ASSERT_TRUE(GetGraphDef(graph, &graph_def));

  // Validate GraphDef is what we expect.
  bool found_placeholder = false;
  bool found_scalar_const = false;
  bool found_add = false;
  for (const auto& n : graph_def.node()) {
    if (IsPlaceholder(n)) {
      EXPECT_FALSE(found_placeholder);
      found_placeholder = true;
    } else if (IsScalarConst(n, 3)) {
      EXPECT_FALSE(found_scalar_const);

    return (Collector) TO_OPTIONAL;
  }

  private static final Object NULL_PLACEHOLDER = new Object();

  private static final Collector<@Nullable Object, ?, @Nullable Object> ONLY_ELEMENT =
      Collector.<@Nullable Object, ToOptionalState, @Nullable Object>of(
          ToOptionalState::new,
          (state, o) -> state.add((o == null) ? NULL_PLACEHOLDER : o),
          ToOptionalState::combine,
          state -> {

    return;
  }

  TF_Operation* placeholder_op = TF_GraphOperationByName(
      session->graph,
      tensorflow::strings::StrCat("arg_tensor_enqueue_", tensor_id).c_str());
  if (placeholder_op == nullptr) {
    status->status = tensorflow::errors::Internal(
        "Unable to find the placeholder node as input to enqueue in the TF "
        "graph.");
    return;
  }

    // In order for the weak hash map to work correctly, we must not hold any reference to
    // the model used as the key.  So we use a dummy model as a placeholder to indicate that
    // we want to store the model used as they key.
    private static final Model KEY = Model.newInstance();

    private final ProfileModelMerger merger = new ProfileModelMerger();

    @Override

   *     message is formed by replacing each {@code %s} placeholder in the template with an
   *     argument. These are matched by position - the first {@code %s} gets {@code
   *     errorMessageArgs[0]}, etc. Unmatched arguments will be appended to the formatted message in
   *     square braces. Unmatched placeholders will be left as-is.

}

void TF_SetAttrPlaceholder(TF_OperationDescription* desc, const char* attr_name,
                           const char* placeholder) {
  tensorflow::AttrValue attr_value;
  attr_value.set_placeholder(placeholder);
  desc->node_builder.Attr(attr_name, attr_value);
}

void TF_SetAttrFuncName(TF_OperationDescription* desc, const char* attr_name,

  tensorflow::FunctionDef fdef;
  status->status = tensorflow::GraphToFunctionDef(
      fn_body->graph, fn_name, append_hash_to_fn_name != 0,
      /*set_stateful_from_nodes=*/true,
      /*copy_placeholder_attrs_from_nodes=*/true, body_nodes, input_tensors,
      output_tensors, output_names_vec, control_output_nodes,
      control_output_names_vec, description, &fdef);
  if (TF_GetCode(status) != TF_OK) {
    return nullptr;

              --input $(location :tensorflow_def_file) \\
              --output $@
          """,
        "//conditions:default": "touch $@",  # Just a placeholder for Unix platforms
    }),
    tools = ["@local_config_def_file_filter//:def_file_filter"],
    visibility = ["//visibility:public"],
)

				if i > 0 {
					buf.WriteString(", ")
				}
				w.writeType(buf, targs.At(i))
			}
			buf.WriteByte(']')
		}

	case *types.TypeParam:
		// Type parameter names may change, so use a placeholder instead.
		fmt.Fprintf(buf, "$%d", typ.Index())

	default:
		panic(fmt.Sprintf("unknown type %T", typ))
	}
}

func (w *Walker) writeSignature(buf *bytes.Buffer, sig *types.Signature) {

    *   `tf.types.experimental.TraceType` now requires an additional `placeholder_value` method to be defined.
    *   `tf.function` now traces with placeholder values generated by TraceType instead of the value itself.