# 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_NOT_QUOTE, GraphFst
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from fun_text_processing.text_normalization.es.graph_utils import (
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add_cardinal_apocope_fem,
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shift_cardinal_gender,
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strip_cardinal_apocope,
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)
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from pynini.lib import pynutil
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class CardinalFst(GraphFst):
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"""
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Finite state transducer for verbalizing cardinals
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e.g. cardinal { integer: "dos" } -> "dos"
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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="cardinal", kind="verbalize", deterministic=deterministic)
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optional_sign = pynini.closure(pynini.cross("negative: \"true\" ", "menos "), 0, 1)
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self.optional_sign = optional_sign
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integer = pynini.closure(DAMO_NOT_QUOTE, 1)
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self.integer = pynutil.delete(" \"") + integer + pynutil.delete("\"")
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integer = pynutil.delete("integer:") + self.integer
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graph_masc = optional_sign + integer
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graph_fem = shift_cardinal_gender(graph_masc)
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self.graph_masc = pynini.optimize(graph_masc)
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self.graph_fem = pynini.optimize(graph_fem)
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# Adding adjustment for fem gender (choice of gender will be random)
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graph = graph_masc | graph_fem
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if not deterministic:
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# For alternate renderings when apocope is omitted (i.e. cardinal stands alone)
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graph |= strip_cardinal_apocope(graph_masc)
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# "una" will drop to "un" in unique contexts
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graph |= add_cardinal_apocope_fem(graph_fem)
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delete_tokens = self.delete_tokens(graph)
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self.fst = delete_tokens.optimize()
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