return new Failure(t);
    }
  }

  /**
   * An inlined private copy of {@link Uninterruptibles#getUninterruptibly} used to break an
   * internal dependency on other /util/concurrent classes.
   */
  @ParametricNullness
  private static <V extends @Nullable Object> V getUninterruptibly(Future<V> future)
      throws ExecutionException {
    boolean interrupted = false;

# build is static and TensorFlow symbols (in Python only) are loaded into the
# global symbol table in order to support op registration. This means that
# projects building with Bazel and importing TensorFlow as a dependency will not
# depend on libtensorflow_framework.so unless they opt in.
tf_cc_shared_library(
    name = "tensorflow_framework",
    additional_linker_inputs = [
        "//tensorflow:tf_framework_version_script.lds",

TF_CAPI_EXPORT extern void TF_ImportGraphDefOptionsRemapControlDependency(
    TF_ImportGraphDefOptions* opts, const char* src_name, TF_Operation* dst);

// Cause the imported graph to have a control dependency on `oper`. `oper`
// should exist in the graph being imported into.
TF_CAPI_EXPORT extern void TF_ImportGraphDefOptionsAddControlDependency(
    TF_ImportGraphDefOptions* opts, TF_Operation* oper);

  TF_DeleteBuffer(graph_def);
  graph_def = TF_NewBuffer();
  TF_GraphToGraphDef(graph, graph_def, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Import again, with remapped control dependency, into the same graph
  TF_DeleteImportGraphDefOptions(opts);
  opts = TF_NewImportGraphDefOptions();
  TF_ImportGraphDefOptionsSetPrefix(opts, "imported4");

func (c *typeConv) Type(dtype dwarf.Type, pos token.Pos) *Type {
	return c.loadType(dtype, pos, "")
}

// loadType recursively loads the requested dtype and its dependency graph.
func (c *typeConv) loadType(dtype dwarf.Type, pos token.Pos, parent string) *Type {
	// Always recompute bad pointer typedefs, as the set of such
	// typedefs changes as we see more types.
	checkCache := true

# Config to use a mostly-static build and disable modular op registration
# support (this will revert to loading TensorFlow with RTLD_GLOBAL in Python).
# By default, TensorFlow will build with a dependence on
# //tensorflow:libtensorflow_framework.so.
build:monolithic --define framework_shared_object=false
build:monolithic --define tsl_protobuf_header_only=false