%19 = "tf.StringLength"(%arg0) {device = "", unit = "BYTE"} : (tensor<1x!tf_type.string>) -> tensor<1xi32>
  %20 = "tf.ExpandDims"(%19, %7) {device = ""} : (tensor<1xi32>, tensor<i32>) -> tensor<1x1xi32>
  %21 = "tf.Cast"(%20) {Truncate = false, device = ""} : (tensor<1x1xi32>) -> tensor<1x1xi64>
  %22 = "tf.Reshape"(%21, %12) {device = ""} : (tensor<1x1xi64>, tensor<1xi64>) -> tensor<1xi64>

// CHECK-DAG: %[[CONST_0:.+]] = "tfl.pseudo_const"() <{value = dense<{{\[\[0, 0\], \[1, 1\], \[1, 1\], \[0, 0\]\]}}> : tensor<4x2xi32>}> : () -> tensor<4x2xi32>

  %11 = "tf.Reshape"(%10, %0) {device = ""} : (tensor<4x1x1x2x1xi32>, tensor<2xi32>) -> tensor<4x2xi32>
  %12 = "tf.Transpose"(%11, %6) {device = ""} : (tensor<4x2xi32>, tensor<2xi32>) -> tensor<2x4xi32>
  %13 = "tf.Reshape"(%arg0, %1) {device = ""} : (tensor<1x1x2x1xf32>, tensor<1xi32>) -> tensor<2xf32>

}

// -----

func.func @testPadUnsupportedPaddings(tensor<*xf32>, tensor<6x3xi32>) -> tensor<? x f32> {
^bb0(%arg0: tensor<*xf32>, %arg1: tensor<6x3xi32>):
  // expected-error @+1 {{'tfl.pad' op failed to verify that the first dim size of the padding argument must be at most 5}}
  %0 = "tfl.pad"(%arg0, %arg1) : (tensor<*xf32>, tensor<6x3xi32>) -> tensor<? x f32>
  func.return %0#0 : tensor<? x f32>
}

// -----

//                   (tensor<4x1xf32>, tensor<4x2xf32>, tensor<4x3xf32>)
//
// We will generate slices following slices:
// %0 = "mhlo.slice"(%input) {
//        limit_indices = dense<[4, 1]> : tensor<2xi64>,
//        start_indices = dense<0> : tensor<2xi64>,
//        strides = dense<1> : tensor<2xi64>} :
//        (tensor<4x6xf32>) -> tensor<4x1xf32>
// %1 = "mhlo.slice"(%input) {