core_gpu_kernels_lib}
     ${tensorflow_EXTERNAL_LIBRARIES}
     tf_protos_cc
+		tf_python_protos_cc
     ${PYTHON_LIBRARIES}
 )
 
diff --git a/tensorflow/core/BUILD b/tensorflow/core/BUILD
index 1c37921afc..79546ccd20 100644
--- a/tensorflow/core/BUILD
+++ b/tensorflow/core/BUILD
@@ -379,6 +379,7 @@ tf_gen_op_libs(
         "no_op",
         "parsing_ops",
         "random_ops",
+        "resource_variable_ops",
         "sdca_ops",
         "script_ops",
         "sendrecv_ops",
@@ -542,6 +543,7 @@ cc_library(
         "//tensorflow/core/kernels:parsing",
         "//tensorflow/core/kernels:random_ops",
         "//tensorflow/core/kernels:required",
+        "//tensorflow/core/kernels:resource_variable_ops",
         "//tensorflow/core/kernels:sdca_ops",
         "//tensorflow/core/kernels:sparse",
         "//tensorflow/core/kernels:state",
diff --git a/tensorflow/core/common_runtime/shape_refiner.cc b/tensorflow/core/common_runtime/shape_refiner.cc
index 1ddd483076..e1500ed1ad 100644
--- a/tensorflow/core/common_runtime/shape_refiner.cc
+++ b/tensorflow/core/common_runtime/shape_refiner.cc
@@ -42,6 +42,8 @@ Status ShapeRefiner::AddNode(const Node* node) {
   // indexed by 'node's input.
   std::vector<Node*> input_nodes(node->num_inputs());
   std::vector<ShapeHandle> input_shapes(node->num_inputs());
+  std::vector<DataType> input_handle_dtypes(node->num_inputs());
+  std::vector<ShapeHandle> input_handle_shapes(node->num_inputs());
   for (const Edge* e : node->in_edges()) {
     if (e->IsControlEdge()) continue;
 
@@ -57,6 +59,15 @@ Status ShapeRefiner::AddNode(const Node* node) {
     DCHECK_GE(e->dst_input(), 0);
     input_nodes[e->dst_input()] = input;
     input_shapes[e->dst_input()] = c->output(e->src_output());
+
+    // Only propagate handle xshape and dtype of edges which are carrying
+    // resource handles.
+    if (e->src()->output_type(e->src_output()) == DT_RESOURCE) {
+      input_handle_dtypes[e->dst_input()] =
+          c->output_handle_dtype(e->src_output());
+      input_handle_shapes[e->dst_input()] =
+          c->output_handle_shape(e->src_output());
+    }
   }
 
   // Get the shape function for this node
@@ -76,9 +87,9 @@ Status ShapeRefiner::AddNode(const Node* node) {
   std::vector<ShapeHandle> input_tensors_as_shapes;
 
   // Create the inference context for this node with the existing input shapes.
-  std::unique_ptr<InferenceContext> c(
-      new InferenceContext(&node->def(), node->op_def(), input_shapes,
-                           input_tensors, input_tensors_as_shapes));
+  std::unique_ptr<InferenceContext> c(new InferenceContext(
+      &node->def(), node->op_def(), input_shapes, input_tensors,
+      input_tensors_as_shapes, input_handle_shapes, input_handle_dtypes));
   if (!c->construction_status().ok()) {
     return c->construction_status();
   }
diff --git a/tensorflow/core/framework/common_shape_fns_test.cc b/tensorflow/core/framework/common_shape_fns_test.cc
index 7196bc8304..ca1326844c 100644
--- a/tensorflow/core/framework/common_shape_fns_test.cc
+++ b/tensorflow/core/framework/common_shape_fns_test.cc
@@ -56,7 +56,7 @@ TEST(CommonShapeFnsTest, NoOutputShapeTest) {
                   .Input({{"data", 0, DT_FLOAT}})
                   .Finalize(&def));
 
-  InferenceContext c(&def, op_def, {S({}), S({10})}, {}, {});
+  InferenceContext c(&def, op_def, {S({}), S({10})}, {}, {}, {}, {});
   TF_EXPECT_OK(NoOutputs(&c));
   EXPECT_EQ(0, c.num_outputs());
 }
@@ -74,14 +74,14 @@ TEST(CommonShapeFnsTest, ScalarShapeTest) {
       NodeDefBuilder("test", "L2Loss").Input("t", 0, DT_FLOAT).Finalize(&def));
 
   {
-    InferenceContext c(&def, op_def, {S({})}, {}, {});
+    InferenceContext c(&def, op_def, {S({})}, {}, {}, {}, {});
     TF_EXPECT_OK(ScalarShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ(0, c.Rank(output));
   }
 
   {
-    InferenceContext c(&def, op_def, {S({1, 23, 4, 4, 2})}, {}, {});
+    InferenceContext c(&def, op_def, {S({1, 23, 4, 4, 2})}, {}, {}, {}, {});
     TF_EXPECT_OK(ScalarShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ(0, c.Rank(output));
@@ -108,7 +108,7 @@ TEST(CommonShapeFnsTest, MatMulShapeTest) {
                   .Finalize(&def));
 
   {
-    InferenceContext c(&def, op_def, {S({2, 3}), S({3, 4})}, {}, {});
+    InferenceContext c(&def, op_def, {S({2, 3}), S({3, 4})}, {}, {}, {}, {});
     TF_EXPECT_OK(MatMulShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ(2, c.Value(c.Dim(output, 0)));
@@ -117,7 +117,7 @@ TEST(CommonShapeFnsTest, MatMulShapeTest) {
 
   {
     // Unknown inner dimension for one
-    InferenceContext c(&def, op_def, {S({2, -1}), S({3, 4})}, {}, {});
+    InferenceContext c(&def, op_def, {S({2, -1}), S({3, 4})}, {}, {}, {}, {});
     TF_EXPECT_OK(MatMulShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ(2, c.Value(c.Dim(output, 0)));
@@ -126,7 +126,7 @@ TEST(CommonShapeFnsTest, MatMulShapeTest) {
 
   {
     // Invalid rank.
-    InferenceContext c(&def, op_def, {S({2}), S({3, 4})}, {}, {});
+    InferenceContext c(&def, op_def, {S({2}), S({3, 4})}, {}, {}, {}, {});
     auto s = MatMulShape(&c);
     EXPECT_FALSE(s.ok());
     EXPECT_TRUE(
@@ -136,7 +136,7 @@ TEST(CommonShapeFnsTest, MatMulShapeTest) {
 
   {
     // Unknown outer dimension
-    InferenceContext c(&def, op_def, {S({2, 3}), S({3, -1})}, {}, {});
+    InferenceContext c(&def, op_def, {S({2, 3}), S({3, -1})}, {}, {}, {}, {});
     TF_EXPECT_OK(MatMulShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ(2, c.Value(c.Dim(output, 0)));
@@ -145,7 +145,7 @@ TEST(CommonShapeFnsTest, MatMulShapeTest) {
 
   {
     // Inner shapes not compatible
-    InferenceContext c(&def, op_def, {S({2, 5}), S({3, 4})}, {}, {});
+    InferenceContext c(&def, op_def, {S({2, 5}), S({3, 4})}, {}, {}, {}, {});
     auto s = MatMulShape(&c);
     EXPECT_FALSE(s.ok());
     EXPECT_TRUE(
@@ -156,7 +156,8 @@ TEST(CommonShapeFnsTest, MatMulShapeTest) {
 
   {
     // Inner shapes not compatible
-    InferenceContext c(&def, op_def, {S({2, 5, 3}), S({3, 5, 4})}, {}, {});
+    InferenceContext c(&def, op_def, {S({2, 5, 3}), S({3, 5, 4})}, {}, {}, {},
+                       {});
     auto s = MatMulShape(&c);
     EXPECT_FALSE(s.ok());
     EXPECT_TRUE(
@@ -174,7 +175,7 @@ TEST(CommonShapeFnsTest, MatMulShapeTest) {
                     .Attr("type", DT_FLOAT)
                     .Finalize(&def));
 
-    InferenceContext c(&def, op_def, {S({3, 2}), S({3, 4})}, {}, {});
+    InferenceContext c(&def, op_def, {S({3, 2}), S({3, 4})}, {}, {}, {}, {});
     auto s = MatMulShape(&c);
     ShapeHandle output = c.output(0);
     EXPECT_EQ(2, c.Value(c.Dim(output, 0)));
@@ -191,7 +192,7 @@ TEST(CommonShapeFnsTest, MatMulShapeTest) {
                     .Attr("type", DT_FLOAT)
                     .Finalize(&def));
 
-    InferenceContext c(&def, op_def, {S({2, 3}), S({4, 3})}, {}, {});
+    InferenceContext c(&def, op_def, {S({2, 3}), S({4, 3})}, {}, {}, {}, {});
     auto s = MatMulShape(&c);
     ShapeHandle output = c.output(0);
     EXPECT_EQ(2, c.Value(c.Dim(output, 0)));
@@ -215,7 +216,7 @@ TEST(CommonShapeFnsTest, BiasAddShapeTest) {
                   .Finalize(&def));
 
   {
-    InferenceContext c(&def, op_def, {S({2, 10}), S({10})}, {}, {});
+    InferenceContext c(&def, op_def, {S({2, 10}), S({10})}, {}, {}, {}, {});
     TF_EXPECT_OK(BiasAddShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ(2, c.Value(c.Dim(output, 0)));
@@ -224,7 +225,7 @@ TEST(CommonShapeFnsTest, BiasAddShapeTest) {
 
   {
     // Unknown ranks.
-    InferenceContext c(&def, op_def, {Unknown(), Unknown()}, {}, {});
+    InferenceContext c(&def, op_def, {Unknown(), Unknown()}, {}, {}, {}, {});
     TF_EXPECT_OK(BiasAddShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_FALSE(c.RankKnown(output));
@@ -232,7 +233,8 @@ TEST(CommonShapeFnsTest, BiasAddShapeTest) {
 
   {
     // Rank > 2
-    InferenceContext c(&def, op_def, {S({4, 3, 4, 2, 15}), S({15})}, {}, {});
+    InferenceContext c(&def, op_def, {S({4, 3, 4, 2, 15}), S({15})}, {}, {}, {},
+                       {});
     TF_EXPECT_OK(BiasAddShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ("[4,3,4,2,15]", c.DebugString(output));
@@ -245,7 +247,7 @@ TEST(CommonShapeFnsTest, BiasAddShapeTest) {
                     .Input("b", 0, DT_FLOAT)
                     .Attr("data_format", "NCHW")
                     .Finalize(&def));
-    InferenceContext c(&def, op_def, {S({2, 3, 4, 5}), S({3})}, {}, {});
+    InferenceContext c(&def, op_def, {S({2, 3, 4, 5}), S({3})}, {}, {}, {}, {});
     TF_EXPECT_OK(BiasAddShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ("[2,3,4,5]", c.DebugString(output));
@@ -258,8 +260,8 @@ TEST(CommonShapeFnsTest, BiasAddShapeTest) {
                     .Input("b", 0, DT_FLOAT)
                     .Attr("data_format", "NCHW")
                     .Finalize(&def));
-    InferenceContext c(&def, op_def, {S({8, 6, 4, 2, 3, 4, 5}), S({3})}, {},
-                       {});
+    InferenceContext c(&def, op_def, {S({8, 6, 4, 2, 3, 4, 5}), S({3})}, {}, {},
+                       {}, {});
     TF_EXPECT_OK(BiasAddShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ("[8,6,4,2,3,4,5]", c.DebugString(output));
@@ -272,7 +274,8 @@ TEST(CommonShapeFnsTest, BiasAddShapeTest) {
                     .Input("b", 0, DT_FLOAT)
                     .Attr("data_format", "NCHW")
                     .Finalize(&def));
-    InferenceContext c(&def, op_def, {S({10, 11, 12}), S({10})}, {}, {});
+    InferenceContext c(&def, op_def, {S({10, 11, 12}), S({10})}, {}, {}, {},
+                       {});
     TF_EXPECT_OK(BiasAddShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ("[10,11,12]", c.DebugString(output));
@@ -280,7 +283,7 @@ TEST(CommonShapeFnsTest, BiasAddShapeTest) {
 
   {
     // Input rank not high enough
-    InferenceContext c(&def, op_def, {S({3}), S({3})}, {}, {});
+    InferenceContext c(&def, op_def, {S({3}), S({3})}, {}, {}, {}, {});
     EXPECT_FALSE(BiasAddShape(&c).ok());
   }
 
@@ -292,7 +295,7 @@ TEST(CommonShapeFnsTest, BiasAddShapeTest) {
                     .Attr("data_format", "NCHW")
                     .Finalize(&def));
     // NCHW format
-    InferenceContext c(&def, op_def, {S({2, 3}), S({3})}, {}, {});
+    InferenceContext c(&def, op_def, {S({2, 3}), S({3})}, {}, {}, {}, {});
     EXPECT_FALSE(BiasAddShape(&c).ok());
   }
 }
@@ -311,7 +314,7 @@ TEST(CommonShapeFnsTest, BiasAddGradShapeTest) {
                   .Finalize(&def));
 
   {
-    InferenceContext c(&def, op_def, {S({2, 10})}, {}, {});
+    InferenceContext c(&def, op_def, {S({2, 10})}, {}, {}, {}, {});
     TF_EXPECT_OK(BiasAddGradShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ(10, c.Value(c.Dim(output, 0)));
@@ -319,7 +322,7 @@ TEST(CommonShapeFnsTest, BiasAddGradShapeTest) {
 
   {
     // Rank > 2
-    InferenceContext c(&def, op_def, {S({5, 7, 2, 10})}, {}, {});
+    InferenceContext c(&def, op_def, {S({5, 7, 2, 10})}, {}, {}, {}, {});
     TF_EXPECT_OK(BiasAddGradShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ(10, c.Value(c.Dim(output, 0)));
@@ -331,7 +334,7 @@ TEST(CommonShapeFnsTest, BiasAddGradShapeTest) {
                     .Input("a", 0, DT_FLOAT)
                     .Attr("data_format", "NCHW")
                     .Finalize(&def));
-    InferenceContext c(&def, op_def, {S({2, 3, 4, 5})}, {}, {});
+    InferenceContext c(&def, op_def, {S({2, 3, 4, 5})}, {}, {}, {}, {});
     TF_EXPECT_OK(BiasAddGradShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ(3, c.Value(c.Dim(output, 0)));
@@ -343,7 +346,8 @@ TEST(CommonShapeFnsTest, BiasAddGradShapeTest) {
                     .Input("a", 0, DT_FLOAT)
                     .Attr("data_format", "NCHW")
                     .Finalize(&def));
-    InferenceContext c(&def, op_def, {S({8, 6, 4, 2, 3, 4, 5})}, {}, {});
+    InferenceContext c(&def, op_def, {S({8, 6, 4, 2, 3, 4, 5})}, {}, {}, {},
+                       {});
     TF_EXPECT_OK(BiasAddGradShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ(3, c.Value(c.Dim(output, 0)));
@@ -355,7 +359,7 @@ TEST(CommonShapeFnsTest, BiasAddGradShapeTest) {
                     .Input("a", 0, DT_FLOAT)
                     .Attr("data_format", "NCHW")
                     .Finalize(&def));
-    InferenceContext c(&def, op_def, {S({10, 11, 12})}, {}, {});
+    InferenceContext c(&def, op_def, {S({10, 11, 12})}, {}, {}, {}, {});
     TF_EXPECT_OK(BiasAddGradShape(&c));
     ShapeHandle output = c.output(0);
     EXPECT_EQ(10, c.Value(c.Dim(output, 0)));
@@ -363,7 +367,7 @@ TEST(CommonShapeFnsTest, BiasAddGradShapeTest) {
 
   {
     // Input rank not high enough
-    InferenceContext c(&def, op_def, {S({3})}, {}, {});
+    InferenceContext c(&def, op_def, {S({3})}, {}, {}, {}, {});
     EXPECT_FALSE(BiasAddGradShape(&c).ok());
   }
 
@@ -374,7 +378,7 @@ TEST(CommonShapeFnsTest, BiasAddGradShapeTest) {
                     .Attr("data_format", "NCHW")
                     .Finalize(&def));
     // NCHW format
-    InferenceContext c(&def, op_def, {S({2, 3})}, {}, {});
+    InferenceContext c(&def, op_def, {S({2, 3})}, {}, {}, {}, {});
     EXPECT_FALSE(BiasAddGradShape(&c).ok());
   }
 }
diff --git a/tensorflow/core/framework/node_def_util.h b/tensorflow/core/framework/node_def_util.h
index 2d16760625..85b83c4d74 100644
--- a/tensorflow/core/framework/node_def_util.h
+++ b/tensorflow/core/framework/node_def_util.h
@@ -66,6 +66,14 @@ void AddNodeAttr(StringPiece name, std::initializer_list<T> value,
       AttrValueMap::value_type(name.ToString(), attr_value));
 }
 
+// Adds an attr to an attr value map.
+template <class T>
+void AddAttr(StringPiece name, T&& value, AttrValueMap* map) {
+  AttrValue attr_value;
+  SetAttrValue(value, &attr_value);
+  map->insert(AttrValueMap::value_type(name.ToString(), attr_value));
+}
+
 class AttrSlice {
  public:
   AttrSlice(const NodeDef& node_def);  // NOLINT(runtime/explicit)
diff --git a/tensorflow/core/framework/resource_mgr.h b/tensorflow/core/framework/resource_mgr.h
index f823462079..30bb2cb708 100644
--- a/tensorflow/core/framework/resource_mgr.h
+++ b/tensorflow/core/framework/resource_mgr.h
@@ -21,6 +21,7 @@ limitations under the License.
 #include <typeinfo>
 #include <unordered_map>
 
+#include "tensorflow/core/framework/common_shape_fns.h"
 #include "tensorflow/core/framework/graph.pb.h"
 #include "tensorflow/core/framework/op_kernel.h"
 #include "tensorflow/core/framework/tensor.h"
diff --git a/tensorflow/core/framework/shape_inference.cc b/tensorflow/core/framework/shape_inference.cc
index da88b6a7ca..4aa32f6a84 100644
--- a/tensorflow/core/framework/shape_inference.cc
+++ b/tensorflow/core/framework/shape_inference.cc
@@ -31,7 +31,9 @@ InferenceContext::InferenceContext(
     const NodeDef* node_def, const OpDef& op_def,
     const std::vector<TensorShapeProto>& input_shapes,
     const std::vector<const Tensor*>& input_tensors,
-    const std::vector<ShapeHandle>& input_tensors_as_shapes)
+    const std::vector<ShapeHandle>& input_tensors_as_shapes,
+    const std::vector<TensorShapeProto>& input_handle_shapes,
+    const std::vector<DataType>& input_handle_dtypes)
     : node_def_(*CHECK_NOTNULL(node_def)) {
   PreInputInit(op_def, input_tensors, input_tensors_as_shapes);
   if (!construction_status_.ok()) return;
@@ -43,19 +45,30 @@ InferenceContext::InferenceContext(
     }
     inputs_.push_back(shape);
   }
-  PostInputInit();
+  std::vector<ShapeHandle> handle_shapes;
+  for (const auto& p : input_handle_shapes) {
+    ShapeHandle shape;
+    construction_status_.Update(MakeShapeFromShapeProto(p, &shape));
+    if (!construction_status_.ok()) {
+      return;
+    }
+    handle_shapes.push_back(shape);
+  }
+  PostInputInit(handle_shapes, input_handle_dtypes);
 }
 
 InferenceContext::InferenceContext(
     const NodeDef* node_def, const OpDef& op_def,
     const std::vector<ShapeHandle>& input_shapes,
     const std::vector<const Tensor*>& input_tensors,
-    const std::vector<ShapeHandle>& input_tensors_as_shapes)
+    const std::vector<ShapeHandle>& input_tensors_as_shapes,
+    const std::vector<ShapeHandle>& input_handle_shapes,
+    const std::vector<DataType>& input_handle_dtypes)
     : node_def_(*CHECK_NOTNULL(node_def)) {
   PreInputInit(op_def, input_tensors, input_tensors_as_shapes);
   if (!construction_status_.ok()) return;
   inputs_ = input_shapes;
-  PostInputInit();
+  PostInputInit(input_handle_shapes, input_handle_dtypes);
 }
 
 InferenceContext::~InferenceContext() {
@@ -124,15 +137,44 @@ void InferenceContext::PreInputInit(
   for (int i = 0; i < num_outputs; ++i) {
     outputs_.push_back(nullptr);
   }
+  output_handle_shape_.reserve(num_outputs);
+  for (int i = 0; i < num_outputs; ++i) {
+    output_handle_shape_.push_back(UnknownShape());
+  }
+  output_handle_dtype_ = std::vector<DataType>(num_outputs, DT_INVALID);
 }
 
-void InferenceContext::PostInputInit() {
+void InferenceContext::PostInputInit(
+    const std::vector<ShapeHandle>& input_handle_shapes,
+    const std::vector<DataType>& input_handle_dtypes) {
   int num_inputs_from_node_def = 0;
   for (const auto& e : input_name_map_) {
     num_inputs_from_node_def =
         std::max(num_inputs_from_node_def, e.second.second);
   }
 
+  // Allow passing empty shapes/dtypes to avoid changing every single test.
+  if (input_handle_shapes.empty()) {
+    input_handle_shape_.resize(inputs_.size());
+  } else {
+    input_handle_shape_ = input_handle_shapes;
+    if (input_handle_shape_.size() != inputs_.size()) {
+      construction_status_ = errors::InvalidArgument(
+          "Wrong number of handle shapes passed; expected ", inputs_.size(),
+          " got ", input_handle_shape_.size());
+    }
+  }
+  if (input_handle_dtypes.empty()) {
+    input_handle_dtype_ = std::vector<DataType>(inputs_.size(), DT_INVALID);
+  } else {
+    input_handle_dtype_ = input_handle_dtypes;
+    if (input_handle_dtype_.size() != inputs_.size()) {
+      construction_status_ = errors::InvalidArgument(
+          "Wrong number of handle dtypes passed; expected ", inputs_.size(),
+          " got ", input_handle_dtype_.size());
+    }
+  }
+
   if (inputs_.size() != num_inputs_from_node_def) {
     construction_status_ = errors::InvalidArgument(
         "Wrong number of inputs passed: ", inputs_.size(), " while ",
@@ -737,6 +779,13 @@ Status InferenceContext::AttachContext(const Status& status) {
                 strings::StrCat(status.error_message(), error_context));
 }
 
+ShapeHandle InferenceContext::input_handle_shape(int idx) {
+  if (!input_handle_shape_[idx].IsSet()) {
+    input_handle_shape_[idx] = UnknownShape();
+  }
+  return input_handle_shape_[idx];
+}
+
 // -----------------------------------------------------------------------------
 // ShapeManager
 // -----------------------------------------------------------------------------
diff --git a/tensorflow/core/framework/shape_inference.h b/tensorflow/core/framework/shape_inference.h
index f5befc15a1..e02490efd9 100644
--- a/tensorflow/core/framework/shape_inference.h
+++ b/tensorflow/core/framework/shape_inference.h
@@ -147,7 +147,9 @@ class InferenceContext {
   InferenceContext(const NodeDef* node_def, const OpDef& op_def,
                    const std::vector<ShapeHandle>& input_shapes,
                    const std::vector<const Tensor*>& input_tensors,
-                   const std::vector<ShapeHandle>& input_tensors_as_shapes);
+                   const std::vector<ShapeHandle>& input_tensors_as_shapes,
+                   const std::vector<ShapeHandle>& input_handle_shapes,
+                   const std::vector<DataType>& input_handle_dtypes);
 
   // <input_tensors> is NULL-padded to be the same size as <input_shapes>.
   //
@@ -162,7 +164,9 @@ class InferenceContext {
   InferenceContext(const NodeDef* node_def, const OpDef& op_def,
                    const std::vector<TensorShapeProto>& input_shapes,
                    const std::vector<const Tensor*>& input_tensors,
-                   const std::vector<ShapeHandle>& input_tensors_as_shapes);
+                   const std::vector<ShapeHandle>& input_tensors_as_shapes,
+                   const std::vector<TensorShapeProto>& input_handle_shapes,
+                   const std::vector<DataType>& input_handle_dtypes);
 
   ~InferenceContext();
 
@@ -231,12 +235,12 @@ class InferenceContext {
     }
     return s->dims_[idx];
   }
-  int32 Rank(ShapeHandle s) { return s->rank_; }
-  bool RankKnown(ShapeHandle s) { return Rank(s) != kUnknownRank; }
-  inline int64 Value(DimensionOrConstant d) {
+  int32 Rank(ShapeHandle s) const { return s->rank_; }
+  bool RankKnown(ShapeHandle s) const { return Rank(s) != kUnknownRank; }
+  inline int64 Value(DimensionOrConstant d) const {
     return d.dim.IsSet() ? d.dim->value_ : d.val;
   }
-  inline bool ValueKnown(DimensionOrConstant d) {
+  inline bool ValueKnown(DimensionOrConstant d) const {
     return Value(d) != kUnknownDim;
   }
 
@@ -391,6 +395,30 @@ class InferenceContext {
 
   Status construction_status() const { return construction_status_; }
 
+  // Methods to propagate shape and dtype on edges of handles. Handles are the
+  // dtype DT_RESOURCE which can be used to access state stored in a
+  // ResourceManager. When ops (such as variables) consume these handles to
+  // produce tensors they might need to know side-information about the shapes
+  // and dtypes of tensors which can be accessed via the handle. These methods
+  // propagate that information. Output handle dtypes and shapes are ignored if
+  // the output tensor is not of type DT_RESOURCE.
+  ShapeHandle input_handle_shape(int idx);
+  DataType input_handle_dtype(int idx) const {
+    return input_handle_dtype_[idx];
+  }
+  void set_output_handle_shape(int idx, ShapeHandle shape) {
+    output_handle_shape_[idx] = shape;
+  }
+  void set_output_handle_dtype(int idx, DataType dtype) {
+    output_handle_dtype_[idx] = dtype;
+  }
+  ShapeHandle output_handle_shape(int idx) const {
+    return output_handle_shape_[idx];
+  }
+  DataType output_handle_dtype(int idx) const {
+    return output_handle_dtype_[idx];
+  }
+
   // Validates the 3 component tensors of a sparse tensor have the proper
   // shapes. This mimics SparseTensor.__init__ in python/framework/ops.py.
   Status ValidateSparseTensor(ShapeHandle indices_shape,
@@ -481,7 +509,8 @@ class InferenceContext {
   void PreInputInit(const OpDef& op_def,
                     const std::vector<const Tensor*>& input_tensors,
                     const std::vector<ShapeHandle>& input_tensors_as_shapes);
-  void PostInputInit();
+  void PostInputInit(const std::vector<ShapeHandle>& input_handle_shapes,
+                     const std::vector<DataType>& input_handle_dtypes);
 
   DimensionHandle GetDimension(const DimensionOrConstant& d);
 
@@ -510,6 +539,11 @@ class InferenceContext {
   std::vector<ShapeHandle> input_tensors_as_shapes_;
   std::vector<bool> requested_input_tensor_as_partial_shape_;
 
+  std::vector<ShapeHandle> input_handle_shape_;
+  std::vector<DataType> input_handle_dtype_;
+  std::vector<ShapeHandle> output_handle_shape_;
+  std::vector<DataType> output_handle_dtype_;
+
   const NodeDef& node_def_;
   NameRangeMap input_name_map_;
   NameRangeMap output_name_map_;
diff --git a/tensorflow/core/framework/shape_inference_test.cc b/tensorflow/core/framework/shape_inference_test.cc
index 06096bfdcc..8d6b4ac021 100644
--- a/tensorflow/core/framework/shape_inference_test.cc
+++ b/tensorflow/core/framework/shape_inference_test.cc
@@ -71,7 +71,8 @@ TEST_F(ShapeInferenceTest, InputOutputByName) {
                .Attr("N", 3)
                .Input(FakeInput(DT_FLOAT))
                .Finalize(&def);
-  InferenceContext c(&def, op_def, {S({1, 5}), S({2, 5}), S({1, 3})}, {}, {});
+  InferenceContext c(&def, op_def, {S({1, 5}), S({2, 5}), S({1, 3})}, {}, {},
+                     {}, {});
 
   EXPECT_EQ("5", c.DebugString(c.NumElements(c.input(0))));
   EXPECT_EQ("10", c.DebugString(c.NumElements(c.input(1))));
@@ -107,7 +108,7 @@ static OpDef MakeOpDef(int num_inputs, int num_outputs) {
 
 TEST_F(ShapeInferenceTest, DimensionOrConstant) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(1, 1), {Unknown()}, {}, {});
+  InferenceContext c(&def, MakeOpDef(1, 1), {Unknown()}, {}, {}, {}, {});
   EXPECT_EQ(InferenceContext::kUnknownDim,
             c.Value(InferenceContext::kUnknownDim));
   EXPECT_EQ(1, c.Value(1));
@@ -122,7 +123,7 @@ TEST_F(ShapeInferenceTest, Run) {
   NodeDef def;
   def.set_name("foo");
   def.set_op("foo_op");
-  InferenceContext c(&def, MakeOpDef(3, 2), {S({1})}, {}, {});
+  InferenceContext c(&def, MakeOpDef(3, 2), {S({1})}, {}, {}, {}, {});
 
   {
     auto fn = [](InferenceContext* c) {
@@ -154,7 +155,7 @@ TEST_F(ShapeInferenceTest, Run) {
 TEST_F(ShapeInferenceTest, RankAndDimInspection) {
   NodeDef def;
   InferenceContext c(&def, MakeOpDef(3, 2), {Unknown(), S({1, -1, 3}), S({})},
-                     {}, {});
+                     {}, {}, {}, {});
   EXPECT_EQ(3, c.num_inputs());
   EXPECT_EQ(2, c.num_outputs());
 
@@ -195,7 +196,8 @@ TEST_F(ShapeInferenceTest, RankAndDimInspection) {
 TEST_F(ShapeInferenceTest, NumElements) {
   NodeDef def;
   InferenceContext c(&def, MakeOpDef(3, 2),
-                     {Unknown(), S({1, -1, 3}), S({5, 4, 3, 2})}, {}, {});
+                     {Unknown(), S({1, -1, 3}), S({5, 4, 3, 2})}, {}, {}, {},
+                     {});
 
   EXPECT_EQ("?", c.DebugString(c.NumElements(c.input(0))));
   EXPECT_EQ("?", c.DebugString(c.NumElements(c.input(1))));
@@ -208,7 +210,8 @@ TEST_F(ShapeInferenceTest, NumElements) {
 
 TEST_F(ShapeInferenceTest, WithRank) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(2, 2), {Unknown(), S({1, -1, 3})}, {}, {});
+  InferenceContext c(&def, MakeOpDef(2, 2), {Unknown(), S({1, -1, 3})}, {}, {},
+                     {}, {});
 
   auto in0 = c.input(0);
   auto in1 = c.input(1);
@@ -246,7 +249,8 @@ TEST_F(ShapeInferenceTest, WithRank) {
 
 TEST_F(ShapeInferenceTest, WithRankAtMost) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(2, 2), {Unknown(), S({1, -1, 3})}, {}, {});
+  InferenceContext c(&def, MakeOpDef(2, 2), {Unknown(), S({1, -1, 3})}, {}, {},
+                     {}, {});
 
   auto in0 = c.input(0);
   auto in1 = c.input(1);
@@ -284,7 +288,8 @@ TEST_F(ShapeInferenceTest, WithRankAtMost) {
 
 TEST_F(ShapeInferenceTest, WithRankAtLeast) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(2, 2), {Unknown(), S({1, -1, 3})}, {}, {});
+  InferenceContext c(&def, MakeOpDef(2, 2), {Unknown(), S({1, -1, 3})}, {}, {},
+                     {}, {});
 
   auto in0 = c.input(0);
   auto in1 = c.input(1);
@@ -322,7 +327,7 @@ TEST_F(ShapeInferenceTest, WithRankAtLeast) {
 
 TEST_F(ShapeInferenceTest, WithValue) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(1, 2), {S({1, -1})}, {}, {});
+  InferenceContext c(&def, MakeOpDef(1, 2), {S({1, -1})}, {}, {}, {}, {});
 
   auto d0 = c.Dim(c.input(0), 0);
   auto d1 = c.Dim(c.input(0), 1);
@@ -363,7 +368,8 @@ TEST_F(ShapeInferenceTest, WithValue) {
 
 TEST_F(ShapeInferenceTest, MergeDim) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(1, 2), {S({2, -1, 2, 1, -1})}, {}, {});
+  InferenceContext c(&def, MakeOpDef(1, 2), {S({2, -1, 2, 1, -1})}, {}, {}, {},
+                     {});
 
   auto d2 = c.Dim(c.input(0), 0);
   auto d_unknown = c.Dim(c.input(0), 1);
@@ -412,7 +418,7 @@ TEST_F(ShapeInferenceTest, MergeShape) {
   InferenceContext c(&def, MakeOpDef(7, 2),
                      {Unknown(), S({1, 2}), S({-1, 2}), S({1, -1}), S({1, 3}),
                       Unknown(), S({1})},
-                     {}, {});
+                     {}, {}, {}, {});
 
   auto s_unknown = c.input(0);
   auto s_1_2 = c.input(1);
@@ -483,7 +489,7 @@ TEST_F(ShapeInferenceTest, MergePrefix) {
                      {
                          Unknown(), S({-1, 2}), S({1, -1, 3}), S({2, 4}),
                      },
-                     {}, {});
+                     {}, {}, {}, {});
 
   auto s_unknown = c.input(0);
   auto s_u_2 = c.input(1);
@@ -536,7 +542,7 @@ TEST_F(ShapeInferenceTest, MergePrefix) {
 TEST_F(ShapeInferenceTest, Subshape) {
   NodeDef def;
   InferenceContext c(&def, MakeOpDef(2, 2), {S({1, 2, 3, -1, 5}), Unknown()},
-                     {}, {});
+                     {}, {}, {}, {});
 
   ShapeHandle unknown = c.input(1);
   ShapeHandle out;
@@ -611,7 +617,7 @@ TEST_F(ShapeInferenceTest, Subshape) {
 TEST_F(ShapeInferenceTest, Concatenate) {
   NodeDef def;
   InferenceContext c(&def, MakeOpDef(3, 2),
-                     {S({1, -1, 3}), S({4, 5}), Unknown()}, {}, {});
+                     {S({1, -1, 3}), S({4, 5}), Unknown()}, {}, {}, {}, {});
 
   auto in0 = c.input(0);
   auto in1 = c.input(1);
@@ -637,7 +643,8 @@ TEST_F(ShapeInferenceTest, Concatenate) {
 
 TEST_F(ShapeInferenceTest, ReplaceDim) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(2, 0), {S({1, 2, 3}), Unknown()}, {}, {});
+  InferenceContext c(&def, MakeOpDef(2, 0), {S({1, 2, 3}), Unknown()}, {}, {},
+                     {}, {});
 
   auto in = c.input(0);
   auto unknown = c.input(1);
@@ -668,7 +675,8 @@ TEST_F(ShapeInferenceTest, ReplaceDim) {
 
 TEST_F(ShapeInferenceTest, MakeShape) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(1, 2), {S({1, 2, 3, -1, 5})}, {}, {});
+  InferenceContext c(&def, MakeOpDef(1, 2), {S({1, 2, 3, -1, 5})}, {}, {}, {},
+                     {});
 
   std::vector<DimensionHandle> dims;
   auto in0 = c.input(0);
@@ -693,7 +701,7 @@ TEST_F(ShapeInferenceTest, MakeShape) {
 TEST_F(ShapeInferenceTest, UnknownShape) {
   NodeDef def;
   std::vector<ShapeHandle> empty;
-  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {});
+  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {}, {}, {});
 
   auto u0 = c.UnknownShape();
   auto u1 = c.UnknownShape();
@@ -705,7 +713,7 @@ TEST_F(ShapeInferenceTest, UnknownShape) {
 TEST_F(ShapeInferenceTest, Scalar) {
   NodeDef def;
   std::vector<ShapeHandle> empty;
-  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {});
+  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {}, {}, {});
 
   auto s0 = c.Scalar();
   EXPECT_EQ("[]", c.DebugString(s0));
@@ -716,7 +724,7 @@ TEST_F(ShapeInferenceTest, Scalar) {
 TEST_F(ShapeInferenceTest, Vector) {
   NodeDef def;
   std::vector<ShapeHandle> empty;
-  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {});
+  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {}, {}, {});
 
   auto s0 = c.Vector(1);
   EXPECT_EQ("[1]", c.DebugString(s0));
@@ -732,7 +740,7 @@ TEST_F(ShapeInferenceTest, Vector) {
 TEST_F(ShapeInferenceTest, Matrix) {
   NodeDef def;
   std::vector<ShapeHandle> empty;
-  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {});
+  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {}, {}, {});
 
   auto s0 = c.Matrix(1, 2);
   EXPECT_EQ("[1,2]", c.DebugString(s0));
@@ -754,7 +762,7 @@ TEST_F(ShapeInferenceTest, Matrix) {
 TEST_F(ShapeInferenceTest, MakeShapeFromShapeTensor) {
   auto create = [&](Tensor* t) {
     NodeDef def;
-    InferenceContext c(&def, MakeOpDef(1, 0), {Unknown()}, {t}, {});
+    InferenceContext c(&def, MakeOpDef(1, 0), {Unknown()}, {t}, {}, {}, {});
     ShapeHandle out;
     Status s = c.MakeShapeFromShapeTensor(0, &out);
     if (s.ok()) {
@@ -806,7 +814,8 @@ TEST_F(ShapeInferenceTest, MakeShapeFromShapeTensor) {
   // Test when the input shape is wrong.
   {
     NodeDef def;
-    InferenceContext c(&def, MakeOpDef(1, 0), {S({1, -1})}, {nullptr}, {});
+    InferenceContext c(&def, MakeOpDef(1, 0), {S({1, -1})}, {nullptr}, {}, {},
+                       {});
     ShapeHandle out;
     EXPECT_EQ("Shape must be rank 1 but is rank 2",
               c.MakeShapeFromShapeTensor(0, &out).error_message());
@@ -816,7 +825,7 @@ TEST_F(ShapeInferenceTest, MakeShapeFromShapeTensor) {
 TEST_F(ShapeInferenceTest, MakeShapeFromShapeProto) {
   NodeDef def;
   std::vector<ShapeHandle> empty;
-  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {});
+  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {}, {}, {});
   TensorShapeProto proto;
 
   // With a set unknown rank.
@@ -852,7 +861,7 @@ TEST_F(ShapeInferenceTest, MakeShapeFromShapeProto) {
 TEST_F(ShapeInferenceTest, MakeDim) {
   NodeDef def;
   std::vector<ShapeHandle> empty;
-  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {});
+  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {}, {}, {});
 
   auto d0 = c.MakeDim(1);
   auto d1 = c.MakeDim(1);
@@ -866,7 +875,7 @@ TEST_F(ShapeInferenceTest, MakeDim) {
 TEST_F(ShapeInferenceTest, UnknownDim) {
   NodeDef def;
   std::vector<ShapeHandle> empty;
-  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {});
+  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {}, {}, {});
 
   auto d0 = c.UnknownDim();
   auto d1 = c.UnknownDim();
@@ -878,7 +887,7 @@ TEST_F(ShapeInferenceTest, UnknownDim) {
 TEST_F(ShapeInferenceTest, UnknownShapeOfRank) {
   NodeDef def;
   std::vector<ShapeHandle> empty;
-  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {});
+  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {}, {}, {});
 
   auto unknown_shape_of_rank_3 = c.UnknownShapeOfRank(3);
   EXPECT_EQ("[?,?,?]", c.DebugString(unknown_shape_of_rank_3));
@@ -892,7 +901,7 @@ TEST_F(ShapeInferenceTest, InputTensors) {
   const Tensor t2 = tensorflow::test::AsTensor<float>({20, 30});
   NodeDef def;
   InferenceContext c(&def, MakeOpDef(3, 2), {S({1}), S({2}), S({3})},
-                     {&t1, &t2}, {});
+                     {&t1, &t2}, {}, {}, {});
 
   EXPECT_TRUE(c.input_tensor(0) == &t1);
   EXPECT_TRUE(c.input_tensor(1) == &t2);
@@ -903,7 +912,8 @@ TEST_F(ShapeInferenceTest, MakeDimForScalarInput) {
   Tensor t1 = tensorflow::test::AsScalar<int32>(20);
   Tensor t2 = tensorflow::test::AsScalar<int32>(-1);
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(2, 2), {S({}), S({})}, {&t1, &t2}, {});
+  InferenceContext c(&def, MakeOpDef(2, 2), {S({}), S({})}, {&t1, &t2}, {}, {},
+                     {});
 
   DimensionHandle d;
   EXPECT_TRUE(c.MakeDimForScalarInput(0, &d).ok());
@@ -934,7 +944,7 @@ TEST_F(ShapeInferenceTest, GetAttr) {
             .ok());
 
   std::vector<ShapeHandle> empty;
-  InferenceContext c(&def, op_reg_data.op_def, empty, {}, {});
+  InferenceContext c(&def, op_reg_data.op_def, empty, {}, {}, {}, {});
   string value;
   EXPECT_TRUE(c.GetAttr("foo", &value).ok());
   EXPECT_EQ("bar", value);
@@ -942,7 +952,8 @@ TEST_F(ShapeInferenceTest, GetAttr) {
 
 TEST_F(ShapeInferenceTest, Divide) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(1, 2), {S({6, -1, 1, 2, 0})}, {}, {});
+  InferenceContext c(&def, MakeOpDef(1, 2), {S({6, -1, 1, 2, 0})}, {}, {}, {},
+                     {});
 
   auto s = c.input(0);
   auto d_6 = c.Dim(s, 0);
@@ -1004,7 +1015,7 @@ TEST_F(ShapeInferenceTest, Divide) {
 
 TEST_F(ShapeInferenceTest, Add) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(1, 2), {S({6, -1, 0})}, {}, {});
+  InferenceContext c(&def, MakeOpDef(1, 2), {S({6, -1, 0})}, {}, {}, {}, {});
 
   auto s = c.input(0);
   auto d_6 = c.Dim(s, 0);
@@ -1055,7 +1066,7 @@ TEST_F(ShapeInferenceTest, Add) {
 
 TEST_F(ShapeInferenceTest, Subtract) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(1, 2), {S({6, -1, 0, 5})}, {}, {});
+  InferenceContext c(&def, MakeOpDef(1, 2), {S({6, -1, 0, 5})}, {}, {}, {}, {});
 
   auto s = c.input(0);
   auto d_6 = c.Dim(s, 0);
@@ -1104,7 +1115,7 @@ TEST_F(ShapeInferenceTest, Subtract) {
 
 TEST_F(ShapeInferenceTest, Multiply) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(1, 2), {S({6, -1, 0, 1})}, {}, {});
+  InferenceContext c(&def, MakeOpDef(1, 2), {S({6, -1, 0, 1})}, {}, {}, {}, {});
 
   auto s = c.input(0);
   auto d_6 = c.Dim(s, 0);
@@ -1157,7 +1168,7 @@ TEST_F(ShapeInferenceTest, Multiply) {
 TEST_F(ShapeInferenceTest, FullyDefined) {
   NodeDef def;
   std::vector<ShapeHandle> empty;
-  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {});
+  InferenceContext c(&def, MakeOpDef(0, 2), empty, {}, {}, {}, {});
 
   // No rank or missing dimension information should return false.
   EXPECT_FALSE(c.FullyDefined(c.UnknownShape()));
@@ -1170,7 +1181,7 @@ TEST_F(ShapeInferenceTest, FullyDefined) {
 
 TEST_F(ShapeInferenceTest, Min) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(1, 2), {S({1, 2, -1, 0})}, {}, {});
+  InferenceContext c(&def, MakeOpDef(1, 2), {S({1, 2, -1, 0})}, {}, {}, {}, {});
 
   auto s = c.input(0);
   auto d_1 = c.Dim(s, 0);
@@ -1218,7 +1229,7 @@ TEST_F(ShapeInferenceTest, Min) {
 
 TEST_F(ShapeInferenceTest, Max) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(1, 2), {S({1, 2, -1})}, {}, {});
+  InferenceContext c(&def, MakeOpDef(1, 2), {S({1, 2, -1})}, {}, {}, {}, {});
 
   auto s = c.input(0);
   auto d_1 = c.Dim(s, 0);
@@ -1256,7 +1267,7 @@ TEST_F(ShapeInferenceTest, Max) {
 TEST_F(ShapeInferenceTest, ValidateSparseTensor_UnknownShapes) {
   NodeDef def;
   InferenceContext c(&def, MakeOpDef(3, 1), {Unknown(), Unknown(), Unknown()},
-                     {}, {});
+                     {}, {}, {}, {});
   EXPECT_EQ(3, c.num_inputs());
   EXPECT_EQ(1, c.num_outputs());
 
@@ -1269,7 +1280,7 @@ TEST_F(ShapeInferenceTest, ValidateSparseTensor_UnknownShapes) {
 TEST_F(ShapeInferenceTest, ValidateSparseTensor_UnknownDims) {
   NodeDef def;
   InferenceContext c(&def, MakeOpDef(3, 1), {S({-1, -1}), S({-1}), S({-1})}, {},
-                     {});
+                     {}, {}, {});
   EXPECT_EQ(3, c.num_inputs());
   EXPECT_EQ(1, c.num_outputs());
 
@@ -1281,8 +1292,8 @@ TEST_F(ShapeInferenceTest, ValidateSparseTensor_UnknownDims) {
 
 TEST_F(ShapeInferenceTest, ValidateSparseTensor_InvalidIndicesRank) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(3, 1), {S({-1}), S({-1}), S({-1})}, {},
-                     {});
+  InferenceContext c(&def, MakeOpDef(3, 1), {S({-1}), S({-1}), S({-1})}, {}, {},
+                     {}, {});
   EXPECT_EQ(3, c.num_inputs());
   EXPECT_EQ(1, c.num_outputs());
 
@@ -1295,8 +1306,8 @@ TEST_F(ShapeInferenceTest, ValidateSparseTensor_InvalidIndicesRank) {
 
 TEST_F(ShapeInferenceTest, ValidateSparseTensor_InvalidNumElements) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(3, 1), {S({5, 3}), S({4}), S({3})}, {},
-                     {});
+  InferenceContext c(&def, MakeOpDef(3, 1), {S({5, 3}), S({4}), S({3})}, {}, {},
+                     {}, {});
   EXPECT_EQ(3, c.num_inputs());
   EXPECT_EQ(1, c.num_outputs());
 
@@ -1309,8 +1320,8 @@ TEST_F(ShapeInferenceTest, ValidateSparseTensor_InvalidNumElements) {
 
 TEST_F(ShapeInferenceTest, ValidateSparseTensor_InvalidRank) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(3, 1), {S({5, 3}), S({5}), S({4})}, {},
-                     {});
+  InferenceContext c(&def, MakeOpDef(3, 1), {S({5, 3}), S({5}), S({4})}, {}, {},
+                     {}, {});
   EXPECT_EQ(3, c.num_inputs());
   EXPECT_EQ(1, c.num_outputs());
 
@@ -1324,7 +1335,7 @@ TEST_F(ShapeInferenceTest, ValidateSparseTensor_InvalidRank) {
 TEST_F(ShapeInferenceTest, ValidateSparseTensor_UnknownNumIndexElements) {
   NodeDef def;
   InferenceContext c(&def, MakeOpDef(3, 1), {S({-1, 3}), S({5}), S({3})}, {},
-                     {});
+                     {}, {}, {});
   EXPECT_EQ(3, c.num_inputs());
   EXPECT_EQ(1, c.num_outputs());
 
@@ -1337,7 +1348,7 @@ TEST_F(ShapeInferenceTest, ValidateSparseTensor_UnknownNumIndexElements) {
 TEST_F(ShapeInferenceTest, ValidateSparseTensor_UnknownNumValueElements) {
   NodeDef def;
   InferenceContext c(&def, MakeOpDef(3, 1), {S({5, 3}), S({-1}), S({3})}, {},
-                     {});
+                     {}, {}, {});
   EXPECT_EQ(3, c.num_inputs());
   EXPECT_EQ(1, c.num_outputs());
 
@@ -1350,7 +1361,7 @@ TEST_F(ShapeInferenceTest, ValidateSparseTensor_UnknownNumValueElements) {
 TEST_F(ShapeInferenceTest, ValidateSparseTensor_UnknownIndexRank) {
   NodeDef def;
   InferenceContext c(&def, MakeOpDef(3, 1), {S({5, -1}), S({5}), S({3})}, {},
-                     {});
+                     {}, {}, {});
   EXPECT_EQ(3, c.num_inputs());
   EXPECT_EQ(1, c.num_outputs());
 
@@ -1363,7 +1374,7 @@ TEST_F(ShapeInferenceTest, ValidateSparseTensor_UnknownIndexRank) {
 TEST_F(ShapeInferenceTest, ValidateSparseTensor_UnknownShapeRank) {
   NodeDef def;
   InferenceContext c(&def, MakeOpDef(3, 1), {S({5, 3}), S({5}), S({-1})}, {},
-                     {});
+                     {}, {}, {});
   EXPECT_EQ(3, c.num_inputs());
   EXPECT_EQ(1, c.num_outputs());
 
@@ -1375,8 +1386,8 @@ TEST_F(ShapeInferenceTest, ValidateSparseTensor_UnknownShapeRank) {
 
 TEST_F(ShapeInferenceTest, ValidateSparseTensor) {
   NodeDef def;
-  InferenceContext c(&def, MakeOpDef(3, 1), {S({5, 3}), S({5}), S({3})}, {},
-                     {});
+  InferenceContext c(&def, MakeOpDef(3, 1), {S({5, 3}), S({5}), S({3})}, {}, {},
+                     {}, {});
   EXPECT_EQ(3, c.num_inputs());
   EXPECT_EQ(1, c.num_outputs());
 
diff --git a/tensorflow/core/framework/shape_inference_testutil.cc b/tensorflow/core/framework/shape_inference_testutil.cc
index ed1d3ec520..a225824f82 100644
--- a/tensorflow/core/framework/shape_inference_testutil.cc
+++ b/tensorflow/core/framework/shape_inference_testutil.cc
@@ -44,8 +44,7 @@ Status ShapeInferenceTestutil::InferShapes(ShapeInferenceTestOp op,
   }
 
   shape_inference::InferenceContext c(&op.node_def, op_reg_data->op_def,
-                                      in_shapes, op.input_tensors,
-                                      {} /* input_tensors_as_shapes */);
+                                      in_shapes, op.input_tensors, {}, {}, {});
   TF_RETURN_IF_ERROR(c.construction_status());
   if (op_reg_data->shape_inference_fn == nullptr) {
     return errors::InvalidArgument(
diff --git a/tensorflow/core/framework/tensor.h b/tensorflow/core/framework/tensor.h
index 92915685f5..47d74d4def 100644
--- a/tensorflow/core/framework/tensor.h
+++ b/tensorflow/core/framework/tensor.h
@@ -435,6 +435,7 @@ class Tensor {
   friend class VariableOp;            // For access to set_shape
   friend class AutoReloadVariableOp;  // For access to set_shape
   friend class TensorTestHelper;      // For access to set_shape
+  friend class CreateVariableOp;
 
   // Creates a tensor with the input datatype, shape and buf.
   //
diff --git a/tensorflow/core/kernels/BUILD b/tensorflow/core/kernels/BUILD
index 34954f0066..1954ebdc10 100644
--- a/tensorflow/core/kernels/BUILD
+++ b/tensorflow/core/kernels/BUILD
@@ -1031,6 +1031,18 @@ tf_kernel_library(
 )
 
 tf_kernel_library(
+    name = "resource_variable_ops",
+    srcs = ["resource_variable_ops.cc"],
+    deps = [
+        ":variable_ops",
+        "//tensorflow/core:framework",
+        "//tensorflow/core:lib",
+        "//tensorflow/core:resource_variable_ops_op_lib",
+        "//third_party/eigen3",
+    ],
+)
+
+tf_kernel_library(
     name = "fact_op",
     prefix = "fact_op",
     deps = [
diff --git a/tensorflow/core/kernels/resource_variable_ops.cc b/tensorflow/core/kernels/resource_variable_ops.cc
new file mode 100644
index 0000000000..fbe66e8386
--- /dev/null
+++ b/tensorflow/core/kernels/resource_variable_ops.cc
@@ -0,0 +1,49 @@
+/* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+==============================================================================*/
+
+#include "tensorflow/core/framework/op_kernel.h"
+#include "tensorflow/core/framework/register_types.h"
+#include "tensorflow/core/framework/resource_mgr.h"
+#include "tensorflow/core/kernels/variable_ops.h"
+#include "tensorflow/core/lib/core/errors.h"
+#include "tensorflow/core/platform/mutex.h"
+#include "tensorflow/core/platform/types.h"
+
+namespace tensorflow {
+
+REGISTER_RESOURCE_HANDLE_KERNEL(Var);
+
+class CreateVariableOp : public OpKernel {
+ public:
+  CreateVariableOp(OpKernelConstruction* c) : OpKernel(c) {
+    OP_REQUIRES_OK(c, c->GetAttr("dtype", &dtype_));
+  }
+
+  void Compute(OpKernelContext* c) override {
+    Var* var = new Var(dtype_);
+    var->Ref();
+    core::ScopedUnref ur(var);
+    OP_REQUIRES_OK(c, CreateResource<Var>(c, HandleFromInput(c, 0), var));
+    // TODO(apassos): this currently does not initialize the tensor, so it's
+    // pointless, other than checking construction in tests. Fix this.
+  }
+
+ private:
+  DataType dtype_;
+};
+REGISTER_KERNEL_BUILDER(Name("CreateVariableOp").Device(DEVICE_CPU),
+                        CreateVariableOp);
+
+}  // namespace tensorflow
diff --git a/tensorflow/core/kernels/variable_ops.h b/tensorflow/core/kernels/variable_ops.h
index f754629a72..f44f94c51b 100644
--- a/tensorflow/core/kernels/variable_ops.h
+++ b/tensorflow/core/kernels/variable_ops.h
@@ -26,6 +26,26 @@ limitations under the License.
 
 namespace tensorflow {
 
+// Resource stored by variables in the resource manager.
+class Var : public ResourceBase {
+ public:
+  explicit Var(DataType dtype) : tensor_(dtype) {}
+  mutex* mu() { return &mu_; }
+  Tensor* tensor() { return &tensor_; }
+
+  string DebugString() override {
+    return strings::StrCat(DataTypeString(tensor_.dtype()), "/",
+                           tensor_.shape().DebugString());
+  }
+
+ private:
+  mutex mu_;
+  Tensor tensor_;
+
+  ~Var() override {}
+  TF_DISALLOW_COPY_AND_ASSIGN(Var);
+};
+
 class VariableOp : public OpKernel {
  public:
   explicit VariableOp(OpKernelConstruction* context) : OpKernel(context) {
@@ -59,25 +79,6 @@ class VariableOp : public OpKernel {
   }
 
  private:
-  class Var : public ResourceBase {
-   public:
-    explicit Var(DataType dtype) : tensor_(dtype) {}
-    mutex* mu() { return &mu_; }
-    Tensor* tensor() { return &tensor_; }
-
-    string DebugString() override {
-      return strings::StrCat(DataTypeString(tensor_.dtype()), "/",
-                             tensor_.shape().DebugString());
-    }
-
-   private:
-    mutex mu_;
-    Tensor tensor_;
-
-    ~Var() override {}
-    TF_DISALLOW_COPY_AND_ASSIGN(Var);
-  };
-
   DataType dtype_;
   TensorShape shape_;
 
diff --git a/tensorflow/core/ops/array_ops.cc b/tensorflow/core/ops/array_ops.cc
index 6e076a092e..58b95fcff1 100644
--- a/tensorflow/core/ops/array_ops.cc
+++ b/tensorflow/core/ops/array_ops.cc
@@ -1252,7 +1252,12 @@ REGISTER_OP("Identity")
     .Input("input: T")
     .Output("output: T")
     .Attr("T: type")
-    .SetShapeFn(shape_inference::UnchangedShape)
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      c->set_output(0, c->input(0));
+      c->set_output_handle_dtype(0, c->input_handle_dtype(0));
+      c->set_output_handle_shape(0, c->input_handle_shape(0));
+      return Status::OK();
+    })
     .Doc(R"Doc(
 Return a tensor with the same shape and contents as the input tensor or value.
 )Doc");
diff --git a/tensorflow/core/ops/array_ops_test.cc b/tensorflow/core/ops/array_ops_test.cc
index 8679739b70..90f3c60b64 100644
--- a/tensorflow/core/ops/array_ops_test.cc
+++ b/tensorflow/core/ops/array_ops_test.cc
@@ -15,7 +15,9 @@ limitations under the License.
 
 #include "tensorflow/core/framework/graph.pb.h"
 #include "tensorflow/core/framework/node_def_builder.h"
+#include "tensorflow/core/framework/node_def_util.h"
 #include "tensorflow/core/framework/op.h"
+#include "tensorflow/core/framework/shape_inference.h"
 #include "tensorflow/core/framework/shape_inference_testutil.h"
 #include "tensorflow/core/framework/tensor_testutil.h"
 #include "tensorflow/core/lib/core/status_test_util.h"
@@ -153,6 +155,21 @@ TEST(ArrayOpsTest, UnchangedShapes_ShapeFn) {
   INFER_OK(op, "[1,2,?,4,5];?;?", "in0");
 }
 
+TEST(ArrayOpsTest, Identity_ShapeFnHandles) {
+  const char* op_name = "Identity";
+  ShapeInferenceTestOp op(op_name);
+  // Check that handle dtypes are preserved.
+  const OpRegistrationData* op_reg_data;
+  TF_ASSERT_OK(OpRegistry::Global()->LookUp(op.name, &op_reg_data));
+  shape_inference::InferenceContext c(&op.node_def, op_reg_data->op_def,
+                                      {TensorShapeProto()}, {}, {}, {},
+                                      {DT_BOOL});
+  TF_ASSERT_OK(c.construction_status());
+  ASSERT_TRUE(op_reg_data->shape_inference_fn != nullptr);
+  TF_ASSERT_OK(c.Run(op_reg_data->shape_inference_fn));
+  EXPECT_TRUE(c.output_handle_dtype(0) == DT_BOOL);
+}
+
 TEST(ArrayOpsTest, Diag_ShapeFn) {
   ShapeInferenceTestOp op("Diag");
   INFER_OK(op, "?", "?");
diff --git a/tensorflow/core/ops/math_ops.cc b/tensorflow/core/ops/math_ops.cc
index 8d3d9310a4..ff00214da3 100644
--- a/tensorflow/core/ops/math_ops.cc
+++ b/tensorflow/core/ops/math_ops.cc
@@ -911,6 +911,19 @@ REGISTER_OP("Select")
     .Output("output: T")
     .Attr("T: type")
     .SetShapeFn([](InferenceContext* c) {
+      // Merge handle shape and dtype if applicable.
+      if (c->input_handle_dtype(1) != c->input_handle_dtype(2)) {
+        // TODO(apassos) resolve this in the manner of b/32476923
+        return errors::InvalidArgument(
+            "Trying to merge handles pointing to different dtypes.");
+      }
+      c->set_output_handle_dtype(0, c->input_handle_dtype(1));
+      ShapeHandle output_handle_shape;
+      TF_RETURN_IF_ERROR(c->Merge(c->input_handle_shape(1),
+                                  c->input_handle_shape(2),
+                                  &output_handle_shape));
+      c->set_output_handle_shape(0, output_handle_shape);
+
       // The inputs 'then' and 'else' must have the same shape.
       ShapeHandle data = c->input(1);
       ShapeHandle other = c->input(2);
@@ -961,8 +974,9 @@ REGISTER_OP("Select")
       }
 
       c->set_output(0, data);
+
       return Status::OK();
-   })
+    })
     .Doc(R"doc(
 Selects elements from `t` or `e`, depending on `condition`.
 
diff --git a/tensorflow/core/ops/math_ops_test.cc b/tensorflow/core/ops/math_ops_test.cc
index 79ae187342..6a1cc8e7eb 100644
--- a/tensorflow/core/ops/math_ops_test.cc
+++ b/tensorflow/core/ops/math_ops_test.cc
@@ -216,6 +216,37 @@ TEST(MathOpsTest, Select_ShapeFn) {
   INFER_OK(op, "[2,?,?];[?,?,3];[?,2,?]", "[d0_0,d2_1,d1_2]");
   INFER_ERROR("Dimension 2 in both shapes must be equal, but are 3 and 5", op,
               "[2,?,5];[?,?,3];[?,2,?]");
+
+  // Test that handle shapes were merged.
+  const OpRegistrationData* op_reg_data;
+  TF_ASSERT_OK(OpRegistry::Global()->LookUp(op.name, &op_reg_data));
+  TensorShapeProto i0;
+  i0.add_dim()->set_size(1);
+  i0.add_dim()->set_size(-1);
+  TensorShapeProto i1;
+  i1.add_dim()->set_size(-1);
+  i1.add_dim()->set_size(2);
+
+  ASSERT_TRUE(op_reg_data->shape_inference_fn != nullptr);
+  shape_inference::InferenceContext c(
+      &op.node_def, op_reg_data->op_def,
+      {TensorShapeProto(), TensorShapeProto(), TensorShapeProto()}, {}, {},
+      {TensorShapeProto(), i0, i1}, {});
+  TF_ASSERT_OK(c.construction_status());
+  TF_ASSERT_OK(c.Run(op_reg_data->shape_inference_fn));
+  EXPECT_TRUE(c.FullyDefined(c.output_handle_shape(0)));
+  EXPECT_EQ("[1,2]", c.DebugString(c.output_handle_shape(0)));
+
+  // Expect an error when the shapes can't be merged.
+  TensorShapeProto i2;
+  i1.add_dim()->set_size(2);
+  i1.add_dim()->set_size(2);
+  shape_inference::InferenceContext c2(
+      &op.node_def, op_reg_data->op_def,
+      {TensorShapeProto(), TensorShapeProto(), TensorShapeProto()}, {}, {},
+      {TensorShapeProto(), i0, i2}, {});
+  TF_ASSERT_OK(c.construction_status());
+  EXPECT_FALSE(c2.Run(op_reg_data->shape_inference_fn).ok());
 }
 
 TEST(MathOpsTest, Range_ShapeFn) {
diff --git a/tensorflow/core/ops/resource_variable_ops.cc b/tensorflow/core/ops/resource_variable_ops.cc
new file mode 100644
index 0000000000..6211b07ac5
--- /dev/null
+++ b/tensorflow/core/ops/resource_variable_ops.cc
@@ -0,0 +1,80 @@
+// Copyright 2016 The TensorFlow Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+// ============================================================================
+
+#include "tensorflow/core/framework/node_def_util.h"
+#include "tensorflow/core/framework/op.h"
+#include "tensorflow/core/framework/resource_mgr.h"
+#include "tensorflow/core/framework/shape_inference.h"
+
+namespace tensorflow {
+
+REGISTER_OP("VarHandleOp")
+    .Attr("container: string = ''")
+    .Attr("shared_name: string = ''")
+    .Attr("dtype: type")
+    .Attr("shape: shape")
+    .Output("resource: resource")
+    .SetIsStateful()
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      c->set_output(0, c->Scalar());
+      DataType t;
+      c->GetAttr("dtype", &t);
+      c->set_output_handle_dtype(0, t);
+      TensorShapeProto p;
+      c->GetAttr("shape", &p);
+      shape_inference::ShapeHandle s;
+      TF_RETURN_IF_ERROR(c->MakeShapeFromShapeProto(p, &s));
+      c->set_output_handle_shape(0, s);
+      return Status::OK();
+    })
+    .Doc(R"(
+Creates a handle to a Variable resource.
+
+container: the container this variable is placed in.
+shared_name: the name by which this variable is referred to.
+dtype: the type of this variable. Must agree with the dtypes
+  of all ops using this variable.
+shape: The (possibly partially specified) shape of this variable.
+)");
+
+REGISTER_OP("CreateVariableOp")
+    .Input("resource: resource")
+    .Input("value: dtype")
+    .Attr("dtype: type")
+    .SetShapeFn([](shape_inference::InferenceContext* c) {
+      DataType handle_dtype = c->input_handle_dtype(0);
+      DataType value_dtype;
+      c->GetAttr("dtype", &value_dtype);
+      if (handle_dtype != value_dtype) {
+        return errors::InvalidArgument(
+            "Trying to initialize handle for variable with wrong dtype. "
+            "Expected ",
+            handle_dtype, " got ", value_dtype);
+      }
+      shape_inference::ShapeHandle s = c->input_handle_shape(0);
+      shape_inference::ShapeHandle value_shape = c->input(1);
+      shape_inference::ShapeHandle unused;
+      TF_RETURN_IF_ERROR(c->Merge(s, value_shape, &unused));
+      return Status::OK();
+    })
+    .Doc(R"(
+Creates a variable resource.
+
+resource: handle to the resource in which to store the variable.
+value: the value to set the new tensor to use.
+dtype: the dtype of the value.
+)");
+
+}  // namespace tensorflow
diff --git a/tensorflow/python/BUILD b/tensorflow/python/BUILD
index dcb6f52605..da875c081a 100644
--- a/tensorflow/python/BUILD
+++ b/tensorflow/python/BUILD
@@ -218,23 +218,6 @@ cc_library(
 )
 
 cc_library(
-    name = "cpp_shape_inference",
-    srcs = ["framework/cpp_shape_inference.cc"],
-    hdrs = ["framework/cpp_shape_inference.h"],
-    copts = ["-Wno-sign-compare"],
-    visibility = ["//visibility:public"],
-    deps = [
-        ":numpy_lib",
-        ":py_func_lib",
-        "//tensorflow/c:tf_status_helper",
-        "//tensorflow/core:framework",
-        "//tensorflow/core:protos_cc",
-        "//third_party/py/numpy:headers",
-        "//util/python:python_headers",
-    ],
-)
-
-cc_library(
     name = "python_op_gen_main",
     srcs = [
         "framework/python_op_gen_main.cc",
@@ -284,6 +267,7 @@ py_library(
     ],
     srcs_version = "PY2AND3",
     deps = [
+        ":cpp_shape_inference_proto_py",
         ":framework_for_generated_wrappers",
         ":pywrap_tensorflow",
     ],
@@ -661,6 +645,11 @@ tf_gen_op_wrapper_private_py(
 )
 
 tf_gen_op_wrapper_private_py(
+    name = "resource_variable_ops_gen",
+    require_shape_functions = True,
+)
+
+tf_gen_op_wrapper_private_py(
     name = "script_ops_gen",
     require_shape_functions = True,
 )
@@ -990,6 +979,16 @@ py_library(
 )
 
 py_library(
+    name = "resource_variable_ops",
+    srcs = ["ops/resource_variable_ops.py"],
+    srcs_version = "PY2AND3",
+    deps = [
+        ":framework",
+        ":resource_variable_ops_gen",
+    ],
+)
+
+py_library(
     name = "nn",
     srcs = ["ops/nn.py"],
     srcs_version = "PY2AND3",
@@ -1409,6 +1408,7 @@ py_library(
         ":partitioned_variables",
         ":random_ops",
         ":random_ops_gen",
+        ":resource_variable_ops",
         ":resources",
         ":rnn",
         ":rnn_cell",
@@ -1690,6 +1690,7 @@ tf_proto_library(
         ["**/*.proto"],
         exclude = [
             "util/protobuf/compare_test.proto",
+            "framework/cpp_shape_inference.proto",
         ],
     ),
     go_api_version = 2,
@@ -1701,6 +1702,13 @@ tf_proto_library_py(
     srcs = ["util/protobuf/compare_test.proto"],
 )
 
+tf_proto_library(
+    name = "cpp_shape_inference_proto",
+    srcs = ["framework/cpp_shape_inference.proto"],
+    cc_api_version = 2,
+    cc_libs = ["//tensorflow/core:protos_all_cc"],
+)
+
 py_test(
     name = "protobuf_compare_test",
     size = "small",
@@ -1767,6 +1775,24 @@ py_library(
     ],
 )
 
+cc_library(
+    name = "cpp_shape_inference",
+    srcs = ["framework/cpp_shape_inference.cc"],
+    hdrs = ["framework/cpp_shape_inference.h"],
+    copts = ["-Wno-sign-compare"],
+    visibility = ["//visibility:public"],
+    deps = [
+        ":cpp_shape_inference_proto_cc",
+        ":numpy_lib",
+        ":py_func_lib",
+        "//tensorflow/c:tf_status_helper",
+        "//tensorflow/core:framework",
+        "//tensorflow/core:protos_cc",
+        "//third_party/py/numpy:headers",
+        "//util/python:python_headers",
+    ],
+)
+
 cuda_py_tests(
     name = "device_lib_test",
     size = "small",
diff --git a/tensorflow/python/framework/common_shapes.py b/tensorflow/python/framework/common_shapes.py
index a0c97f5f8f..09afe56b19 100644
--- a/tensorflow/python/framework/common_shapes.py
+++ b/tensorflow/python/framework/common_shapes.py
@@ -20,8 +20,8 @@ from __future__ import print_function
 import numpy as np
 import six.moves
 
-from tensorflow.core.framework import tensor_shape_pb2
 from tensorflow.python import pywrap_tensorflow
+from tensorflow.python.framework import cpp_shape_inference_pb2
 from tensorflow.python.framework import errors
 from tensorflow.python.framework import tensor_shape
 from tensorflow.python.framework import tensor_util
@@ -567,8 +567,12 @@ def call_cpp_shape_fn(op, input_tensors_needed=None,
       the C++ shape function.
 
   Returns:
-    A TensorShape list of the output shapes of the op, as computed using the
-    C++ shape inference function registered for the op.
+    A dictionary with the following keys:
+      shapes: A TensorShape list of the output shapes of the op, as computed
+        using the C++ shape inference function registered for the op.
+      handle_shapes: A TensorShape list of the shapes for handle outputs, if
+         any.
+      handle_dtypes: A list of DataType enums for the handle outputs, if any.
 
   Raises:
     ValueError: If the C++ shape function returned an error (e.g. because the
@@ -576,8 +580,16 @@ def call_cpp_shape_fn(op, input_tensors_needed=None,
     according to the shape function).
   """
   node_def_str = op.node_def.SerializeToString()
-  input_shapes = [i.get_shape().as_proto().SerializeToString() for i in
-                  op.inputs]
+
+  def tensor_to_inference_result(t):
+    r = cpp_shape_inference_pb2.CppShapeInferenceResult()
+    r.shape.CopyFrom(t.get_shape().as_proto())
+    # pylint: disable=protected-access
+    r.handle_shape.CopyFrom(t._handle_shape)
+    r.handle_dtype = t._handle_dtype
+    # pylint: enable=protected-access
+    return r.SerializeToString()
+  input_shapes = [tensor_to_inference_result(i) for i in op.inputs]
 
   input_tensors = [None for i in input_shapes]
   if input_tensors_needed:
@@ -596,10 +608,13 @@ def call_cpp_shape_fn(op, input_tensors_needed=None,
     raise ValueError(err.message)
 
   # Convert TensorShapeProto values in output_shapes.
-  result = [
-      tensor_shape.TensorShape(tensor_shape_pb2.TensorShapeProto.FromString(s))
+  result_protos = [
+      cpp_shape_inference_pb2.CppShapeInferenceResult().FromString(s)
       for s in output_shapes
   ]
+  result = [r.shape for r in result_protos]
+  result_handle_shapes = [r.handle_shape for r in result_protos]
+  result_handle_dtypes = [r.handle_dtype for r in result_protos]
 
   if debug_python_shape_fn:
     try:
@@ -616,4 +631,6 @@ def call_cpp_shape_fn(op, input_tensors_needed=None,
                str(result), str(python_result), str(op.node_def),
                ",".join([str(i.get_shape()) for i in op.inputs])))
 
-  return result
+  return {"shapes": result,
+          "handle_shapes": result_handle_shapes,
+          "handle_dtypes": result_handle_dtypes}
diff --git a/tensorflow/python/framework/cpp_shape_inference.cc b/tensorflow/python/framework/cpp_shape_inference.cc
index bb5a57e617..57b85e8118 100644
--- a/tensorflow/python/framework/cpp_shape_inference.cc
+++ b/tensorflow/python/framework/cpp_shape_inference.cc
@@ -20,12 +20,32 @@ limitations under the License.
 #include "tensorflow/core/framework/shape_inference.h"
 #include "tensorflow/core/lib/core/errors.h"
 #include "tensorflow/core/lib/strings/strcat.h"
+#include "tensorflow/python/framework/cpp_shape_inference.pb.h"
 #include "tensorflow/python/lib/core/py_func.h"
 
 namespace tensorflow {
 namespace swig {
 namespace {
 
+void ProtoFromShapeHandle(tensorflow::shape_inference::ShapeHandle s,
+                          tensorflow::shape_inference::InferenceContext* c,
+                          TensorShapeProto* out) {
+  if (c->RankKnown(s)) {
+    const int32 rank = c->Rank(s);
+    for (int i = 0; i < rank; ++i) {
+      shape_inference::DimensionHandle d = c->Dim(s, i);
+      auto* out_dim = out->add_dim();
+      if (c->ValueKnown(d)) {
+        out_dim->set_size(c->Value(d));
+      } else {
+        out_dim->set_size(-1);
+      }
+    }
+  } else {
+    out->set_unknown_rank(true);
+  }
+}
+
 Status RunCppShapeInferenceImpl(
     const string& serialized_node_def,
     const std::vector<string>& input_serialized_shapes,
@@ -49,12 +69,21 @@ Status RunCppShapeInferenceImpl(
 
   // Convert input shapes.
   std::vector<TensorShapeProto> input_shapes;
+  std::vector<TensorShapeProto> input_handle_shapes;
+  std::vector<DataType> input_handle_dtypes;
   input_shapes.resize(input_serialized_shapes.size());
+  input_handle_shapes.resize(input_serialized_shapes.size());
+  input_handle_dtypes.resize(input_serialized_shapes.size());
+  CppShapeInferenceResult tmp;
   for (int i = 0; i < input_serialized_shapes.size(); ++i) {
-    if (!input_shapes[i].ParseFromString(input_serialized_shapes[i])) {
+    tmp.Clear();
+    if (!tmp.ParseFromString(input_serialized_shapes[i])) {
       return errors::InvalidArgument(
           "Error parsing shape proto during cpp shape inference");
     }
+    input_shapes[i].Swap(tmp.mutable_shape());
+    input_handle_dtypes[i] = tmp.handle_dtype();
+    input_handle_shapes[i].Swap(tmp.mutable_handle_shape());
   }
 
   // Convert input tensor values;
@@ -73,34 +102,23 @@ Status RunCppShapeInferenceImpl(
   }
 
   // Run shape inference.
-  // TODO(cwhipkey): pass a value for input_tensors_as_shapes.
   tensorflow::shape_inference::InferenceContext c(
       &node, op_reg_data->op_def, input_shapes, input_tensors,
-      {} /* input_tensors_as_shapes */);
+      {} /* input_tensors_as_shapes */, input_handle_shapes,
+      input_handle_dtypes);
   TF_RETURN_IF_ERROR(c.construction_status());
 
   TF_RETURN_IF_ERROR(c.Run(op_reg_data->shape_inference_fn));
 
   // Convert output shapes.
   output_tensor_shape_protos->resize(c.num_outputs());
-  TensorShapeProto out;
+  CppShapeInferenceResult out;
   for (int i = 0; i < c.num_outputs(); ++i) {
-    shape_inference::ShapeHandle s = c.output(i);
     out.Clear();
-    if (c.RankKnown(s)) {
-      const int32 rank = c.Rank(s);
-      for (int i = 0; i < rank; ++i) {
-        shape_inference::DimensionHandle d = c.Dim(s, i);
-        auto* out_dim = out.add_dim();
-        if (c.ValueKnown(d)) {
-          out_dim->set_size(c.Value(d));
-        } else {
-          out_dim->set_size(-1);
-        }
-      }
-    } else {
-      out.set_unknown_rank(true);
-    }
+    ProtoFromShapeHandle(c.output(i), &c, out.mutable_shape());
+    ProtoFromShapeHandle(c.output_handle_shape(i), &c,
+                         out.mutable_handle_shape());
+    out.set_handle_dtype(c.output_handle_dtype(i));
     CHECK(out.AppendToString(&(*output_tensor_shape_protos)[i]));
   }
 
diff --git a/tensorflow/python/framework/cpp_shape_inference.h b/tensorflow/python/framework/cpp_shape_inference.h
index a2f52227d6..f91af8e1a8 100644
--- a/tensorflow/python/framework/cpp_shape_inference.h
+++ b/tensorflow/python/framework/cpp_shape_inference.h
@@ -36,7 +36,7 @@ namespace swig {
 // inference was successful.
 //
 // On success, <*output_shapes> is populated with the inferred output shapes (as
-// serialized TensorShapeProtos).
+// serialized CppShapeInferenceResult protos).
 // <*output_shapes> must be empty when this function is called.
 //
 // This is temporary code to be used during the migration
diff --git a/tensorflow/python/framework/cpp_shape_inference.proto b/tensorflow/python/framework/cpp_shape_inference.proto
new file mode 100644
index 0000000000..c7d59cc55e
--- /dev/null
+++ b/tensorflow/python/framework/cpp_shape_inference.proto
@@ -0,0 +1,13 @@
+syntax = "proto3";
+
+package tensorflow;
+option cc_enable_arenas = true;
+
+import "tensorflow/core/framework/types.proto";
+import "tensorflow/core/framework/tensor_shape.proto";
+
+message CppShapeInferenceResult {
+  TensorShapeProto shape = 1;
+  TensorShapeProto handle_shape = 2;
+  DataType handle_dtype = 3;
+}
\ No newline at end of file
diff --git a/tensorflow/python/framework/ops.py b/tensorflow/python/framework/ops.py
index 6d80da1300..be9de08ba3 100644
--- a/tensorflow/python/framework/ops.py
+++ b/tensorflow/python/framework/ops.py
@@ -32,6 +32,8 @@ from tensorflow.core.framework import attr_value_pb2
 from tensorflow.core.framework import function_pb2
 from tensorflow.core.framework import graph_pb2
 from tensorflow.core.framework import node_def_pb2
+from tensorflow.core.framework import tensor_shape_pb2
+from tensorflow.core.framework import types_pb2
 from tensorflow.core.framework import versions_pb2
 from tensorflow.python.framework import device as pydev
 from tensorflow.python.framework import dtypes
@@ -297,6 +299,10 @@ class Tensor(object):
     # to easily navigate a computation graph.
     self._consumers = []
 
+    # Attributes used for C++ shape inference. Not inspected, only forwarded.
+    self._handle_shape = tensor_shape_pb2.TensorShapeProto()
+    self._handle_dtype = types_pb2.DT_INVALID
+
   @property
   def op(self):
     """The `Operation` that produces this tensor as an output."""
@@ -1791,10 +1797,22 @@ def set_shapes_for_outputs(op):
   if shapes is None:
     raise RuntimeError(
         "Shape function for op %s did not return any shapes" % op)
+  elif isinstance(shapes, dict):
+    # Returned by call_cpp_shape_fn
+    shapes_dict = shapes
+    shapes = shapes_dict["shapes"]
+    handle_shapes = shapes_dict["handle_shapes"]
+    handle_dtypes = shapes_dict["handle_dtypes"]
+    for output, handle_shape, handle_dtype in zip(op.outputs, handle_shapes, handle_dtypes):
+      # pylint: disable=protected-access
+      output._handle_shape = handle_shape
+      output._handle_dtype = handle_dtype
+      # pylint: enable=protected-access
+
   if len(op.outputs) != len(shapes):
     raise RuntimeError(
-        "Shape function for op %s returned %d shapes but expected %d" %
-        (op, len(shapes), len(op.outputs)))
+        "Shape function for op %s returned %d shapes but expected %d %s %s" %
+        (op, len(shapes), len(op.outputs), shape_func.__name__, str(shapes)))
   for output, s in zip(op.outputs, shapes):
     output.set_shape(s)
 
diff --git a/tensorflow/python/kernel_tests/BUILD b/tensorflow/python/kernel_tests/BUILD
index baa48ec8a4..fe74b3426c 100644
--- a/tensorflow/python/kernel_tests/BUILD
+++ b/tensorflow/python/kernel_tests/BUILD
@@ -256,6 +256,16 @@ tf_py_test(
 )
 
 tf_py_test(
+    name = "resource_variable_ops_test",
+    size = "small",
+    srcs = ["resource_variable_ops_test.py"],
+    additional_deps = [
+        "//tensorflow:tensorflow_py",
+        "//tensorflow/python:resource_variable_ops",
+    ],
+)
+
+tf_py_test(
     name = "save_restore_ops_test",
     size = "small",
     srcs = ["save_restore_ops_test.py"],
diff --git a/tensorflow/python/kernel_tests/resource_variable_ops_test.py b/tensorflow/python/kernel_tests/resource_variable_ops_test.py
new file mode 100644
index 0000000000..cb4375ce91
--- /dev/null
+++ b/tensorflow/python/kernel_tests/resource_variable_ops_test.py
@@ -0,0 +1,51 @@
+# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Tests for tensorflow.ops.resource_variable_ops."""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
+from tensorflow.python.ops import array_ops
+from tensorflow.python.ops import resource_variable_ops
+from tensorflow.python.platform import test
+
+
+class ResourceVariableOpsTest(test_util.TensorFlowTestCase):
+
+  def testHandleDtypeShapeMatch(self):
+    with self.test_session():
+      handle = resource_variable_ops.var_handle_op(dtype=dtypes.int32, shape=[])
+      with self.assertRaises(ValueError):
+        resource_variable_ops.create_variable_op(
+            handle, constant_op.constant(0.0, dtype=dtypes.float32)).run()
+      with self.assertRaises(ValueError):
+        resource_variable_ops.create_variable_op(
+            handle, constant_op.constant([0], dtype=dtypes.int32)).run()
+      resource_variable_ops.create_variable_op(
+          handle, constant_op.constant(0, dtype=dtypes.int32)).run()
+
+  def testDtypeSurvivesIdentity(self):
+    with self.test_session():
+      handle = resource_variable_ops.var_handle_op(dtype=dtypes.int32, shape=[])
+      id_handle = array_ops.identity(handle)
+      resource_variable_ops.create_variable_op(
+          id_handle, constant_op.constant(0, dtype=dtypes.int32)).run()
+
+
+if __name__ == "__main__":
+  test.main()
diff --git a/tensorflow/python/ops/resource_variable_ops.py b/tensorflow/python/ops/resource_variable_ops.py
new file mode 100644
index 0000000000..7db9731e19
--- /dev/null
+++ b/tensorflow/python/ops/resource_variable_ops.py
@@ -0,0 +1,30 @@
+# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Ops to use variables as resources."""
+
+# pylint: disable=g-bad-name
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from tensorflow.python.framework import common_shapes
+from tensorflow.python.framework import ops
+# go/tf-wildcard-import
+# pylint: disable=wildcard-import
+from tensorflow.python.ops.gen_resource_variable_ops import *
+# pylint: enable=wildcard-import
+
+ops.RegisterShape("VarHandleOp")(common_shapes.call_cpp_shape_fn)
+ops.RegisterShape("CreateVariableOp")(common_shapes.call_cpp_shape_fn)