func.return %0 : tensor<?x?x?x?x?xf32>
}

// -----

func.func @testConv3dMisMatchInputType(%arg0: tensor<2x3x4x5x2xi32>,%arg1:  tensor<2x2x2x2x3xf32>,%arg2: tensor<3xf32>) -> tensor<?x?x?x?x?xf32> {

    %12 = "tf.Identity"(%11) {device = ""} : (tensor<2x3x4x5xi8>) -> tensor<2x3x4x5xi8>
    %13 = "tf.Cast"(%12) {Truncate = false, device = ""} : (tensor<2x3x4x5xi8>) -> tensor<2x3x4x5xi32>
    %14 = "tf.Sub"(%13, %cst_5) {device = ""} : (tensor<2x3x4x5xi32>, tensor<i32>) -> tensor<2x3x4x5xi32>
    %15 = "tf.Identity"(%5) {device = ""} : (tensor<2x6x4x5xi8>) -> tensor<2x6x4x5xi8>

  auto build_result = BuildHloFromGraph(*graph, /*use_output_shapes=*/true);
  ASSERT_FALSE(build_result.ok());
  EXPECT_THAT(build_result.message(),
              HasSubstr("op operand type 'tensor<2x3x4x5xi32>' and result type "
                        "'tensor<1xi32>' are cast incompatible"));
}

}  // namespace

func.func @identityTransposeConst(%arg0: tensor<2x3x4x5x6xf32>) -> tensor<2x3x4x5x6xf32> {
  %0 = arith.constant dense<[0, 1, 2, 3, 4]> : tensor<5xi32>
  %1 = "tf.Transpose"(%arg0, %0) : (tensor<2x3x4x5x6xf32>, tensor<5xi32>) -> tensor<2x3x4x5x6xf32>

  func.return %1 : tensor<2x3x4x5x6xf32>
  // CHECK: return %arg0
}

// CHECK-LABEL: @nonIdentityTranspose
func.func @nonIdentityTranspose(%arg0: tensor<2x3x4x5x6xf32>) -> tensor<2x3x4x6x5xf32> {