TF_ASSERT_OK(OpRegistry::Global()->LookUpOpDef("Add", &expected_op_def));
  string expected_serialized;
  expected_op_def->SerializeToString(&expected_serialized);
  string actual_string(reinterpret_cast<const char*>(buffer->data),
                       buffer->length);
  EXPECT_EQ(expected_serialized, actual_string);

  TF_GraphGetOpDef(graph, "MyFakeOp", buffer, status);

*   Fixes a null-dereference when specializing tensor type
    ([CVE-2022-23570](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-23570))
*   Fixes a crash when type cannot be specialized
    ([CVE-2022-23572](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-23572))
*   Fixes a heap OOB read/write in `SpecializeType`
    ([CVE-2022-23574](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-23574))

  }
  return nullptr;
}

void TFE_ContextAddFunctionDef(TFE_Context* ctx,
                               const char* serialized_function_def, size_t size,
                               TF_Status* status) {
  tensorflow::FunctionDef function_def;
  if (!function_def.ParseFromArray(serialized_function_def, size)) {
    status->status =
        tensorflow::errors::InvalidArgument("Invalid FunctionDef proto");
    return;
  }

#include "tensorflow/core/platform/refcount.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

class FunctionRecord;

// A traced function: this hides the complexity of converting the serialized
// representation between various supported formats e.g. FunctionDef and Mlir
// function.
class AbstractFunction : public core::RefCounted {
 protected:
  enum AbstractFunctionKind { kGraph, kMlir };