func.return %0 : tensor<1x64x84x32xf32>

  %0 = "tfl.custom"(%arg0, %arg1, %arg2) {custom_code = "Convolution2DTransposeBias", custom_option = #tfl<const_bytes : "0x010000000200000002000000">} : (tensor<32x4x4x128xf32>, tensor<1x32x42x128xf32>, tensor<4xi32>) -> tensor<1x64x84x32xf32>
  func.return %0 : tensor<1x64x84x32xf32>
}
// CHECK-LABEL: main

  %0 = "tfl.custom"(%arg0, %arg1, %arg2) {custom_code = "Convolution2DTransposeBias", custom_option = #tfl<const_bytes : "0x010000000200000002000000">} : (tensor<32x4x4x128xf32>, tensor<1x32x42x128xf32>, tensor<4xi32>) -> tensor<1x64x84x32xf32>
  func.return %0 : tensor<1x64x84x32xf32>
}
// CHECK-LABEL: main

  %cst = "tfl.no_value"() {value = unit} : () -> none
  // CHECK: _arithmetic_count = 176160768 : i64
  %0 = "tfl.transpose_conv"(%arg0, %arg1, %arg2, %cst) {padding = "SAME", stride_h = 2 : i32, stride_w = 2 : i32, fused_activation_function = "NONE"} : (tensor<4xi32>, tensor<32x4x4x128xf32>, tensor<1x32x42x128xf32>, none) -> tensor<1x64x84x32xf32>
  func.return %0 : tensor<1x64x84x32xf32>
}

  %1 = "tfl.add"(%0, %cst) {fused_activation_function = "NONE"} : (tensor<1x64x84x32xf32>, tensor<32xf32>) -> tensor<1x64x84x32xf32>
  func.return %1 : tensor<1x64x84x32xf32>

  // CHECK-DAG: %[[SHAPE:.*]] = arith.constant dense<[1, 64, 84, 32]> : tensor<4xi32>

}

// -----

func.func @testTFLiteDetectionPostProcess(%arg0: tensor<1x64x64x32xf32>, %arg1: tensor<1x64x64x32xf32>, %arg2: tensor<1x64x64x32xf32>) -> (tensor<1x32x32x32xf32>, tensor<1x32x32x32xf32>) {
  %0, %1, %2, %3 = "tfl.custom_tf"(%arg0, %arg1, %arg2) ({
  ^bb0(%a0: tensor<1x64x64x32xf32>, %a1: tensor<1x64x64x32xf32>, %a2: tensor<1x64x64x32xf32>):

  %27 = mhlo.subtract %26, %19 : tensor<1x64x32x32xf32>
  %28 = "mhlo.broadcast_in_dim"(%1) <{broadcast_dimensions = dense<3> : tensor<1xi64>}> : (tensor<32xf32>) -> tensor<1x64x32x32xf32>
  %29 = mhlo.multiply %27, %28 : tensor<1x64x32x32xf32>
  %30 = mhlo.add %19, %29 : tensor<1x64x32x32xf32>

// CHECK:           %[[VAL_5:.*]] = "tfl.reshape"(%[[VAL_0]], %[[VAL_3]]) : (tensor<4x384x32xf32>, tensor<4xi32>) -> tensor<1x4x384x32xf32>
// CHECK:           %[[VAL_6:.*]] = "tfl.slice"(%[[VAL_5]], %[[VAL_1]], %[[VAL_2]]) : (tensor<1x4x384x32xf32>, tensor<4xi32>, tensor<4xi32>) -> tensor<1x1x384x32xf32>

  func.func @operand_as_shape(%18: tensor<i32>, %39: tensor<1x4x4x32xf32>) -> () {
    %cst_5 = arith.constant dense<512> : tensor<i32>
    %19 = "tf.Pack"(%18, %cst_5) {N = 2 : i64, T = i32, axis = 0 : i64, device = ""} : (tensor<i32>, tensor<i32>) -> tensor<2xi32>
    // CHECK: -> tensor<1x512xf32>
    %40 = "tf.Reshape"(%39, %19) {T = f32, Tshape = i32, device = ""} : (tensor<1x4x4x32xf32>, tensor<2xi32>) -> tensor<?x?xf32>
   func.return
  }