namespace tensorflow {
namespace tracing {
namespace graph {
GraphFunction::GraphFunction(FunctionDef fdef)
    : AbstractFunction(kGraph),
      func_record_(new FunctionRecord(std::move(fdef), {}, true)) {}
GraphFunction::~GraphFunction() {}
Status GraphFunction::GetFunctionDef(const FunctionDef **fdef) {
  *fdef = &(func_record_->fdef());
  return absl::OkStatus();
}
}  // namespace graph
}  // namespace tracing

  // Adding a non-existent remote worker to cluster def. This should cause the
  // UpdateServerDef call to fail.
  tensorflow::ClusterDef* cluster_def = server_def.mutable_cluster();
  tensorflow::JobDef* job_def = cluster_def->mutable_job(0);
  int port = tensorflow::testing::PickUnusedPortOrDie();
  job_def->mutable_tasks()->insert(
      {2, tensorflow::strings::StrCat("localhost:", port)});
  server_def.set_task_index(0);

class UserInputError(Exception):
  pass


def is_windows():
  return platform.system() == 'Windows'


def is_linux():
  return platform.system() == 'Linux'


def is_macos():
  return platform.system() == 'Darwin'


def is_ppc64le():
  return platform.machine() == 'ppc64le'


def is_s390x():
  return platform.machine() == 's390x'


def is_cygwin():

void TestRemoteExecute(bool async) {
  tensorflow::ServerDef server_def = GetServerDef(2);

  // This server def has the task index set to 0.
  string serialized = server_def.SerializeAsString();

  server_def.set_task_index(1);

  std::unique_ptr<tensorflow::GrpcServer> worker_server;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(
                  server_def, tensorflow::Env::Default(), &worker_server)
                  .ok());

import pkg_resources

logging.basicConfig(level=logging.INFO)


class ImportApiPackagesTest(unittest.TestCase):
  """ImportApiPackagesTest class. See description at the top of the file."""

  def setUp(self):
    def _get_api_packages_v2():
      api_packages_path = pkg_resources.resource_filename(
          "tensorflow", "_api/v2/api_packages.txt"
      )

      logging.info("Load api packages file: %s", api_packages_path)

    grad_inputs[0] = grad_outputs[0];
    if (grad_inputs[0]) {
      grad_inputs[0]->Ref();
    }
    return absl::OkStatus();
  }
};

// Computes:
//
// @tf.custom_gradient
// def f(input):
//   def grad(grads):
//     return grads[0]
//   return tf.exp(input), grad
// outputs = [f(inputs[0])]
Status ExpWithPassThroughGrad(AbstractContext* ctx,

+    char ut_host[UT_HOSTSIZE]
+      __attribute_nonstring__;	/* Hostname for remote login.  */
     long int ut_time;
   };
 
diff --git a/misc/sys/cdefs.h b/misc/sys/cdefs.h
index 30482a1..551d5fd 100644
--- a/misc/sys/cdefs.h
+++ b/misc/sys/cdefs.h
@@ -391,6 +391,15 @@
 
 #include <bits/wordsize.h>
 
+#if __GNUC_PREREQ (8, 0)
+/* Describes a char array whose address can safely be passed as the first

      // Name
      "AssertAndCollective",
      // Args
      {"x: float", "condition: bool"},
      // Return values
      {"y: float"},
      // Attr def
      {},
      // Nodes
      {
          {{"assert"},
           "Assert",
           {"condition", "x"},
           {{"T", std::vector<DataType>{DT_FLOAT}}}},
          {{"y"},

// overhead and copies.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_NewTensorHandleFromScalar(
    TF_DataType data_type, void* data, size_t len, TF_Status* status);

// Specify the server_def that enables collective ops.
// This is different to the above function in that it doesn't create remote
// contexts, and remotely executing ops is not possible. It just enables
// communication for collective ops.

  tensorflow::GradientDef gdef;
  gdef.set_function_name(func->record->fdef().signature().name());
  gdef.set_gradient_func(grad->record->fdef().signature().name());
  status->status = g->graph.AddGradientDef(std::move(gdef));
}

int TF_GraphNumFunctions(TF_Graph* g) {
  tensorflow::mutex_lock l(g->mu);
  return g->graph.flib_def().num_functions();
}

int TF_GraphGetFunctions(TF_Graph* g, TF_Function** funcs, int max_func,