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import pynini
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from fun_text_processing.text_normalization.en.graph_utils import DAMO_NOT_QUOTE, GraphFst
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from fun_text_processing.text_normalization.en.verbalizers.ordinal import OrdinalFst
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from pynini.lib import pynutil
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class RomanFst(GraphFst):
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"""
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Finite state transducer for verbalizing roman numerals
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e.g. tokens { roman { integer: "one" } } -> one
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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 transduction are generated (used for audio-based normalization)
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"""
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def __init__(self, deterministic: bool = True):
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super().__init__(name="roman", kind="verbalize", deterministic=deterministic)
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suffix = OrdinalFst().suffix
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cardinal = pynini.closure(DAMO_NOT_QUOTE)
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ordinal = pynini.compose(cardinal, suffix)
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graph = (
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pynutil.delete("key_cardinal: \"")
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+ pynini.closure(DAMO_NOT_QUOTE, 1)
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+ pynutil.delete("\"")
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+ pynini.accep(" ")
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+ pynutil.delete("integer: \"")
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+ cardinal
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+ pynutil.delete("\"")
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).optimize()
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graph |= (
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pynutil.delete("default_cardinal: \"default\" integer: \"") + cardinal + pynutil.delete("\"")
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).optimize()
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graph |= (
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pynutil.delete("default_ordinal: \"default\" integer: \"") + ordinal + pynutil.delete("\"")
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).optimize()
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graph |= (
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pynutil.delete("key_the_ordinal: \"")
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+ pynini.closure(DAMO_NOT_QUOTE, 1)
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+ pynutil.delete("\"")
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+ pynini.accep(" ")
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+ pynutil.delete("integer: \"")
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+ pynini.closure(pynutil.insert("the "), 0, 1)
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+ ordinal
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+ pynutil.delete("\"")
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).optimize()
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delete_tokens = self.delete_tokens(graph)
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self.fst = delete_tokens.optimize()
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