host_compute_core = [], input_sharding_configuration = ["\08\01\1A\01\01\22\01\00", "\08\01\1A\01\01\22\01\00", "\08\01\1A\01\01\22\01\00", "\08\01\1A\01\01\22\01\00", "\08\01\1A\01\01\22\01\00", "\08\01\1A\01\01\22\01\00", "\08\01\1A\01\01\22\01\00", "\08\01\1A\01\01\22\01\00", "\08\01\1A\01\01\22\01\00"], num_cores_per_replica = 1 : i64, output_sharding_configuration = ["\08\01\1A\01\01\22\01\00", "\08\01\1A\01\01\22\01\00", "\08\01\1A\01\01\22\01\00", "\08\01\1A\01\01\22\01\00"], step_marker_location...

      NumDynamicShapes = 0 : i64,
      // The metadata encodes 2 parameter and two return values.
      metadata = "\0A\0E\08\01\18\01\22\08\08\01\1A\01\01\22\01\00\0A \08\01\12\10\12\02\08\03\12\02\08\03\12\02\08\01\12\02\08 \18\01\22\08\08\01\1A\01\01\22\01\00\12\0A\0A\08\08\01\1A\01\01\22\01\00\12\0A\0A\08\08\01\1A\01\01\22\01\00\18\02 \01",
      mlir_module = "..."} : () -> (tensor<!tf_type.string>, tensor<2x!tf_type.string>)

    // CHECK:      "tf._TPUCompil...

  // CHECK: input_sharding_configuration
  // CHECK-SAME: ["\08\01\1A\01\01\22\01\00"]
  // CHECK: output_sharding_configuration
  // CHECK-SAME: ["\08\01\1A\01\01\22\01\00"]
  func.return
}

// CHECK-LABEL: func @func_without_sharding
// CHECK-SAME: (%{{[a-z0-9]+}}: tensor<*xi32> {mhlo.sharding = "\08\01\1A\01\01\22\01\00"})
// CHECK-SAME: -> (tensor<*xi32> {mhlo.sharding = "\08\01\1A\01\01\22\01\00"})

        given:
        def consoleOutput = """\u001B[1A\u001B[1m> Connecting to Daemon\u001B[m\u001B[22D
\u001B[1A\u001B[90m> IDLE\u001B[39m\u001B[0K\u001B[6D
\u001B[1A\u001B[1m<-------------> 0% CONFIGURING [0s]\u001B[m\u001B[35D\u001B[1B\u001B[1m> root project\u001B[m\u001B[14D

              metadata = "\0A\0E\08\01\18\01\22\08\08\01\1A\01\01\22\01\00\0A \08\01\12\10\12\02\08\03\12\02\08\03\12\02\08\01\12\02\08 \18\01\22\08\08\01\1A\01\01\22\01\00\0A\0E\08\01\18\01\22\08\08\01\1A\01\01\22\01\00\12\0A\0A\08\08\01\1A\01\01\22\01\00\12\0A\0A\08\08\01\1A\01\01\22\01\00\12\0A\0A\08\08\01\1A\01\01\22\01\00\18\02 \01",

00000110  b6 d7 49 a6 b5 68 1a 41  03 56 6b dc 5a 89        |..I..h.A.Vk.Z.|
>>> Flow 2 (server to client)
00000000  16 03 03 00 5d 02 00 00  59 03 03 1c ad ae e9 64  |....]...Y......d|
00000010  35 80 c6 04 f5 69 05 bb  5c 38 78 d3 99 2f ad e6  |5....i..\8x../..|
00000020  56 20 d4 79 89 1a 51 54  14 ac 6d 20 06 6d 1a bd  |V .y..QT..m .m..|

00000220  6f 6c 61 6e 67 30 0d 06  09 2a 86 48 86 f7 0d 01  |olang0...*.H....|
00000230  01 0b 05 00 03 81 81 00  9d 30 cc 40 2b 5b 50 a0  |.........0.@+[P.|
00000240  61 cb ba e5 53 58 e1 ed  83 28 a9 58 1a a9 38 a4  |a...SX...(.X..8.|
00000250  95 a1 ac 31 5a 1a 84 66  3d 43 d3 2d d9 0b f2 97  |...1Z..f=C.-....|
00000260  df d3 20 64 38 92 24 3a  00 bc cf 9c 7d b7 40 20  |.. d8.$:....}.@ |
00000270  01 5f aa d3 16 61 09 a2  76 fd 13 c3 cc e1 0c 5c  |._...a..v......\|

      func.func @main(%arg0: tensor<2x2xf32>) -> (tensor<2x2xf32> {mhlo.sharding = "\08\03\1A\02\02\01\22\02\00\01"}) {
        %0 = tf_executor.graph {
          %outputs, %control = tf_executor.island wraps "tf.XlaSharding"(%arg0) {_XlaSharding = "\08\03\1A\02\02\01\22\02\00\01", sharding = "\08\03\1A\02\02\01\22\02\00\01"} : (tensor<2x2xf32>) -> tensor<2x2xf32>

00000000  16 03 02 00 5d 02 00 00  59 03 02 79 2f de f0 f3  |....]...Y..y/...|
00000010  97 6a 5e e3 07 66 d9 f2  8b e9 be 1a 97 9f 6d c8  |.j^..f........m.|
00000020  9d b5 88 57 fc 8c 5d 7f  d7 3e 34 20 e5 4c 51 33  |...W..]..>4 .LQ3|
00000030  52 23 a0 52 77 ca 41 4a  1b e4 22 fb 1c 82 f8 e4  |R#.Rw.AJ..".....|
00000040  aa 13 c2 1a ce cd d5 42  de b0 e9 10 c0 13 00 00  |.......B........|