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

// -----

func.func @testConv3dInvalidBiasShape(%arg0: tensor<2x3x4x5x2xf32>,%arg1:  tensor<2x2x2x2x3xf32>,%arg2: tensor<4xf32>) -> tensor<?x?x?x?x?xf32> {

// CHECK: %0 = tfl.sub %arg0, %cst_0 {fused_activation_function = "NONE"} : tensor<2x3x4x5xf32>
// CHECK: %1 = "tfl.transpose"(%0, %cst) : (tensor<2x3x4x5xf32>, tensor<4xi32>) -> tensor<5x2x3x4xf32>
// CHECK: return %1 : tensor<5x2x3x4xf32>

// -----

// CHECK-LABEL: permNotConstNoChange
func.func @permNotConstNoChange(%arg0: tensor<2x3x4x5xf32>, %perm: tensor<4xi32>) -> tensor<5x2x3x4xf32> {

  %cst = "tf.Const"() {device = "", value = dense<1.0> : tensor<2x3x3x3x2xf32>} : () -> tensor<2x3x3x3x2xf32>
  %0 = "tf.Conv3D"(%arg0, %cst) {
    data_format = "NDHWC", device = "", dilations = [1, 1, 1, 1, 1], padding = "SAME", strides = [1, 1, 2, 1, 1]
  } : (tensor<1x3x4x3x3xf32>, tensor<2x3x3x3x2xf32>) -> tensor<1x3x2x3x2xf32>
  %1 = "tf.Relu"(%0) {device = ""} : (tensor<1x3x2x3x2xf32>) -> tensor<1x3x2x3x2xf32>

// -----

// CHECK-LABEL: transpose_simple_4d
func.func @transpose_simple_4d() -> tensor<5x2x3x4xf32> {
  %0 = stablehlo.constant dense<1.000000e+0> : tensor<2x3x4x5xf32>
  %1 = stablehlo.transpose %0, dims = [3, 0, 1, 2] : (tensor<2x3x4x5xf32>) -> tensor<5x2x3x4xf32>
  return %1 : tensor<5x2x3x4xf32>
}
// CHECK-DAG: %[[CONST_0:.+]] = stablehlo.constant dense<1.000000e+00> : tensor<5x2x3x4xf32>
// CHECK-NOT: transpose

  %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> {

func.func @ConvertSliceToIdentityI32(%arg0: tensor<2x3x4x5xf32>) -> tensor<2x3x4x5xf32> {
  %begin = arith.constant dense<0> : tensor<4xi32>
  %shape = arith.constant dense<[2,3,4,5]> : tensor<4xi32>
  %0 = "tfl.slice"(%arg0, %begin, %shape) : (tensor<2x3x4x5xf32>, tensor<4xi32>, tensor<4xi32>) -> tensor<2x3x4x5xf32>
  func.return %0 : tensor<2x3x4x5xf32>
  // CHECK: return %arg0
}

}

func.func @LRN(%arg0: tensor<2x3x4x5xf32>) -> tensor<2x3x4x5xf32> {
  %0 = "tf.LRN"(%arg0) {depth_radius = 5 :i64, bias = 1.0 :f32, alpha = 1.0 : f32, beta = 0.5 :f32} : (tensor<2x3x4x5xf32>) -> (tensor<2x3x4x5xf32>)
  func.return %0: tensor<2x3x4x5xf32>

  // CHECK-LABEL: LRN