func.return %r0, %r1 : tensor<1xi32>, tensor<0xi32>
}

// -----

// CHECK-LABEL: @acos
func.func @acos(%arg0: tensor<2xf32>) -> tensor<2xf32> {
  // CHECK-NOT:  tf.Acos
  %0 = "tf.Acos"(%arg0) : (tensor<2xf32>) -> tensor<2xf32>
  func.return %0 : tensor<2xf32>
}

// -----

// NOFALLBACK-LABEL: @xla_svd

  func.return %2, %3, %4, %5: tensor<2xf32>, tensor<2xf32>, tensor<2xf32>, tensor<2xf32>
}

// CHECK-LABEL: func @addNWithZerosInt
func.func @addNWithZerosInt(%arg0: tensor<2xi32>) -> (tensor<2xi32>, tensor<2xi32>, tensor<2xi32>, tensor<2xi32>) {
  %0 = "tf.Const"() {value = dense<1> : tensor<2xi32>} : () -> tensor<2xi32>
  %1 = "tf.Const"() {value = dense<0> : tensor<2xi32>} : () -> tensor<2xi32>

  %s0 = "tf.Const"() {value = dense<[1, 2]> : tensor<2xi32>} : () -> tensor<2xi32>
  %s1 = "tf.Const"() {value = dense<[1, 2]> : tensor<2xi32>} : () -> tensor<2xi32>
  %r0, %r1 = "tf.BroadcastGradientArgs"(%s0, %s1) {} : (tensor<2xi32>, tensor<2xi32>) -> (tensor<0xi32>, tensor<0xi32>)

  // CHECK-DAG: %[[R:.*]] = "tf.Const"() <{value = dense<> : tensor<0xi32>}> : () -> tensor<0xi32>

     %t2 = "tf.Acosh"(%arg1) : (tensor<2xf32>) -> tensor<2xf32>
    "tf.Yield"(%t0, %t1, %t2) : (tensor<2xf32>, tensor<2xf32>, tensor<2xf32>) -> ()
    }, {
     %e0 = "tf.Neg"(%arg1) : (tensor<2xf32>) -> tensor<2xf32>
     %e1 = "tf.Relu"(%arg1) : (tensor<2xf32>) -> tensor<2xf32>
     %e2 = "tf.Sin"(%arg1) : (tensor<2xf32>) -> tensor<2xf32>
     "tf.Yield"(%e0, %e1, %e2) : (tensor<2xf32>, tensor<2xf32>, tensor<2xf32>) -> ()

  func.return %3 : tensor<2xi32>

  // CHECK: %[[CST:.*]] = arith.constant dense<1> : tensor<2xi32>
  // CHECK: return %[[CST]] : tensor<2xi32>
}

// CHECK-LABEL: @concat_3_tensors_1_empty
func.func @concat_3_tensors_1_empty() -> tensor<?xi32> {
  %0 = arith.constant dense<1> : tensor<2xi32>
  %1 = arith.constant dense<1> : tensor<2xi32>
  %2 = arith.constant dense<[]> : tensor<0xi32>

  func.return %0#0 : tensor<2xi32>

// CHECK-LABEL: unpack3Tensors
// CHECK: "tfl.unpack"(%arg0) <{axis = 1 : i32, num = 3 : i32}> : (tensor<2x3xi32>) -> (tensor<2xi32>, tensor<2xi32>, tensor<2xi32>)
}

func.func @unpackNegAxis(%arg0: tensor<2x3xi32>) -> tensor<2xi32> {
  %0:3 = "tf.Unpack"(%arg0) {axis = -1 : i64} : (tensor<2x3xi32>) -> (tensor<2xi32>, tensor<2xi32>, tensor<2xi32>)

  %0 = "tf.BroadcastTo"(%input, %shape) : (tensor<3xi32>, tensor<2xi32>) -> tensor<*xi32>
  func.return %0: tensor<*xi32>

// CHECK-LABEL: broadcast_to_i32_low_dim_with_unknown_output
// CHECK:  %0 = "tf.BroadcastTo"(%arg0, %arg1) : (tensor<3xi32>, tensor<2xi32>) -> tensor<*xi32>
// CHECK:  return %0 : tensor<*xi32>
}

  func.return %0 : tensor<?x?x?x?xi32>
}

// CHECK-LABEL:   func @add(
// CHECK-SAME:              %[[VAL_0:.*]]: tensor<2xi32>) -> tensor<2xi32> {
// CHECK:           %[[VAL_1:.*]] = "tf.AddV2"(%[[VAL_0]], %[[VAL_0]]) : (tensor<2xi32>, tensor<2xi32>) -> tensor<2xi32>
// CHECK:           %[[VAL_2:.*]] = "tf.AddV2"(%[[VAL_1]], %[[VAL_0]]) : (tensor<2xi32>, tensor<2xi32>) -> tensor<2xi32>
// CHECK:           return %[[VAL_2]] : tensor<2xi32>

  %0 = "tf.RealDiv"(%arg0, %arg0) : (tensor<2xi32>, tensor<2xi32>) -> tensor<2xi32>
  func.return %0: tensor<2xi32>
}

// CHECK-LABEL: func @sub
func.func @sub(%arg0: tensor<2xi32>) -> tensor<2xi32> {
  // CHECK-NEXT:  %0 = mhlo.subtract %arg0, %arg0 : tensor<2xi32>
  // CHECK-NEXT:  return %0 : tensor<2xi32>
  %0 = "tf.Sub"(%arg0, %arg0) : (tensor<2xi32>, tensor<2xi32>) -> tensor<2xi32>
  func.return %0: tensor<2xi32>
}

    // CHECK:     tf.BroadcastGradientArgs
    %r0, %r1 = "tf.BroadcastGradientArgs"(%s0, %s1) : (tensor<4xi32>, tensor<4xi32>) -> (tensor<1xi32>, tensor<0xi32>)
    func.return %r0, %r1 : tensor<1xi32>, tensor<0xi32>
  }

  // CHECK-LABEL: @acos
  func.func @acos(%arg0: tensor<2xf32>) -> tensor<2xf32> {
    // CHECK-NOT:  tf.Acos