tf_executor.fetch %outputs_2#1, %outputs_4#1, %outputs_6#1 : tensor<5xf32>, tensor<5xf32>, tensor<5xf32>
  }
  func.return %0#0, %0#1, %0#2 : tensor<5xf32>, tensor<5xf32>, tensor<5xf32>
}

func.func @cond(%arg0: tensor<*xi32>, %arg1: tensor<*xf32>) -> tensor<i1> {
  %0 = tf_executor.graph {

00000030  13 00 23 00 00 ff 01 00  01 00 00 17 00 00 00 0b  |..#.............|
00000040  00 02 01 00 16 03 03 02  59 0b 00 02 55 00 02 52  |........Y...U..R|
00000050  00 02 4f 30 82 02 4b 30  82 01 b4 a0 03 02 01 02  |..O0..K0........|
00000060  02 09 00 e8 f0 9d 3f e2  5b ea a6 30 0d 06 09 2a  |......?.[..0...*|
00000070  86 48 86 f7 0d 01 01 0b  05 00 30 1f 31 0b 30 09  |.H........0.1.0.|

/**
 * Unit tests for {@link SipHashFunction}.
 *
 * @author Kurt Alfred Kluever
 */
public class SipHashFunctionTest extends TestCase {

  // From https://131002.net/siphash/siphash24.c
  // k = 00 01 02 ...
  private static final long K0 = 0x0706050403020100L;
  private static final long K1 = 0x0f0e0d0c0b0a0908L;
  private static final HashFunction SIP_WITH_KEY = Hashing.sipHash24(K0, K1);

	0xfb3d,
	0xfb3f,
	0xfb42,
	0xfb45,
	0xfe53,
	0xfe67,
	0xfe75,
	0xffe7,
}

var isPrint32 = []uint32{
	0x010000, 0x01004d,
	0x010050, 0x01005d,
	0x010080, 0x0100fa,
	0x010100, 0x010102,
	0x010107, 0x010133,
	0x010137, 0x01019c,
	0x0101a0, 0x0101a0,
	0x0101d0, 0x0101fd,
	0x010280, 0x01029c,
	0x0102a0, 0x0102d0,
	0x0102e0, 0x0102fb,
	0x010300, 0x010323,
	0x01032d, 0x01034a,

00000030  13 00 23 00 00 ff 01 00  01 00 00 17 00 00 00 0b  |..#.............|
00000040  00 02 01 00 16 03 01 02  59 0b 00 02 55 00 02 52  |........Y...U..R|
00000050  00 02 4f 30 82 02 4b 30  82 01 b4 a0 03 02 01 02  |..O0..K0........|
00000060  02 09 00 e8 f0 9d 3f e2  5b ea a6 30 0d 06 09 2a  |......?.[..0...*|
00000070  86 48 86 f7 0d 01 01 0b  05 00 30 1f 31 0b 30 09  |.H........0.1.0.|

00000030  13 00 23 00 00 ff 01 00  01 00 00 17 00 00 00 0b  |..#.............|
00000040  00 02 01 00 16 03 03 02  59 0b 00 02 55 00 02 52  |........Y...U..R|
00000050  00 02 4f 30 82 02 4b 30  82 01 b4 a0 03 02 01 02  |..O0..K0........|
00000060  02 09 00 e8 f0 9d 3f e2  5b ea a6 30 0d 06 09 2a  |......?.[..0...*|
00000070  86 48 86 f7 0d 01 01 0b  05 00 30 1f 31 0b 30 09  |.H........0.1.0.|

00000030  13 00 23 00 00 ff 01 00  01 00 00 17 00 00 00 0b  |..#.............|
00000040  00 02 01 00 16 03 03 02  59 0b 00 02 55 00 02 52  |........Y...U..R|
00000050  00 02 4f 30 82 02 4b 30  82 01 b4 a0 03 02 01 02  |..O0..K0........|
00000060  02 09 00 e8 f0 9d 3f e2  5b ea a6 30 0d 06 09 2a  |......?.[..0...*|
00000070  86 48 86 f7 0d 01 01 0b  05 00 30 1f 31 0b 30 09  |.H........0.1.0.|

      : (tensor<32xf32>, tensor<64xf32>, tensor<8xf32>, tensor<2xf32>, tensor<2x!tf_type.string>)
        -> (tensor<32xf32>, tensor<64xf32>, tensor<8xf32>)
    tf_device.return %0#0, %0#1, %0#2 : tensor<32xf32>, tensor<64xf32>, tensor<8xf32>
  }) {device = "/job:localhost/replica:0/task:0/device:TPU:0"} : () -> (tensor<32xf32>, tensor<64xf32>, tensor<8xf32>)
  // CHECK-NEXT: tf_device.return
  // CHECK-NEXT: })

		{Ordered, 1, 401},
		{Ordered, 401, 6},
		{Ordered_Fail, 2, 401},

		// SetEqual unseen nodes and then connect
		{Checkpoint, 0, 0},
		{SetEqual, 500, 501},
		{SetEqual, 102, 501},
		{Equal, 500, 102},
		{Ordered, 501, 106},
		{Ordered, 100, 500},
		{SetEqual, 500, 501},
		{Ordered_Fail, 500, 501},
		{Ordered_Fail, 102, 501},

		// SetNonEqual relations
		{Undo, 0, 0},
		{Checkpoint, 0, 0},

    // CHECK-DAG:   %[[ZERO:.*]] = "tf.Const"() <{value = dense<0.000000e+00> : tensor<f32>}> : () -> tensor<f32>
    // CHECK-DAG:   %[[SCALE:.*]] = "tf.Const"() <{value = dense<1.05070102> : tensor<f32>}> : () -> tensor<f32>
    // CHECK-DAG:   %[[SCALED_ALPHA:.*]] = "tf.Const"() <{value = dense<1.75809932> : tensor<f32>}> : () -> tensor<f32>