%18 = "tf.Const"() {value = dense<1> : tensor<4xi32>} : () -> tensor<4xi32>
  %57 = "tf.Const"() {value = dense<0> : tensor<4xi32>} : () -> tensor<4xi32>
  %534 = "tf.StridedSlice"(%arg0, %57, %57, %18) {begin_mask = 11 : i64, device = "", ellipsis_mask = 0 : i64, end_mask = 11 : i64, new_axis_mask = 4 : i64, shrink_axis_mask = 0 : i64} : (tensor<*xf32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>) -> tensor<*xf32>
  "func.return"(%534) : (tensor<*xf32>) -> ()

  %8 = "tfl.mul"(%2, %3) {fused_activation_function = "NONE"} : (tensor<4xi32>, tensor<4xi32>) -> tensor<4xi32>

  func.return %5, %6, %7, %8 : tensor<i32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>
}

// CHECK-LABEL: @add_dense_splat_int
func.func @add_dense_splat_int() -> tensor<4xi32> {
  %0 = arith.constant dense<[-10, -1, 42, 100]> : tensor<4xi32>

  // Convert input: NCHW -> NHWC
  %0 = "tf.Const"() {value = dense<[0, 2, 3, 1]> : tensor<4xi32>} : () -> tensor<4xi32>
  %1 = "tf.Transpose"(%arg0, %0) : (tensor<1x3x32x32xf32>, tensor<4xi32>) -> tensor<1x32x32x3xf32>

  // Compute in NHWC
  %2 = "tf.Conv2D"(%1, %arg1)
    {
      data_format = "NHWC",
      padding = "SAME",
      strides = [1, 1, 1, 1],

// -----

func.func @testFusedActivationFunction(%arg0: tensor<4xi32>, %arg1: tensor<4xi32>) -> (tensor<4xi32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>) {
  // CHECK: "NONE"
  %0 = tfl.add %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<4xi32>
  // CHECK: "RELU"
  %1 = tfl.add %arg0, %arg1 {fused_activation_function = "RELU"} : tensor<4xi32>
  // CHECK: "RELU_N1_TO_1"

  // CHECK-DAG: %[[cst:.*]] = arith.constant dense<[0, 2, 1, 3]> : tensor<4xi32>
  // CHECK-DAG: %[[cst_1:.*]] = arith.constant dense<[0, 2, 3, 1]> : tensor<4xi32>
  // CHECK: %[[v0:.*]] = "tf.Transpose"(%arg0, %[[cst]]) : (tensor<2x5x7x3xf32>, tensor<4xi32>) -> tensor<2x7x5x3xf32>
  // CHECK: %[[v1:.*]] = "tf.Transpose"(%arg1, %[[cst_1]]) : (tensor<2x4x7x3xf32>, tensor<4xi32>) -> tensor<2x7x3x4xf32>

  %1 = "tf.Transpose"(%arg0, %0) : (tensor<1x4x4x8xf32>, tensor<4xi32>) -> tensor<1x8x4x4xf32>
  %2 = "tf.Transpose"(%1, %0) : (tensor<1x8x4x4xf32>, tensor<4xi32>) -> tensor<1x4x8x4xf32>
  %3 = "tf.Transpose"(%arg1, %0) : (tensor<1x4x4x8xf32>, tensor<4xi32>) -> tensor<1x8x4x4xf32>
  %4 = "tf.Transpose"(%3, %0) : (tensor<1x8x4x4xf32>, tensor<4xi32>) -> tensor<1x4x8x4xf32>

  %0 = "tf.AddV2"(%arg0, %arg1) {device = ""} : (tensor<1x1x2x3xf32>, tensor<2x3xf32>) -> tensor<1x1x2x3xf32>
  %1 = "tf.Transpose"(%0, %cst) {device = ""} : (tensor<1x1x2x3xf32>, tensor<4xi32>) -> tensor<1x2x1x3xf32>

  func.return %1 : tensor<1x2x1x3xf32>

  // CHECK: %[[CST:.*]] = "tf.Const"() <{value = dense<[0, 2, 1, 3]> : tensor<4xi32>}> : () -> tensor<4xi32>

    // CHECK: tf.Const
    // CHECK-SAME: () -> tensor<4xi32>
    %0 = "tf.Const"() {value = dense<[200, 26, 26, 32]> : tensor<4xi32>} : () -> tensor<*xi32>
    // CHECK: tf.Const
    // CHECK-SAME: () -> tensor<4xi32>
    %1 = "tf.Const"() {value = dense<[200, 26, 26, 32]> : tensor<4xi32>} : () -> tensor<*xi32>
    // CHECK: tf.Add
    // CHECK-SAME: (tensor<4xi32>, tensor<4xi32>) -> tensor<4xi32>

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

// CHECK-LABEL: func @shift_left
func.func @shift_left(%arg0: tensor<4xi32>, %arg1: tensor<4xi32>) -> tensor<4xi32> {
  // CHECK:  mhlo.shift_left %arg0, %arg1 : tensor<4xi32>
  %0 = "tf.LeftShift"(%arg0, %arg1) : (tensor<4xi32>, tensor<4xi32>) -> tensor<4xi32>
  func.return %0 : tensor<4xi32>
}

// CHECK-LABEL: func @div_unranked

func.func @main(%arg0: tensor<4xi8>, %arg1: tensor<4xi32>) -> (tensor<4xi32>, tensor<4xi8>)
// CHECK: attributes {tf.entry_function = {inputs = "input0,input1", outputs = "output0,output1"}}
attributes {tf.entry_function = {inputs = "input0,input1", outputs = "output0,output1"}} {
  %0 = "tfl.neg"(%arg0) : (tensor<4xi8>) -> tensor<4xi8> loc("neg")
  %1 = "tfl.neg"(%arg1) : (tensor<4xi32>) -> tensor<4xi32> loc("neg")