# Copyright NeMo (https://github.com/NVIDIA/NeMo). All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import pynini
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from fun_text_processing.text_normalization.en.graph_utils import DAMO_UPPER, GraphFst, insert_space
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from pynini.lib import pynutil
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class AbbreviationFst(GraphFst):
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"""
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Finite state transducer for classifying electronic: as URLs, email addresses, etc.
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e.g. "ABC" -> tokens { abbreviation { value: "A B C" } }
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Args:
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whitelist: whitelist FST
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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, whitelist: 'pynini.FstLike', deterministic: bool = True):
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super().__init__(name="abbreviation", kind="classify", deterministic=deterministic)
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dot = pynini.accep(".")
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# A.B.C. -> A. B. C.
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graph = DAMO_UPPER + dot + pynini.closure(insert_space + DAMO_UPPER + dot, 1)
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# A.B.C. -> A.B.C.
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graph |= DAMO_UPPER + dot + pynini.closure(DAMO_UPPER + dot, 1)
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# ABC -> A B C
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graph |= DAMO_UPPER + pynini.closure(insert_space + DAMO_UPPER, 1)
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# exclude words that are included in the whitelist
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graph = pynini.compose(
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pynini.difference(pynini.project(graph, "input"), pynini.project(whitelist.graph, "input")), graph
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)
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graph = pynutil.insert("value: \"") + graph.optimize() + pynutil.insert("\"")
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graph = self.add_tokens(graph)
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self.fst = graph.optimize()
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