std::vector<float> compressed_data =
              BuildSparsityParameterAttribute<float>(result.selected_block_size,
                                                     dense_data.data(), inst,
                                                     &builder, &s_param);
          auto compressed_data_type = RankedTensorType::get(
              {static_cast<int64_t>(compressed_data.size())},
              builder.getF32Type());

  func.return %0 : tensor<3x!quant.uniform<u8<1:255>:f32, 1.0>>
}

func.func @sparse_f32() -> tensor<3x2xf32> {
  // CHECK-LABEL: @sparse_f32

  func.return %0 : tensor<3x!quant.uniform<u8<1:255>:f32, 1.0>>
}

func.func @sparse_f32() -> tensor<3x2xf32> {
  // CHECK-LABEL: @sparse_f32

    return builder
        .create<tfl::SparseQConstOp>(loc, mlir::TypeAttr::get(shaped_type),
                                     dummy_value, s_param, compressed_data)
        .getOperation();
  }
  return builder
      .create<tfl::SparseConstOp>(loc, dummy_value, s_param, compressed_data)
      .getOperation();
}

StatusOr<Operation*> BuildConstOp(const tflite::TensorT& tensor,

  let arguments = (ins ElementsAttr:$value,
                   SparsityParameterAttr:$s_param,
                   ElementsAttr:$compressed_data);

  let results = (outs AnyTensor:$output);

  let builders = [
    OpBuilder<(ins "TypedAttr":$value, "SparsityParameterAttr":$s_param,
      "Attribute":$compressed_data),
    [{
      $_state.addTypes(value.getType());
      $_state.addAttribute("value", value);