%noncon3 = "tf.Complex"(%con1, %arg2) : (tensor<2xf32>, tensor<2xf32>) -> tensor<2xcomplex<f32>>

  %res1 = "tf.MulNoNan"(%arg0, %arg1) : (tensor<2xcomplex<f32>>, tensor<2xcomplex<f32>>) -> tensor<2xcomplex<f32>>
  %res2 = "tf.DivNoNan"(%arg0, %noncon2) : (tensor<2xcomplex<f32>>, tensor<2xcomplex<f32>>) -> tensor<2xcomplex<f32>>

func.func @testMinComplex(%arg0: tensor<4x8xcomplex<f32>>) -> tensor<4x1xcomplex<f32>> {
  %dimension = "tf.Const"() { value = dense<1> : tensor<1xi64> } : () -> tensor<1xi64>
  // expected-error@below {{'tf.Min' op operand #0 must be tensor of}}
  %0 = "tf.Min"(%arg0, %dimension) { keep_dims = true }: (tensor<4x8xcomplex<f32>>, tensor<1xi64>) -> tensor<4x1xcomplex<f32>>
  func.return %0 : tensor<4x1xcomplex<f32>>
}

// -----