%1 = "tf.OpB"() {_XlaSharding = "\08\03\1A\02\02\01\22\02\00\02"} : () -> tensor<2x2xi64>
        // expected-error @+1 {{should have the same sharding}}
        %2 = "tf.OpC"(%0, %1) {_xla_map_outside_compilation = "0", _xla_outside_compilation = "from_launch"} : (tensor<2x2xi64>, tensor<2x2xi64>) -> tensor<2x2xi64>
        "tf.OpD"(%2) : (tensor<2x2xi64>) -> ()
        tf_device.return

}

func.func @concat_v2_i64_axis(%arg0: tensor<2x1xi32>, %arg1: tensor<2x1xi32>, %arg2: tensor<2x1xi32>) -> tensor<2x3xi32> {
  %0 = "tf.Const"() { value = dense<-1> : tensor<i64> } : () -> tensor<i64>
  %1 = "tf.ConcatV2"(%arg0, %arg1, %arg2, %0) : (tensor<2x1xi32>, tensor<2x1xi32>, tensor<2x1xi32>, tensor<i64>) -> tensor<2x3xi32>

  func.return %0 : tensor<?x?xf32>
}

// -----

func.func @stridedSliceGrad(%dy: tensor<4x8xf32>, %begin: tensor<2xi64>, %end: tensor<2xi64>, %strides: tensor<2xi64>, %shape: tensor<1x2xi64>) -> tensor<?x?xf32> {
  // expected-error @+1 {{'shape' operand must be 1D tensor, but got 2D tensor}}

}

// CHECK-LABEL: @testMatrixSetDiag
func.func @testMatrixSetDiag(%arg0: tensor<3x3xi64>, %arg1: tensor<3xi64>) -> tensor<3x3xi64> {
  %0 = "tf.MatrixSetDiag"(%arg0, %arg1) {device = "/job:localhost/replica:0/task:0/device:GPU:0"} : (tensor<3x3xi64>, tensor<3xi64>) -> tensor<3x3xi64>
  func.return %0 : tensor<3x3xi64>

  // CHECK: %[[ZERO:.*]] = "tf.Const"() <{value = dense<0> : tensor<i32>}>

// CHECK-LABEL: testAddWithI64Broadcasting
func.func @testAddWithI64Broadcasting(tensor< 2x3xi64>, tensor<3xi64>) -> tensor<2x3xi64> {
^bb0(%arg0: tensor<2x3xi64>, %arg1: tensor<3xi64>):
  // CHECK: tfl.add(%arg0, %arg1)
  %0 = tfl.add(%arg0, %arg1) {fused_activation_function = "RELU6"} : (tensor< 2x3xi64>, tensor<3xi64>) -> tensor<2x3xi64>
  func.return %0#0 : tensor<2x3xi64>
}

// -----

// CHECK-LABEL: add_with_i32_five_dim_broadcasting

// CHECK-DAG:       [[VAL_35:%.*]] = arith.constant dense<0> : tensor<1xi64>
// CHECK-DAG:       [[VAL_36:%.*]] = arith.constant dense<1> : tensor<1xi64>
// CHECK:           [[VAL_37:%.*]] = "tf.Slice"([[VAL_3]], [[VAL_35]], [[VAL_36]]) : (tensor<2xf32>, tensor<1xi64>, tensor<1xi64>) -> tensor<1xf32>
// CHECK-DAG:       [[VAL_38:%.*]] = arith.constant dense<1> : tensor<1xi64>

// CHECK: %[[BITCAST2:.+]] = "tfl.bitcast"(%[[ARG2]]) : (tensor<i64>) -> tensor<1xi64>
// CHECK: %[[MIN2:.+]] = "tfl.minimum"(%[[BITCAST2]], %[[MAX2]]) : (tensor<1xi64>, tensor<1xi64>) -> tensor<1xi64>
// CHECK: %[[CONCAT:.+]] = "tfl.concatenation"(%[[MIN1]], %[[MIN2]]) <{axis = 0 : i32, fused_activation_function = "NONE"}> : (tensor<1xi64>, tensor<1xi64>) -> tensor<2xi64>

    %shape_64 = "tf.TensorListElementShape"(%tl_1) : (tensor<!tf_type.variant<tensor<?x1xf32>>>) -> tensor<?xi64>
    // CHECK: %[[CAST:.*]] = "tf.Cast"(%[[ELEMENT_SHAPE]]){{.*}}: (tensor<2xi32>) -> tensor<2xi64>
    // CHECK: "tf._SomeOtherOp"(%[[ELEMENT_SHAPE]], %[[CAST]])
    "tf._SomeOtherOp"(%shape_32, %shape_64) : (tensor<?xi32>, tensor<?xi64>) -> ()
    func.return
  }