%m0 = mhlo.constant dense<0> : tensor<i32>
  %t0 = "tf.Const"() { value = dense<0> : tensor<1xi32> } : () -> tensor<1xi32>
  %m1 = mhlo.constant dense<1> : tensor<i32>
  %t1 = "tf.Const"() { value = dense<1> : tensor<1xi32> } : () -> tensor<1xi32>
  %m2 = mhlo.constant dense<1> : tensor<i32>
  %t2 = "tf.Const"() { value = dense<1> : tensor<1xi32> } : () -> tensor<1xi32>
  %m3 = mhlo.constant dense<1> : tensor<i32>

  // CHECK-DAG: %[[INDICES_3:.*]] = "tf.Mul"(%[[INDICES_2]], %arg0) : (tensor<5xi32>, tensor<5xi32>) -> tensor<5xi32>
  // CHECK-DAG: %[[INDICES_4:.*]] = "tf.TensorScatterAdd"(%[[cst_3]], %0, %[[UPDATES]]) : (tensor<5xi32>, tensor<5x1xi32>, tensor<5xi32>) -> tensor<5xi32>
  // CHECK-DAG: %[[INDICES_5:.*]] = "tf.AddV2"(%[[INDICES_3]], %[[INDICES_4]]) : (tensor<5xi32>, tensor<5xi32>) -> tensor<5xi32>

func.func @testCompatibleCastType(%arg0: tensor<?xf32>) -> (tensor<10xf32>, tensor<10xf32>) {
  %0 = "tf.Cast"(%arg0) {Truncate = false} : (tensor<?xf32>) -> tensor<10xf32>
  %1 = "tf.Cast"(%arg0) {Truncate = true} : (tensor<?xf32>) -> tensor<10xf32>
  func.return %0, %1: tensor<10xf32>, tensor<10xf32>

  // CHECK: %0 = "tf.Cast"(%arg0) <{Truncate = false}> : (tensor<?xf32>) -> tensor<10xf32>

  // CHECK-NEXT: %[[CONST1:.*]] = "tf.Const"() <{value = dense<1> : tensor<1xi32>}> : () -> tensor<1xi32>
  // CHECK-NEXT: %[[NEW_SIZE:.*]] = "tf.AddV2"(%[[READ_SIZE]], %[[CONST1]]) : (tensor<1xi32>, tensor<1xi32>) -> tensor<1xi32>
  // CHECK-NEXT: "tf.AssignVariableOp"(%[[SIZE]], %[[NEW_SIZE]]) : (tensor<!tf_type.resource<tensor<1xi32>>>, tensor<1xi32>) -> ()

    %0 = "tf.Sub"(%cst_0, %cst_1) : (tensor<8xf32>, tensor<8xf32>) -> tensor<8xf32>
    return %0 : tensor<8xf32>
  }
// CHECK: @serving_default
// CHECK-DAG: %[[VAR_HANDLE_2:.*]] = "tf.VarHandleOp"() {{.*shared_name = "const_0".*}} : () -> tensor<!tf_type.resource<tensor<8xf32>>>
// CHECK-DAG: %[[READ_VAR_0:.*]] = "tf.ReadVariableOp"(%[[VAR_HANDLE_2]]) : (tensor<!tf_type.resource<tensor<8xf32>>>) -> tensor<8xf32>

func.func @RemoveRedundantPack(%arg0: tensor<2x5xf32>) -> (tensor<2x5xf32>, tensor<5xf32>) {
  %0:2 = "tfl.unpack"(%arg0) {axis = 0 : i32, num = 2 : i32} : (tensor<2x5xf32>) -> (tensor<5xf32>, tensor<5xf32>)
  %1 = "tfl.pack"(%0#0, %0#1) {axis = 0 : i32, values_count = 2 : i32} : (tensor<5xf32>, tensor<5xf32>) -> (tensor<2x5xf32>)
  func.return %1, %0#0: tensor<2x5xf32>, tensor<5xf32>
  // CHECK: %[[UNPACK:.*]]:2 = "tfl.unpack"

// CHECK-LABEL: func @testLeakyRelu(%arg0: tensor<16xf32>)
func.func @testLeakyRelu(tensor<16xf32>) -> tensor<16xf32> {
^bb0(%arg0: tensor<16xf32>):
  %0 = "tf.LeakyRelu"(%arg0) {alpha = 0.2 : f32} : (tensor<16xf32>) -> tensor<16xf32>
  func.return %0 : tensor<16xf32>
}

// -----
func.func @testLeakyWrongAlphaType(tensor<16xf32>) -> tensor<16xf32> {
^bb0(%arg0: tensor<16xf32>):

  %5 = shape.shape_of %4 : tensor<?x10xf32> -> tensor<2xindex>
  %6 = stablehlo.dynamic_broadcast_in_dim %1, %5, dims = [1] : (tensor<10xf32>, tensor<2xindex>) -> tensor<?x10xf32>
  %7 = stablehlo.add %4, %6 : tensor<?x10xf32>
  %8 = stablehlo.clamp %2, %7, %3 : (tensor<f32>, tensor<?x10xf32>, tensor<f32>) -> tensor<?x10xf32>
  func.return %8: tensor<?x10xf32>
}

  // Just to introduce an extra use for %cst.
  %1 = "tf.AddV2"(%cst, %cst) {device = ""} : (tensor<1xi32>, tensor<1xi32>) -> tensor<1xi32>

  return %0 : tensor<16xf32>
}
// Check that the constant is cloned with same value.
// CHECK-DAG: %[[CST_0:.*]] = "tf.Const"()
// CHECK-SAME: value = dense<1> : tensor<1xi32>
// CHECK-DAG: %[[CST_1:.*]] = "tf.Const"()

    // CHECK: %[[MUL:.*]] = "tf.Mul"{{.*}} (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
    // CHECK: %[[UNKNOWN:.*]] = "tf.Unknown"(%[[MUL]], %[[MUL]]) : (tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
    // CHECK: return %[[UNKNOWN]] : tensor<*xf32>
    %0 = "tf.Mul"(%arg0, %arg0) : (tensor<1xf32>, tensor<1xf32>) -> tensor<*xf32>
    %1 = "tf.Unknown"(%0, %0) : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>