File size: 10,719 Bytes
2216aae | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 | # Generated content DO NOT EDIT
class Trainer:
"""
Base class for all trainers
This class is not supposed to be instantiated directly. Instead, any implementation of a
Trainer will return an instance of this class when instantiated.
"""
def __getstate__(self):
""" """
pass
def __setstate__(self, state):
""" """
pass
class BpeTrainer(Trainer):
"""
Trainer capable of training a BPE model
Args:
vocab_size (:obj:`int`, `optional`):
The size of the final vocabulary, including all tokens and alphabet.
min_frequency (:obj:`int`, `optional`):
The minimum frequency a pair should have in order to be merged.
show_progress (:obj:`bool`, `optional`):
Whether to show progress bars while training.
special_tokens (:obj:`List[Union[str, AddedToken]]`, `optional`):
A list of special tokens the model should know of.
limit_alphabet (:obj:`int`, `optional`):
The maximum different characters to keep in the alphabet.
initial_alphabet (:obj:`List[str]`, `optional`):
A list of characters to include in the initial alphabet, even
if not seen in the training dataset.
If the strings contain more than one character, only the first one
is kept.
continuing_subword_prefix (:obj:`str`, `optional`):
A prefix to be used for every subword that is not a beginning-of-word.
end_of_word_suffix (:obj:`str`, `optional`):
A suffix to be used for every subword that is a end-of-word.
max_token_length (:obj:`int`, `optional`):
Prevents creating tokens longer than the specified size.
This can help with reducing polluting your vocabulary with
highly repetitive tokens like `======` for wikipedia
"""
def __init__(
self,
vocab_size=30000,
min_frequency=0,
show_progress=True,
special_tokens=[],
limit_alphabet=None,
initial_alphabet=[],
continuing_subword_prefix=None,
end_of_word_suffix=None,
max_token_length=None,
words={},
):
pass
def __getstate__(self):
""" """
pass
def __setstate__(self, state):
""" """
pass
@property
def continuing_subword_prefix(self):
""" """
pass
@continuing_subword_prefix.setter
def continuing_subword_prefix(self, value):
""" """
pass
@property
def end_of_word_suffix(self):
""" """
pass
@end_of_word_suffix.setter
def end_of_word_suffix(self, value):
""" """
pass
@property
def initial_alphabet(self):
""" """
pass
@initial_alphabet.setter
def initial_alphabet(self, value):
""" """
pass
@property
def limit_alphabet(self):
""" """
pass
@limit_alphabet.setter
def limit_alphabet(self, value):
""" """
pass
@property
def max_token_length(self):
""" """
pass
@max_token_length.setter
def max_token_length(self, value):
""" """
pass
@property
def min_frequency(self):
""" """
pass
@min_frequency.setter
def min_frequency(self, value):
""" """
pass
@property
def show_progress(self):
""" """
pass
@show_progress.setter
def show_progress(self, value):
""" """
pass
@property
def special_tokens(self):
""" """
pass
@special_tokens.setter
def special_tokens(self, value):
""" """
pass
@property
def vocab_size(self):
""" """
pass
@vocab_size.setter
def vocab_size(self, value):
""" """
pass
class UnigramTrainer(Trainer):
"""
Trainer capable of training a Unigram model
Args:
vocab_size (:obj:`int`):
The size of the final vocabulary, including all tokens and alphabet.
show_progress (:obj:`bool`):
Whether to show progress bars while training.
special_tokens (:obj:`List[Union[str, AddedToken]]`):
A list of special tokens the model should know of.
initial_alphabet (:obj:`List[str]`):
A list of characters to include in the initial alphabet, even
if not seen in the training dataset.
If the strings contain more than one character, only the first one
is kept.
shrinking_factor (:obj:`float`):
The shrinking factor used at each step of the training to prune the
vocabulary.
unk_token (:obj:`str`):
The token used for out-of-vocabulary tokens.
max_piece_length (:obj:`int`):
The maximum length of a given token.
n_sub_iterations (:obj:`int`):
The number of iterations of the EM algorithm to perform before
pruning the vocabulary.
"""
def __init__(
self,
vocab_size=8000,
show_progress=True,
special_tokens=[],
initial_alphabet=[],
shrinking_factor=0.75,
unk_token=None,
max_piece_length=16,
n_sub_iterations=2,
):
pass
def __getstate__(self):
""" """
pass
def __setstate__(self, state):
""" """
pass
@property
def initial_alphabet(self):
""" """
pass
@initial_alphabet.setter
def initial_alphabet(self, value):
""" """
pass
@property
def show_progress(self):
""" """
pass
@show_progress.setter
def show_progress(self, value):
""" """
pass
@property
def special_tokens(self):
""" """
pass
@special_tokens.setter
def special_tokens(self, value):
""" """
pass
@property
def vocab_size(self):
""" """
pass
@vocab_size.setter
def vocab_size(self, value):
""" """
pass
class WordLevelTrainer(Trainer):
"""
Trainer capable of training a WorldLevel model
Args:
vocab_size (:obj:`int`, `optional`):
The size of the final vocabulary, including all tokens and alphabet.
min_frequency (:obj:`int`, `optional`):
The minimum frequency a pair should have in order to be merged.
show_progress (:obj:`bool`, `optional`):
Whether to show progress bars while training.
special_tokens (:obj:`List[Union[str, AddedToken]]`):
A list of special tokens the model should know of.
"""
def __init__(self, vocab_size=30000, min_frequency=0, show_progress=True, special_tokens=[]):
pass
def __getstate__(self):
""" """
pass
def __setstate__(self, state):
""" """
pass
@property
def min_frequency(self):
""" """
pass
@min_frequency.setter
def min_frequency(self, value):
""" """
pass
@property
def show_progress(self):
""" """
pass
@show_progress.setter
def show_progress(self, value):
""" """
pass
@property
def special_tokens(self):
""" """
pass
@special_tokens.setter
def special_tokens(self, value):
""" """
pass
@property
def vocab_size(self):
""" """
pass
@vocab_size.setter
def vocab_size(self, value):
""" """
pass
class WordPieceTrainer(Trainer):
"""
Trainer capable of training a WordPiece model
Args:
vocab_size (:obj:`int`, `optional`):
The size of the final vocabulary, including all tokens and alphabet.
min_frequency (:obj:`int`, `optional`):
The minimum frequency a pair should have in order to be merged.
show_progress (:obj:`bool`, `optional`):
Whether to show progress bars while training.
special_tokens (:obj:`List[Union[str, AddedToken]]`, `optional`):
A list of special tokens the model should know of.
limit_alphabet (:obj:`int`, `optional`):
The maximum different characters to keep in the alphabet.
initial_alphabet (:obj:`List[str]`, `optional`):
A list of characters to include in the initial alphabet, even
if not seen in the training dataset.
If the strings contain more than one character, only the first one
is kept.
continuing_subword_prefix (:obj:`str`, `optional`):
A prefix to be used for every subword that is not a beginning-of-word.
end_of_word_suffix (:obj:`str`, `optional`):
A suffix to be used for every subword that is a end-of-word.
"""
def __init__(
self,
vocab_size=30000,
min_frequency=0,
show_progress=True,
special_tokens=[],
limit_alphabet=None,
initial_alphabet=[],
continuing_subword_prefix="##",
end_of_word_suffix=None,
):
pass
def __getstate__(self):
""" """
pass
def __setstate__(self, state):
""" """
pass
@property
def continuing_subword_prefix(self):
""" """
pass
@continuing_subword_prefix.setter
def continuing_subword_prefix(self, value):
""" """
pass
@property
def end_of_word_suffix(self):
""" """
pass
@end_of_word_suffix.setter
def end_of_word_suffix(self, value):
""" """
pass
@property
def initial_alphabet(self):
""" """
pass
@initial_alphabet.setter
def initial_alphabet(self, value):
""" """
pass
@property
def limit_alphabet(self):
""" """
pass
@limit_alphabet.setter
def limit_alphabet(self, value):
""" """
pass
@property
def min_frequency(self):
""" """
pass
@min_frequency.setter
def min_frequency(self, value):
""" """
pass
@property
def show_progress(self):
""" """
pass
@show_progress.setter
def show_progress(self, value):
""" """
pass
@property
def special_tokens(self):
""" """
pass
@special_tokens.setter
def special_tokens(self, value):
""" """
pass
@property
def vocab_size(self):
""" """
pass
@vocab_size.setter
def vocab_size(self, value):
""" """
pass
|