// -----

func.func @transpose_output_type_bad(%arg0 : tensor<3x4x5x6xi32>) -> tensor<3x4x5x6xi32> {
  %cst = arith.constant dense<[0, 3, 1, 2]> : tensor<4xi32>
  // expected-error @+1 {{expect output type tensor<3x6x4x5xi32>, got tensor<3x4x5x6xi32>}}
  %0 = "tfl.transpose"(%arg0, %cst) : (tensor<3x4x5x6xi32>, tensor<4xi32>) -> tensor<3x4x5x6xi32>
  func.return %0 : tensor<3x4x5x6xi32>
}


// -----

  // CHECK: return %[[v3]] : tensor<2x7x11x5xf32>
}

func.func @einsum_4d_1(%arg0: tensor<3x4x5x6xf32>, %arg1: tensor<3x7x5x6xf32>) -> tensor<3x5x4x7xf32> {
  %0 = "tf.Einsum"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", equation = "jbki,jfki->jkbf"}: (tensor<3x4x5x6xf32>, tensor<3x7x5x6xf32>) -> tensor<3x5x4x7xf32>
  func.return %0 : tensor<3x5x4x7xf32>
  // CHECK-LABEL: einsum_4d_1

    %18 = "tf.Einsum"(%14, %17) {device = "", equation = "abcd,aecd->acbe"} : (tensor<2x3x4x5xi32>, tensor<2x6x4x5xi32>) -> tensor<2x4x3x6xi32>
    %19 = "tf.Cast"(%18) {Truncate = false, device = ""} : (tensor<2x4x3x6xi32>) -> tensor<2x4x3x6xf32>
    %20 = "tf.Mul"(%19, %cst_0) {device = ""} : (tensor<2x4x3x6xf32>, tensor<f32>) -> tensor<2x4x3x6xf32>