// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package disk

import (
	"os"
)

// Fdatasync is a no-op
func Fdatasync(f *os.File) error {
	return nil
}

// FadviseDontNeed is a no-op
func FadviseDontNeed(f *os.File) error {
	return nil

[gradle_verification]: https://docs.gradle.org/current/userguide/dependency_verification.html#sec:signature-verification

/**
 * Utility {@link RemovalListener} implementations intended for use in testing.
 *
 * @author mike nonemacher
 */
@GwtCompatible
@NullUnmarked
final class TestingRemovalListeners {

  /** Returns a new no-op {@code RemovalListener}. */
  static <K, V> NullRemovalListener<K, V> nullRemovalListener() {
    return new NullRemovalListener<>();
  }

  /** Type-inferring factory method for creating a {@link QueuingRemovalListener}. */

                                        const char* device);

// The calls to TF_AddInput and TF_AddInputList must match (in number,
// order, and type) the op declaration.  For example, the "Concat" op
// has registration:
//   REGISTER_OP("Concat")
//       .Input("concat_dim: int32")
//       .Input("values: N * T")
//       .Output("output: T")
//       .Attr("N: int >= 2")

		[case(200)] DfsEnumArray200 *info200;
		[case(300)] DfsEnumArray300 *info300;
	} DfsEnumInfo;

	typedef struct {
		uint32_t level,
		[switch_is(level)] DfsEnumInfo e;
	} DfsEnumStruct;

	[op(0x15)]
	int NetrDfsEnumEx([in,string,unique] wchar_t dfs_name,
			[in] uint32_t level,
			[in] uint32_t prefmaxlen,
			[in,out,unique] DfsEnumStruct *info,
			[in,out,unique] uint32_t *totalentries);

    TF_DeleteStatus(status);
    ASSERT_EQ(TF_OK, code) << status_msg;

    // Test op list.
    TF_Buffer op_list_buf = TF_GetOpList(lib);
    tensorflow::OpList op_list;
    EXPECT_TRUE(op_list.ParseFromArray(op_list_buf.data, op_list_buf.length));
    ASSERT_EQ(op_list.op_size(), 1);
    EXPECT_EQ("TestCApi1", op_list.op(0).name());
    TF_DeleteLibraryHandle(lib);
  }
#endif  // !defined(TENSORFLOW_NO_SHARED_OBJECTS)

  public void testOrdering() {
    List<Integer> callOrder = new ArrayList<>();

    class FakeOp implements Runnable {
      final int op;

      FakeOp(int op) {
        this.op = op;
      }

      @Override
      public void run() {
        callOrder.add(op);
      }
    }

    e.execute(new FakeOp(0));
    e.execute(new FakeOp(1));
    e.execute(new FakeOp(2));
    fakePool.runAll();

	case syscall.O_RDWR:
		fallthrough
	case syscall.O_WRONLY | syscall.O_CREAT:
		fallthrough
	case syscall.O_RDWR | syscall.O_CREAT:
		lockType |= syscall.LOCK_EX
	default:
		return nil, &os.PathError{
			Op:   "open",
			Path: path,
			Err:  syscall.EINVAL,
		}
	}

	f, err := os.OpenFile(path, flag|syscall.O_SYNC, perm)
	if err != nil {
		return nil, err
	}

	}

	var message message
	_, _, err = message.parse(msg)
	if err != nil {
		writeErr(fmt.Errorf("error parsing grid connect: %w", err))
		return
	}
	if message.Op != OpConnect {
		writeErr(fmt.Errorf("unexpected connect op: %v", message.Op))
		return
	}
	var cReq connectReq
	_, err = cReq.UnmarshalMsg(message.Payload)
	if err != nil {
		writeErr(fmt.Errorf("error parsing connectReq: %w", err))
		return

  }

  mutex_lock l(graph->mu);
  op->node.AddAttr(attr_name, attr_val);
  RecordMutation(graph, *op, "setting attribute");
}

void TF_ClearAttr(TF_Graph* graph, TF_Operation* op, const char* attr_name,
                  TF_Status* status) {
  using tensorflow::RecordMutation;
  mutex_lock l(graph->mu);
  op->node.ClearAttr(attr_name);
  RecordMutation(graph, *op, "clearing attribute");
}