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import sys
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from unicodedata import category
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import pynini
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from fun_text_processing.text_normalization.en.graph_utils import DAMO_NOT_SPACE, DAMO_SIGMA, GraphFst
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from fun_text_processing.text_normalization.en.utils import get_abs_path, load_labels
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from pynini.examples import plurals
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from pynini.lib import pynutil
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class PunctuationFst(GraphFst):
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"""
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Finite state transducer for classifying punctuation
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e.g. a, -> tokens { name: "a" } tokens { name: "," }
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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="punctuation", kind="classify", deterministic=deterministic)
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s = "!#%&\'()*+,-./:;<=>?@^_`{|}~\""
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punct_symbols_to_exclude = ["[", "]"]
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punct_unicode = [
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chr(i)
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for i in range(sys.maxunicode)
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if category(chr(i)).startswith("P") and chr(i) not in punct_symbols_to_exclude
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]
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whitelist_symbols = load_labels(get_abs_path("data/whitelist/symbol.tsv"))
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whitelist_symbols = [x[0] for x in whitelist_symbols]
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self.punct_marks = [p for p in punct_unicode + list(s) if p not in whitelist_symbols]
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punct = pynini.union(*self.punct_marks)
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punct = pynini.closure(punct, 1)
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emphasis = (
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pynini.accep("<")
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+ (
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(pynini.closure(DAMO_NOT_SPACE - pynini.union("<", ">"), 1) + pynini.closure(pynini.accep("/"), 0, 1))
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| (pynini.accep("/") + pynini.closure(DAMO_NOT_SPACE - pynini.union("<", ">"), 1))
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)
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+ pynini.accep(">")
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)
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punct = plurals._priority_union(emphasis, punct, DAMO_SIGMA)
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self.graph = punct
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self.fst = (pynutil.insert("name: \"") + self.graph + pynutil.insert("\"")).optimize()
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