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add abbreviation replacement data augmentation op and test #732

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Original file line number Diff line number Diff line change
@@ -0,0 +1,104 @@
# Copyright 2020 The Forte Authors. All Rights Reserved.
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2022*

#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.


import random
import json
from typing import Tuple, Union, Dict, Any

import requests
from forte.data.ontology import Annotation
from forte.processors.data_augment.algorithms.single_annotation_op import (
SingleAnnotationAugmentOp,
)
from forte.common.configuration import Config

__all__ = [
"AbbreviationReplacementOp",
]


class AbbreviationReplacementOp(SingleAnnotationAugmentOp):
r"""
This class is a replacement op utilizing a pre-defined
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The docstring should be more comprehensive. This is what the user is going to see if they want to use this DA op.

abbreviation to replace words.

Args:
configs:
- prob: The probability of replacement,
should fall in [0, 1].
- dict_path: the `url` or the path to the pre-defined
abbreviation json file. The key is a word / phrase we want to replace.
The value is an abbreviated word of the corresponding key.
"""

def __init__(self, configs: Union[Config, Dict[str, Any]]):
super().__init__(configs)
if "dict_path" in configs.keys():
self.dict_path = configs["dict_path"]
else:
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An if-else loop is not needed here as you are already setting a default value in the default_configs

self.dict_path = (
"https://raw.githubusercontent.com/GEM-benchmark/NL-Augmenter/"
+ "main/transformations/abbreviation_transformation/"
+ "phrase_abbrev_dict.json"
)

try:
r = requests.get(self.dict_path)
self.data = json.loads(r.text)
except requests.exceptions.RequestException:
with open(self.dict_path, encoding="utf8") as json_file:
self.data = json.load(json_file)

def single_annotation_augment(
self, input_anno: Annotation
) -> Tuple[bool, str]:
r"""
This function replaces a word from an abbreviation dictionary.
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Again, we should add a better description of what this function will do.


Args:
input_anno: The input annotation.
Returns:
A tuple, where the first element is a boolean value indicating
whether the replacement happens, and the second element is the
replaced string.
"""
# If the replacement does not happen, return False.
if random.random() > self.configs.prob:
return False, input_anno.text
if input_anno.text in self.data.keys():
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Since you are returning from the function if the program enters the earlier if statement, you dont need to add this if

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Also, I am not sure is this check (input_anno.text in self.data.keys()) is necessary.

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I was thinking if the input phrase does not have a corresponding abbreviation, an error will occur.

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  1. When checking dict existence, use text in self.data, don't need to call the keys().
  2. Now we can see that the prob only applies to the annotation that has an abbreviation, which should probably be specified in the class docstring.

result: str = self.data[input_anno.text]
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Something about this replacement:

  1. Do we need to consider the case? Maybe we should lower case your dictionary and user input.
  2. How about substrings? For example, in "see you later": "syl8r", what if we have an input "i will see you later", it looks like we won't replace this?

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Maybe you need to consider using an Aho-Corasick data sturcture here: https://pyahocorasick.readthedocs.io/en/latest/

return True, result
else:
return False, input_anno.text

@classmethod
def default_configs(cls) -> Dict[str, Any]:
r"""
Returns:
A dictionary with the default config for this processor.
Following are the keys for this dictionary:
- prob: The probability of replacement,
should fall in [0, 1]. Default value is 0.1
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The default value below is 0.5. Make sure you check the documentation thoroughly.

- dict_path: the `url` or the path to the pre-defined
abbreviation json file. The key is a word / phrase we want
to replace. The value is an abbreviated word of the
corresponding key.
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I'd recommend adding the default value of dict_path in the docstring as well since this is what will be rendered in the documentation and it would be easier for users to see.

"""
return {
"dict_path": "https://raw.githubusercontent.com/GEM-benchmark/"
+ "NL-Augmenter/main/transformations/"
+ "abbreviation_transformation/phrase_abbrev_dict.json",
"prob": 0.5,
}
Original file line number Diff line number Diff line change
@@ -0,0 +1,54 @@
# Copyright 2020 The Forte Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Unit tests for dictionary word replacement op.
"""

import unittest
from forte.data.data_pack import DataPack
from ft.onto.base_ontology import Token
from forte.processors.data_augment.algorithms.abbreviation_replacement_op import (
AbbreviationReplacementOp,
)


class TestAbbreviationReplacementOp(unittest.TestCase):
def setUp(self):
self.abre = AbbreviationReplacementOp(
configs={
"prob": 1.0,
}
)

def test_replace(self):
data_pack = DataPack()
text = "see you later"
data_pack.set_text(text)
token = Token(data_pack, 0, len(text))
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The Token class is generally used for a single word. When annotating the whole sequence, you should use the Sentence class. Also, if your SingleAnnotationOp augments an annotation other than a Token, you must specify that in the default_configs. For your reference, look at the implementation of the BackTranslationOp and its test cases. Even that Op augments sentences.

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We also have Document https://github.com/asyml/forte/blob/master/ft/onto/base_ontology.py#L136 for the whole article.

I know it is just a test case so it doesn't matter too much, but still worth noting.

data_pack.add_entry(token)

augmented_data_pack = self.abre.perform_augmentation(data_pack)

augmented_token = list(
augmented_data_pack.get("ft.onto.base_ontology.Token")
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I think you should take the comment above into consideration and rework your test cases accordingly.

)[0]

self.assertIn(
augmented_token.text,
["syl8r", "cul83r", "cul8r"],
)


if __name__ == "__main__":
unittest.main()