Qualify uses of std::string.

PiperOrigin-RevId: 302910208
Change-Id: If59968d915f4b4e87f21fa34c05ee87299b75a58

tensorflow/cc/saved_model/loader.h

@@ -124,7 +124,7 @@ Status LoadSavedModel(const SessionOptions& session_options,
 /// the export directory definitely does not contain a SavedModel. If the method
 /// returns `true`, the export directory may contain a SavedModel but provides
 /// no guarantee that it can be loaded.
-bool MaybeSavedModelDirectory(const string& export_dir);
+bool MaybeSavedModelDirectory(const std::string& export_dir);
 
 }  // namespace tensorflow
 

tensorflow/core/framework/allocator.h

@@ -114,7 +114,7 @@ struct AllocatorStats {
         bytes_reserved(0),
         peak_bytes_reserved(0) {}
 
-  string DebugString() const;
+  std::string DebugString() const;
 };
 
 // Allocator is an abstract interface for allocating and deallocating
@@ -127,7 +127,7 @@ class Allocator {
   virtual ~Allocator();
 
   // Return a string identifying this allocator
-  virtual string Name() = 0;
+  virtual std::string Name() = 0;
 
   // Return an uninitialized block of memory that is "num_bytes" bytes
   // in size.  The returned pointer is guaranteed to be aligned to a
@@ -242,7 +242,7 @@ class AllocatorWrapper : public Allocator {
   // Returns the wrapped allocator to which all calls are delegated.
   Allocator* wrapped() const { return wrapped_; }
 
-  string Name() override { return wrapped_->Name(); }
+  std::string Name() override { return wrapped_->Name(); }
 
   void* AllocateRaw(size_t alignment, size_t num_bytes) override {
     return wrapped_->AllocateRaw(alignment, num_bytes);
@@ -336,7 +336,7 @@ struct AllocatorAttributes {
   int32 scope_id = 0;
 
   // Returns a human readable representation of this.
-  string DebugString() const;
+  std::string DebugString() const;
 };
 
 // Returns a trivial implementation of Allocator, which is a process singleton.

tensorflow/core/framework/resource_handle.h

@@ -38,23 +38,23 @@ class ResourceHandle {
   ~ResourceHandle();
 
   // Unique name for the device containing the resource.
-  const string& device() const { return device_; }
+  const std::string& device() const { return device_; }
   // Names of the devices containing the resource.
   const std::vector<string>& allowed_devices() const {
     return allowed_devices_;
   }
-  void set_device(const string& device) { device_ = device; }
+  void set_device(const std::string& device) { device_ = device; }
   void set_allowed_devices(const std::vector<string>& devices) {
     allowed_devices_ = devices;
   }
 
   // Container in which this resource is placed.
-  const string& container() const { return container_; }
-  void set_container(const string& container) { container_ = container; }
+  const std::string& container() const { return container_; }
+  void set_container(const std::string& container) { container_ = container; }
 
   // Unique name of this resource.
-  const string& name() const { return name_; }
-  void set_name(const string& name) { name_ = name; }
+  const std::string& name() const { return name_; }
+  void set_name(const std::string& name) { name_ = name; }
 
   // Hash code for the type of the resource. Is only valid in the same device
   // and in the same execution.
@@ -63,8 +63,10 @@ class ResourceHandle {
 
   // For debug-only, the name of the type pointed to by this handle, if
   // available.
-  const string& maybe_type_name() const { return maybe_type_name_; }
-  void set_maybe_type_name(const string& value) { maybe_type_name_ = value; }
+  const std::string& maybe_type_name() const { return maybe_type_name_; }
+  void set_maybe_type_name(const std::string& value) {
+    maybe_type_name_ = value;
+  }
 
   // Data types and shapes for the underlying resource.
   std::vector<DtypeAndPartialTensorShape> dtypes_and_shapes() const {
@@ -80,10 +82,10 @@ class ResourceHandle {
   void FromProto(const ResourceHandleProto& proto);
 
   // Serialization via ResourceHandleProto
-  string SerializeAsString() const;
-  bool ParseFromString(const string& s);
+  std::string SerializeAsString() const;
+  bool ParseFromString(const std::string& s);
 
-  string DebugString() const;
+  std::string DebugString() const;
 
   // GUID for anonymous resources. Resources with this shared_name will have
   // their shared_name replaced with a GUID at creation time
@@ -93,19 +95,19 @@ class ResourceHandle {
  public:
   // The default device containing the resource, where the ResourceHandle is
   // initially created.
-  string device_;
+  std::string device_;
   // A set of devices containing the resource. If empty, the resource only
   // exists on device_. Can be represented in wildcard patterns.
   std::vector<string> allowed_devices_;
-  string container_;
-  string name_;
+  std::string container_;
+  std::string name_;
   uint64 hash_code_ = 0;
-  string maybe_type_name_;
+  std::string maybe_type_name_;
   std::vector<DtypeAndPartialTensorShape> dtypes_and_shapes_;
 };
 
 // For backwards compatibility for when this was a proto
-string ProtoDebugString(const ResourceHandle& handle);
+std::string ProtoDebugString(const ResourceHandle& handle);
 
 // Encodes a list of ResourceHandle protos in the given StringListEncoder.
 void EncodeResourceHandleList(const ResourceHandle* p, int64 n,

tensorflow/core/framework/shape_inference_testutil.h

@@ -86,11 +86,11 @@ class ShapeInferenceTestutil {
               .error_message())
 #define INFER_ERROR(error_substring, op, i)                                 \
   {                                                                         \
-    string error_message =                                                  \
+    std::string error_message =                                             \
         ::tensorflow::shape_inference::ShapeInferenceTestutil::InferShapes( \
             op, i, "e")                                                     \
             .error_message();                                               \
-    const string& substring = error_substring;                              \
+    const std::string& substring = error_substring;                         \
     EXPECT_NE("", error_message);                                           \
     EXPECT_TRUE(absl::StrContains(error_message, substring))                \
         << "Expected to see '" << substring << "' in '" << error_message    \

tensorflow/core/framework/tensor.h

@@ -571,19 +571,19 @@ class Tensor {
       int64 begin) const;
 
   /// Render the first `max_entries` values in `*this` into a string.
-  string SummarizeValue(int64 max_entries, bool print_v2 = false) const;
+  std::string SummarizeValue(int64 max_entries, bool print_v2 = false) const;
 
   /// A human-readable summary of the tensor suitable for debugging.
   // `num_values` is the number of actual data values in the tensor
   // included in the message. If the tensor might be resident in
   // GPU/TPU memory use DeviceSafeDebugString instead.
-  string DebugString(int num_values) const;
-  string DebugString() const { return DebugString(3); }
+  std::string DebugString(int num_values) const;
+  std::string DebugString() const { return DebugString(3); }
 
   // Variant of DebugString() that should be used for possibly non-CPU tensors.
   // If the tensor is not resident on CPU, we can't read its values as
   // DebugString() does.
-  string DeviceSafeDebugString() const;
+  std::string DeviceSafeDebugString() const;
 
   /// Fill in the `TensorDescription` proto with metadata about the
   /// tensor that is useful for monitoring and debugging.

tensorflow/core/framework/tensor_shape.h

@@ -69,8 +69,8 @@ class TensorShapeRep {
   int64 num_elements() const { return num_elements_; }
 
   /// For error messages.
-  string DebugString() const;
-  static string DebugString(const TensorShapeProto& proto);
+  std::string DebugString() const;
+  static std::string DebugString(const TensorShapeProto& proto);
 
   void DumpRep() const;  // XXX
 
@@ -397,7 +397,8 @@ class TensorShapeUtils {
   static Status MakeShape(gtl::ArraySlice<int64> shape,
                           PartialTensorShape* out);
 
-  static string ShapeListString(const gtl::ArraySlice<TensorShape>& shapes);
+  static std::string ShapeListString(
+      const gtl::ArraySlice<TensorShape>& shapes);
 
   /// \brief Returns true iff `shape` starts with `prefix`.
   static bool StartsWith(const TensorShape& shape, const TensorShape& prefix);
@@ -462,7 +463,7 @@ class PartialTensorShape : public TensorShapeBase<PartialTensorShape> {
 /// common predicates on a partially known tensor shape.
 class PartialTensorShapeUtils {
  public:
-  static string PartialShapeListString(
+  static std::string PartialShapeListString(
       const gtl::ArraySlice<PartialTensorShape>& shapes);
 
   static bool AreIdentical(const gtl::ArraySlice<PartialTensorShape>& shapes0,

tensorflow/core/framework/types.h

@@ -59,14 +59,14 @@ class DeviceType {
   explicit DeviceType(StringPiece type) : type_(type.data(), type.size()) {}
 
   const char* type() const { return type_.c_str(); }
-  const string& type_string() const { return type_; }
+  const std::string& type_string() const { return type_; }
 
   bool operator<(const DeviceType& other) const;
   bool operator==(const DeviceType& other) const;
   bool operator!=(const DeviceType& other) const { return !(*this == other); }
 
  private:
-  string type_;
+  std::string type_;
 };
 std::ostream& operator<<(std::ostream& os, const DeviceType& d);
 
@@ -110,10 +110,10 @@ typedef gtl::InlinedVector<std::pair<DeviceType, int32>, 4>
     PrioritizedDeviceTypeVector;
 
 // Convert the enums to strings for errors:
-string DataTypeString(DataType dtype);
-string DeviceTypeString(const DeviceType& device_type);
-string DataTypeSliceString(const DataTypeSlice dtypes);
-inline string DataTypeVectorString(const DataTypeVector& dtypes) {
+std::string DataTypeString(DataType dtype);
+std::string DeviceTypeString(const DeviceType& device_type);
+std::string DataTypeSliceString(const DataTypeSlice dtypes);
+inline std::string DataTypeVectorString(const DataTypeVector& dtypes) {
   return DataTypeSliceString(dtypes);
 }
 

tensorflow/core/graph/default_device.h

@@ -26,7 +26,7 @@ namespace graph {
 
 // Sets the default device for all nodes in graph_def to "device",
 // only if not already set.
-inline void SetDefaultDevice(const string& device, GraphDef* graph_def) {
+inline void SetDefaultDevice(const std::string& device, GraphDef* graph_def) {
   for (int i = 0; i < graph_def->node_size(); ++i) {
     auto node = graph_def->mutable_node(i);
     if (node->device().empty()) {

tensorflow/core/public/session_options.h

@@ -52,7 +52,7 @@ struct SessionOptions {
   ///
   /// If the session disconnects from the remote process during its
   /// lifetime, session calls may fail immediately.
-  string target;
+  std::string target;
 
   /// Configuration options.
   ConfigProto config;

tensorflow/stream_executor/host/host_gpu_executor.h

@@ -157,7 +157,7 @@ class HostExecutor : public internal::StreamExecutorInterface {
   }
 
   port::Status SetDeviceSharedMemoryConfig(SharedMemoryConfig config) override {
-    string error_msg{
+    std::string error_msg{
         "Shared memory configuration is unsupported for host "
         "executors."};
     LOG(INFO) << error_msg;

tensorflow/stream_executor/host/host_platform.cc

@@ -38,7 +38,7 @@ int HostPlatform::VisibleDeviceCount() const {
   return std::thread::hardware_concurrency();
 }
 
-const string& HostPlatform::Name() const { return name_; }
+const std::string& HostPlatform::Name() const { return name_; }
 
 port::StatusOr<std::unique_ptr<DeviceDescription>>
 HostPlatform::DescriptionForDevice(int ordinal) const {

tensorflow/stream_executor/host/host_platform.h

@@ -49,7 +49,7 @@ class HostPlatform : public Platform {
   // base::NumCPUs().
   int VisibleDeviceCount() const override;
 
-  const string& Name() const override;
+  const std::string& Name() const override;
 
   port::StatusOr<std::unique_ptr<DeviceDescription>> DescriptionForDevice(
       int ordinal) const override;
@@ -71,7 +71,7 @@ class HostPlatform : public Platform {
 
  private:
   // This platform's name.
-  string name_;
+  std::string name_;
 
   // Cache of created StreamExecutors.
   ExecutorCache executor_cache_;