// CHECK:           return %[[VAL_2]] : tensor<10x8xi64>
// CHECK:         }
func.func @convert_remainder_for_int64(%arg0: tensor<10x8xi64>, %arg1: tensor<10x8xi64>) -> tensor<10x8xi64> {
  %0 = mhlo.remainder %arg0, %arg1 : tensor<10x8xi64>
  func.return %0 : tensor<10x8xi64>
}

// CHECK-LABEL:   func @not_convert_remainder_for_int16(
// CHECK-NOT:       "tf.Mod"

func.func @all(%input: tensor<4x8xi1>) -> tensor<4xi1> {
  %dims = "tf.Const"() { value = dense<1> : tensor<1xi32>} : () -> tensor<1xi32>
  // CHECK: %[[INIT:.*]] = mhlo.constant dense<true> : tensor<i1>
  // CHECK: %[[REDUCED:.*]] = mhlo.reduce(%{{.*}} init: %[[INIT]]) applies mhlo.and across dimensions = [1] : (tensor<4x8xi1>, tensor<i1>) -> tensor<4xi1>
  %0 = "tf.All"(%input, %dims) : (tensor<4x8xi1>, tensor<1xi32>) -> tensor<4xi1>

  %1 = "tfl.select"(%0, %cst_0, %arg0) : (tensor<10xi1>, tensor<10xf32>, tensor<10xf32>) -> tensor<10xf32>
  %2 = "tfl.exp"(%1) : (tensor<10xf32>) -> tensor<10xf32>
  %3 = tfl.sub(%2, %cst) {fused_activation_function = "NONE"} : (tensor<10xf32>, tensor<f32>) -> tensor<10xf32>
  %4 = "tfl.select"(%0, %arg0, %3) : (tensor<10xi1>, tensor<10xf32>, tensor<10xf32>) -> tensor<10xf32>