text: # Copyright (c) 2021, NVIDIA CORPORATION.  All rights reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  from inverse_text_normalization.gu.data_loader_utils import get_abs_path
  from inverse_text_normalization.gu.graph_utils import NEMO_CHAR, GraphFst
  
  # from inverse_text_normalization.lang_params import LANG
  # data_path = f'inverse_text_normalization/data/{LANG}_data/'
  data_path = 'data/'
  
  try:
      import pynini
      from pynini.lib import pynutil
  
      PYNINI_AVAILABLE = True
  except (ImportError, ModuleNotFoundError):
      PYNINI_AVAILABLE = False
  
  
  class OrdinalFst(GraphFst):
      """
      Finite state transducer for classifying ordinal
          e.g. thirteenth -> ordinal { integer: "13" }
  
      Args:
          cardinal: Cardinal GraphFST
      """
  
      def __init__(self, cardinal: GraphFst):
          super().__init__(name="ordinal", kind="classify")
  
          cardinal_graph = cardinal.graph_no_exception
          graph_digit = pynini.string_file(get_abs_path(data_path+"ordinals/digit.tsv"))
          graph_teens = pynini.string_file(get_abs_path(data_path+"ordinals/teen.tsv"))
          # change to General UTF8
          graph = pynini.closure(NEMO_CHAR) + pynini.union(
              graph_digit, graph_teens, pynini.cross("tieth", "ty"), pynini.cross("th", "")
          )
  
          self.graph = graph @ cardinal_graph
          final_graph = pynutil.insert("integer: \"") + self.graph + pynutil.insert("\"")
          final_graph = self.add_tokens(final_graph)
          self.fst = final_graph.optimize()
  