import os
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import pynini
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from fun_text_processing.text_normalization.en.graph_utils import (
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GraphFst,
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delete_extra_space,
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delete_space,
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generator_main,
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)
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from fun_text_processing.text_normalization.en.verbalizers.word import WordFst
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from fun_text_processing.text_normalization.es.verbalizers.verbalize import VerbalizeFst
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from pynini.lib import pynutil
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import logging
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class VerbalizeFinalFst(GraphFst):
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"""
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Finite state transducer that verbalizes an entire sentence
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Args:
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deterministic: if True will provide a single transduction option,
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for False multiple options (used for audio-based normalization)
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cache_dir: path to a dir with .far grammar file. Set to None to avoid using cache.
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overwrite_cache: set to True to overwrite .far files
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"""
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def __init__(
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self, deterministic: bool = True, cache_dir: str = None, overwrite_cache: bool = False
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):
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super().__init__(name="verbalize_final", kind="verbalize", deterministic=deterministic)
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far_file = None
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if cache_dir is not None and cache_dir != "None":
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os.makedirs(cache_dir, exist_ok=True)
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far_file = os.path.join(
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cache_dir, f"es_tn_{deterministic}_deterministic_verbalizer.far"
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)
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if not overwrite_cache and far_file and os.path.exists(far_file):
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self.fst = pynini.Far(far_file, mode="r")["verbalize"]
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logging.info(f"VerbalizeFinalFst graph was restored from {far_file}.")
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else:
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verbalize = VerbalizeFst(deterministic=deterministic).fst
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word = WordFst(deterministic=deterministic).fst
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types = verbalize | word
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graph = (
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pynutil.delete("tokens")
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+ delete_space
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+ pynutil.delete("{")
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+ delete_space
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+ types
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+ delete_space
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+ pynutil.delete("}")
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)
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graph = delete_space + pynini.closure(graph + delete_extra_space) + graph + delete_space
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self.fst = graph.optimize()
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if far_file:
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generator_main(far_file, {"verbalize": self.fst})
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logging.info(f"VerbalizeFinalFst grammars are saved to {far_file}.")
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