// CHECK: %{{.*}} = stablehlo.custom_call @tf.ResizeBilinear(%arg0, %{{.*}}) {align_corners = false, device = "", half_pixel_centers = true} : (tensor<1x32x32x128xf32>, tensor<2xi32>) -> tensor<1x64x64x128xf32>
      // CHECK-OPT: %{{.*}} = stablehlo.custom_call @tf.ResizeBilinear(%arg0, %cst) {align_corners = false, device = "", half_pixel_centers = true} : (tensor<1x32x32x128xf32>, tensor<2xi32>) -> tensor<1x64x64x128xf32>
      %1 = "tf.ResizeBilinear"(%arg0, %0) {

      %c = stablehlo.constant dense<40> : tensor<2xi32>
      %0 = "tf.UnconvertedOp"(%arg0, %c) {align_corners = false, half_pixel_centers = false} : (tensor<1x20x20x28xf32>, tensor<2xi32>) -> tensor<1x40x40x28xf32>
      func.return %0 : tensor<1x40x40x28xf32>
  }

    operand_layouts = #vhlo.array_v1<[]>,
    output_operand_aliases = #vhlo.array_v1<[]>,
    result_layouts = #vhlo.array_v1<[]>}> {align_corners = #vhlo.bool_v1<true>, device = #vhlo.string_v1<"">, half_pixel_centers = #vhlo.bool_v1<false>} : (tensor<1x320x1x1xf32>, tensor<2xi32>) -> tensor<1x1600x1x1xf32>
  return %0 : tensor<1x1600x1x1xf32>
}

namespace {

// Convert op to stablehlo.custom_call
//   "tf.ResizeBilinear"(%341, %138) {
//      align_corners = false, device = "", half_pixel_centers = true}
//   ==>
//   stablehlo.custom_call @tf.ResizeBilinear(%arg0, %arg1) {
//      align_corners = false, device = "", half_pixel_centers = true}
LogicalResult SmuggleOp(Operation* op, PatternRewriter& rewriter) {
  auto call_target =

  (TF_ResizeBilinearOp $images, $size, $align_corners, $half_pixel_centers),
  (TFL_ResizeBilinearOp $images, $size, $align_corners, $half_pixel_centers)>;
def LegalizeResizeNearestNeighbor : Pat<
  (TF_ResizeNearestNeighborOp $images, $size, $align_corners,
    $half_pixel_centers),
  (TFL_ResizeNearestNeighborOp $images, $size, $align_corners,
    $half_pixel_centers)>;

// CHECK-DAG:           %[[VAL_3:.*]] = arith.constant dense<32> : tensor<2xi32>
// CHECK-DAG:           %[[VAL_4:.*]] = "tfl.resize_bilinear"(%[[VAL_2]], %[[VAL_3]]) <{align_corners = false, half_pixel_centers = true}> : (tensor<1x16x16x64xf32>, tensor<2xi32>) -> tensor<1x32x32x64xf32>
// CHECK-DAG:           %[[VAL_5:.*]] = arith.constant dense<[0, 3, 1, 2]> : tensor<4xi32>

}

table ResizeBilinearOptions {
  new_height: int (deprecated);
  new_width: int (deprecated);
  align_corners: bool;
  half_pixel_centers: bool;
}

table ResizeNearestNeighborOptions {
  align_corners: bool;
  half_pixel_centers: bool;
}

// A call operation options
table CallOptions {
  // The subgraph index that needs to be called.
  subgraph:uint;
}

}

table ResizeBilinearOptions {
  new_height: int (deprecated);
  new_width: int (deprecated);
  align_corners: bool;
  half_pixel_centers: bool;
}

table ResizeNearestNeighborOptions {
  align_corners: bool;
  half_pixel_centers: bool;
}

// A call operation options
table CallOptions {
  // The subgraph index that needs to be called.
  subgraph:uint;
}

  // CHECK: "tfl.resize_bilinear"(%arg0, %arg1) <{align_corners = true, half_pixel_centers = false}> : (tensor<1x100x100x3xf32>, tensor<4xi32>) -> tensor<?xf32>
}

func.func @resize_with_bilinear_with_half_pixel_centers(%arg0: tensor<1x100x100x3xf32>, %arg1: tensor<4xi32>) -> tensor<?xf32> {
  %0 = "tf.ResizeBilinear"(%arg0, %arg1) {align_corners = false, half_pixel_centers = true} : (tensor<1x100x100x3xf32>, tensor<4xi32>) -> tensor<?xf32>

                                  rewriter.getI32Type()),
            output_sizes));
    // The value of half_pixel_centers couldn't be inferred from the IR and XLA
    // only support half_pixel_centers=True as in 01/11/2022. Here
    // half_pixel_centers=False is hardcoded.
    Value output = rewriter.create<TF::ResizeBilinearOp>(
        conv_op.getLoc(), conv_op.getType(), conv_op.getLhs(),