text: # Copyright (c) 2021, NVIDIA CORPORATION.  All rights reserved.
  # Copyright 2015 and onwards Google, Inc.
  #
  # 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 nemo_text_processing.text_normalization.data_loader_utils import get_abs_path, load_labels
  from nemo_text_processing.text_normalization.graph_utils import GraphFst, convert_space
  
  try:
      import pynini
      from pynini.lib import pynutil
  
      PYNINI_AVAILABLE = True
  except (ModuleNotFoundError, ImportError):
      PYNINI_AVAILABLE = False
  
  
  class WhiteListFst(GraphFst):
      """
      Finite state transducer for classifying whitelist, e.g.
          misses -> tokens { name: "mrs" }
      This class has highest priority among all classifier grammars. Whitelisted tokens are defined and loaded from "data/whitelist.tsv".
  
      Args:
          input_case: accepting either "lower_cased" or "cased" input.
      """
  
      def __init__(self, input_case: str):
          super().__init__(name="whitelist", kind="classify")
  
          whitelist = load_labels(get_abs_path("data/whitelist.tsv"))
          if input_case == "lower_cased":
              whitelist = [(x.lower(), y) for x, y in whitelist]
          else:
              whitelist = [(x, y) for x, y in whitelist]
  
          graph = pynini.string_map(whitelist)
  
          graph = pynutil.insert("name: \"") + convert_space(graph) + pynutil.insert("\"")
          self.fst = graph.optimize()
  