bool GetNodeDef(TF_Operation* oper, tensorflow::NodeDef* node_def);

bool GetFunctionDef(TF_Function* func, tensorflow::FunctionDef* func_def);

bool GetAttrValue(TF_Operation* oper, const char* attr_name,
                  tensorflow::AttrValue* attr_value, TF_Status* s);

// Returns a sorted vector of std::pair<function_name, gradient_func> from
// graph_def.library().gradient()

TF_CAPI_EXPORT extern void TF_AttrBuilderSetType(TF_AttrBuilder* builder,
                                                 const char* attr_name,
                                                 TF_DataType value);
TF_CAPI_EXPORT extern void TF_AttrBuilderSetTypeList(TF_AttrBuilder* builder,
                                                     const char* attr_name,
                                                     const TF_DataType* values,

  TF_DeleteBuffer(buffer);
  TF_DeleteStatus(s);
  return ret;
}

bool GetAttrValue(TF_Operation* oper, const char* attr_name,
                  tensorflow::AttrValue* attr_value, TF_Status* s) {
  TF_Buffer* buffer = TF_NewBuffer();
  TF_OperationGetAttrValueProto(oper, attr_name, buffer, s);
  bool ret = TF_GetCode(s) == TF_OK;
  if (ret) ret = attr_value->ParseFromArray(buffer->data, buffer->length);

    func_ = TF_FunctionImportFunctionDef(buf.data(), buf.size(), s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  }

  void GetAttr(const char* attr_name, AttrValue* out_attr) {
    TF_Buffer* attr_buf = TF_NewBuffer();
    TF_FunctionGetAttrValueProto(func_, attr_name, attr_buf, s_);
    ASSERT_TRUE(out_attr->ParseFromArray(attr_buf->data, attr_buf->length));
    TF_DeleteBuffer(attr_buf);
  }

//
// Analogous to TF_SetAttrValueProto for building graph operations.
TF_CAPI_EXPORT extern void TFE_OpSetAttrValueProto(const TFE_Op* op,
                                                   const char* attr_name,
                                                   const void* proto,
                                                   size_t proto_len,
                                                   TF_Status* status);

pkg debug/dwarf, const AttrLocation Attr
pkg debug/dwarf, const AttrLowerBound Attr
pkg debug/dwarf, const AttrLowpc Attr
pkg debug/dwarf, const AttrMacroInfo Attr
pkg debug/dwarf, const AttrName Attr
pkg debug/dwarf, const AttrNamelistItem Attr
pkg debug/dwarf, const AttrOrdering Attr
pkg debug/dwarf, const AttrPriority Attr
pkg debug/dwarf, const AttrProducer Attr
pkg debug/dwarf, const AttrPrototyped Attr

// That will require setting up the tensorflow build with gmock.
#define EXPECT_TF_META(attr_name, expected_list_size, expected_type, \
                       expected_total_size)                          \
  do {                                                               \
    auto m = TF_OperationGetAttrMetadata(oper, attr_name, s_);       \
    EXPECT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);              \

pkg debug/dwarf, const AttrLocation = 2
pkg debug/dwarf, const AttrLowerBound = 34
pkg debug/dwarf, const AttrLowpc = 17
pkg debug/dwarf, const AttrMacroInfo = 67
pkg debug/dwarf, const AttrName = 3
pkg debug/dwarf, const AttrNamelistItem = 68
pkg debug/dwarf, const AttrOrdering = 9
pkg debug/dwarf, const AttrPriority = 69
pkg debug/dwarf, const AttrProducer = 37
pkg debug/dwarf, const AttrPrototyped = 39

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