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e4b9a7b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 | # -*- coding: utf-8 -*-
# SPDX-FileCopyrightText: 2016-2025 PyThaiNLP Project
# SPDX-FileType: SOURCE
# SPDX-License-Identifier: Apache-2.0
import pickle
import unittest
import fastai
import pandas as pd
import torch
from fastai.text import *
from pythainlp.tokenize import THAI2FIT_TOKENIZER
from pythainlp.ulmfit import (
THWIKI_LSTM,
ThaiTokenizer,
document_vector,
merge_wgts,
post_rules_th,
post_rules_th_sparse,
pre_rules_th,
pre_rules_th_sparse,
process_thai,
)
from pythainlp.ulmfit.preprocess import (
fix_html,
lowercase_all,
remove_space,
replace_rep_after,
replace_rep_nonum,
replace_url,
replace_wrep_post,
replace_wrep_post_nonum,
rm_brackets,
rm_useless_newlines,
rm_useless_spaces,
spec_add_spaces,
ungroup_emoji,
)
from pythainlp.ulmfit.tokenizer import BaseTokenizer as base_tokenizer
class UlmfitTestCaseX(unittest.TestCase):
def test_ThaiTokenizer(self):
self.thai = ThaiTokenizer()
self.assertIsNotNone(self.thai.tokenizer("ทดสอบการตัดคำ"))
self.assertIsNone(self.thai.add_special_cases(["แมว"]))
def test_BaseTokenizer(self):
self.base = base_tokenizer(lang="th")
self.assertIsNotNone(self.base.tokenizer("ทดสอบ การ ตัด คำ"))
self.assertIsNone(self.base.add_special_cases(["แมว"]))
def test_load_pretrained(self):
self.assertIsNotNone(THWIKI_LSTM)
def test_pre_rules_th(self):
self.assertIsNotNone(pre_rules_th)
def test_post_rules_th(self):
self.assertIsNotNone(post_rules_th)
def test_pre_rules_th_sparse(self):
self.assertIsNotNone(pre_rules_th_sparse)
def test_post_rules_th_sparse(self):
self.assertIsNotNone(post_rules_th_sparse)
def test_fix_html(self):
self.assertEqual(
fix_html("Some HTML text<br />"), "Some HTML& text\n"
)
def test_rm_useless_spaces(self):
self.assertEqual(
rm_useless_spaces("Inconsistent use of spaces."),
"Inconsistent use of spaces.",
)
def test_spec_add_spaces(self):
self.assertEqual(
spec_add_spaces("I #like to #put #hashtags #everywhere!"),
"I # like to # put # hashtags # everywhere!",
)
def test_replace_rep_after(self):
self.assertEqual(replace_rep_after("น้อยยยยยยยย"), "น้อยxxrep8 ")
def test_replace_rep_nonum(self):
self.assertEqual(replace_rep_nonum("น้อยยยยยยยย"), "น้อย xxrep ")
def test_replace_wrep_post(self):
self.assertEqual(
replace_wrep_post(["น้อย", "น้อย"]), ["xxwrep", "1", "น้อย"]
)
self.assertEqual(
replace_wrep_post(["นก", "กา", "กา", "กา"]),
["นก", "xxwrep", "2", "กา"],
)
def test_replace_wrep_post_nonum(self):
self.assertEqual(
replace_wrep_post_nonum(["น้อย", "น้อย"]), ["xxwrep", "น้อย"]
)
self.assertEqual(
replace_wrep_post_nonum(["นก", "กา", "กา", "กา"]),
["นก", "xxwrep", "กา"],
)
def test_remove_space(self):
self.assertEqual(remove_space([" ", "น้อย", " ", "."]), ["น้อย", "."])
def test_replace_url(self):
self.assertEqual(replace_url("https://thainlp.org web"), "xxurl web")
def test_rm_useless_newlines(self):
self.assertEqual(rm_useless_newlines("text\n\n"), "text ")
def test_rm_brackets(self):
self.assertEqual(rm_brackets("()()(ข้อความ)"), "(ข้อความ)")
self.assertEqual(rm_brackets("[][][ข้อความ]"), "[ข้อความ]")
self.assertEqual(rm_brackets("{}{}{ข้อความ}"), "{ข้อความ}")
def test_ungroup_emoji(self):
self.assertEqual(ungroup_emoji("👍👍👍"), ["👍", "👍", "👍"])
def test_lowercase_all(self):
self.assertEqual(
lowercase_all("HeLlO ."), ["h", "e", "l", "l", "o", " ", "."]
)
def test_process_thai_sparse(self):
text = "👍👍👍 #AnA มากกกก น้อยน้อย ().1146"
actual = process_thai(text)
# after pre_rules_th_sparse
# >>> "👍👍👍 # Ana มาก xxrep น้้อยน้อย .1146"
#
# after tokenize with word_tokenize(engine="newmm")
# >>> ["👍👍👍", " ", "#", " ","Ana", " ", "มาก", "xxrep",
# " ", "น้อย", "น้อย", " ", ".", "1146"]
#
# after post_rules_th
# - remove whitespace token (" ")
# >>> ["xxwrep, "👍", "#", "ana", "มาก",
# "xxrep", "xxwrep", "น้อย", ".", "1146"]
expect = [
"xxwrep",
"👍",
"#",
"ana",
"มาก",
"xxrep",
"xxwrep",
"น้อย",
".",
"1146",
]
self.assertEqual(actual, expect)
def test_process_thai_dense(self):
text = "👍👍👍 #AnA มากกกก น้อยน้อย ().1146"
actual = process_thai(
text,
pre_rules=pre_rules_th,
post_rules=post_rules_th,
tok_func=THAI2FIT_TOKENIZER.word_tokenize,
)
# after pre_rules_th
# >>> "👍👍👍 # Ana มากxxrep4 น้้อยน้อย .1146"
#
# after tokenize with word_tokenize(engine="newmm")
# >>> ["👍👍👍", " ", "#", "Ana", " ", "มาก", "xxrep", "4",
# " ", "น้อย", "น้อย", " ", ".", "1146"]
# after post_rules_th
# -- because it performs `replace_wrep_post` before `ungroup_emoji`,
# 3 repetitive emoji are not marked with special token "xxwrep num"
#
# >>> ["👍", "👍","👍", " ", "#", "ana", " ", "มาก",
# "xxrep", "4", " ", "xxwrep", "1", "น้อย", " ",
# ".", "1146"]
expect = [
"👍",
"👍",
"👍",
" ",
"#",
" ",
"ana",
" ",
"มาก",
"xxrep",
"4",
" ",
"xxwrep",
"1",
"น้อย",
" ",
".",
"1146",
]
self.assertEqual(actual, expect)
def test_document_vector(self):
imdb = untar_data(URLs.IMDB_SAMPLE)
dummy_df = pd.read_csv(imdb / "texts.csv")
thwiki = THWIKI_LSTM
thwiki_itos = pickle.load(open(thwiki["itos_fname"], "rb"))
thwiki_vocab = fastai.text.transform.Vocab(thwiki_itos)
tt = Tokenizer(
tok_func=ThaiTokenizer,
lang="th",
pre_rules=pre_rules_th,
post_rules=post_rules_th,
)
processor = [
TokenizeProcessor(
tokenizer=tt, chunksize=10000, mark_fields=False
),
NumericalizeProcessor(
vocab=thwiki_vocab, max_vocab=60000, min_freq=3
),
]
data_lm = (
TextList.from_df(
dummy_df, imdb, cols=["text"], processor=processor
)
.split_by_rand_pct(0.2)
.label_for_lm()
.databunch(bs=64)
)
data_lm.sanity_check()
config = {
"emb_sz": 400,
"n_hid": 1550,
"n_layers": 4,
"pad_token": 1,
"qrnn": False,
"tie_weights": True,
"out_bias": True,
"output_p": 0.25,
"hidden_p": 0.1,
"input_p": 0.2,
"embed_p": 0.02,
"weight_p": 0.15,
}
trn_args = {"drop_mult": 0.9, "clip": 0.12, "alpha": 2, "beta": 1}
learn = language_model_learner(
data_lm, AWD_LSTM, config=config, pretrained=False, **trn_args
)
learn.load_pretrained(**thwiki)
self.assertIsNotNone(document_vector("วันนี้วันดีปีใหม่", learn, data_lm))
self.assertIsNotNone(
document_vector("วันนี้วันดีปีใหม่", learn, data_lm, agg="sum")
)
with self.assertRaises(ValueError):
document_vector("วันนี้วันดีปีใหม่", learn, data_lm, agg="abc")
def test_merge_wgts(self):
wgts = {"0.encoder.weight": torch.randn(5, 3)}
itos_pre = ["แมว", "คน", "หนู"]
itos_new = ["ปลา", "เต่า", "นก"]
em_sz = 3
self.assertIsNotNone(merge_wgts(em_sz, wgts, itos_pre, itos_new))
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