func.return %0 : tensor<4x128xf32>
  }
  func.func @_func(%arg0: tensor<4x128xf32>) -> tensor<4x128xf32> {
    func.return %arg0 : tensor<4x128xf32>
  }

//                (tensor<4x2xf32>, tensor<4x2xf32>, tensor<4x2xf32>)
//
// will be converted into:
//
//   %0 = "mhlo.slice"(%input) {
//             limit_indices = dense<[4, 2]> : tensor<2xi64>,
//             start_indices = dense<0> : tensor<2xi64>,
//             strides = dense<1> : tensor<2xi64>} :
//        (tensor<4x6xf32>) -> tensor<4x2xf32>

//     -> tensor<5x2xf32>
//
// is lowered to
//
//   %shape = "tf.Const"() {value = dense<[-1, 2]> : tensor<2xi64>}
//   %inp0 = "tf.Reshape"(%arg0, %shape)
//     : (tensor<2xf32>, tensor<2xi64>) -> tensor<1x2xf32>
//   %inp1 = "tf.Reshape"(%arg1, %shape)
//     : (tensor<2x2x2xf32>, tensor<2xi64>) -> tensor<4x2xf32>
//   %items0 = "tf.Unpack"(%[[INP0]]) {axis = 0 : i64}

func.func @testPack(%arg0: tensor<4x8xf32>, %arg1: tensor<4x8xf32>) -> tensor<*xf32> {
  %0 = "tf.Pack"(%arg0, %arg1) {axis = 1 : i64} : (tensor<4x8xf32>, tensor<4x8xf32>) -> tensor<*xf32>
  func.return %0 : tensor<*xf32>
}


// -----

func.func @testPack(%arg0: tensor<4x8xf32>, %arg1: tensor<4x2xf32>) -> tensor<*xf32> {

  // CHECK-NOT: tf.TensorListReserve
  // CHECK: tf.BroadcastTo
  // CHECK-SAME: tensor<10x32xf32>
  %tl1 = "tf.TensorListReserve"(%arg0, %max_size) : (tensor<*xi32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<32xf32>>>
  func.return
}

// -----

// Tests that the pass reports error on unknown maximum size.

func.func @main(%arg0: tensor<i32>) -> () {

    return success();
  }
};

// Fuses Unpack with proceeding Concatenation to Reshape if output type has
// static shape and activation function is none. For example:
//
//   // %input: tensor<1x3x2xf32>
//   %unpack:3 = "tfl.unpack"(%input) {axis = 1 : i32, num = 3 : i32}
//   %res = "tfl.concatenation"(%unpack#0, %unpack#1, %unpack#2)
//        {axis = -1 : i32, fused_activation_function = "NONE"}
//