^bb0(%arg0: tensor<2x1x3xf32>, %arg1: tensor<3x2xi32>):
  %0 = "tf.MirrorPad"(%arg0, %arg1) { mode = "SYMMETRIC" }: (tensor<2x1x3xf32>, tensor<3x2xi32>) -> tensor<? x f32>
  func.return %0#0 : tensor<? x f32>

  // CHECK-LABEL: mirror_pad
  // CHECK:  "tfl.mirror_pad"(%arg0, %arg1) <{mode = #tfl<mirror_pad_attr SYMMETRIC>}> : (tensor<2x1x3xf32>, tensor<3x2xi32>) -> tensor<?xf32>
  // CHECK:  return
}

// -----

// Tests static range quantized dot_general with symmetric quantized input.

func.func @dot_general_upstream_srq_sym_input(%arg0: tensor<1x2x3x4x!quant.uniform<i8:f32, 1.000000e+0>>) -> tensor<1x2x3x5x!quant.uniform<i8:f32, 4.000000e+0>> {

  let description = [{
Computes the 2-dimensional discrete Fourier transform of a real-valued signal
over the inner-most 2 dimensions of `input`.

Since the DFT of a real signal is Hermitian-symmetric, `RFFT2D` only returns the
`fft_length / 2 + 1` unique components of the FFT for the inner-most dimension
of `output`: the zero-frequency term, followed by the `fft_length / 2`
positive-frequency terms.

  %paddings = "tf.Const"() {value = dense<[0, 1]> : tensor<2xi64>} : () -> tensor<2xi64>
  // expected-error @+1 {{failed to verify that operand 1 is 2-D}}
  %0 = "tf.MirrorPad"(%input, %paddings) { mode = "SYMMETRIC" }: (tensor<2xi64>, tensor<2xi64>) -> tensor<3xi64>
  func.return %0 : tensor<3xi64>
}

// -----