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Fix sp_model_kwargs param missing at unpickle in XLMRobertaTokenizer #11430

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Apr 30, 2021
Merged

Fix sp_model_kwargs param missing at unpickle in XLMRobertaTokenizer #11430

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13 changes: 9 additions & 4 deletions src/transformers/models/xlm_roberta/tokenization_xlm_roberta.py
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Original file line number Diff line number Diff line change
Expand Up @@ -135,7 +135,7 @@ def __init__(
# Mask token behave like a normal word, i.e. include the space before it
mask_token = AddedToken(mask_token, lstrip=True, rstrip=False) if isinstance(mask_token, str) else mask_token

sp_model_kwargs = {} if sp_model_kwargs is None else sp_model_kwargs
self.sp_model_kwargs = {} if sp_model_kwargs is None else sp_model_kwargs

super().__init__(
bos_token=bos_token,
Expand All @@ -145,11 +145,11 @@ def __init__(
cls_token=cls_token,
pad_token=pad_token,
mask_token=mask_token,
sp_model_kwargs=sp_model_kwargs,
sp_model_kwargs=self.sp_model_kwargs,
**kwargs,
)

self.sp_model = spm.SentencePieceProcessor(**sp_model_kwargs)
self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs)
self.sp_model.Load(str(vocab_file))
self.vocab_file = vocab_file

Expand All @@ -175,7 +175,12 @@ def __getstate__(self):

def __setstate__(self, d):
self.__dict__ = d
self.sp_model = spm.SentencePieceProcessor()

# for backward compatibility
if not hasattr(self, "sp_model_kwargs"):
self.sp_model_kwargs = {}

self.sp_model = spm.SentencePieceProcessor(**self.sp_model_kwargs)
self.sp_model.Load(self.vocab_file)

def build_inputs_with_special_tokens(
Expand Down
13 changes: 13 additions & 0 deletions tests/test_tokenization_xlm_roberta.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@

import itertools
import os
import pickle
import unittest

from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
Expand Down Expand Up @@ -142,6 +143,18 @@ def test_subword_regularization_tokenizer(self):

self.assertFalse(all_equal)

def test_pickle_subword_regularization_tokenizer(self):
"""Google pickle __getstate__ __setstate__ if you are struggling with this."""
# Subword regularization is only available for the slow tokenizer.
sp_model_kwargs = {"enable_sampling": True, "alpha": 0.1, "nbest_size": -1}
tokenizer = XLMRobertaTokenizer(SAMPLE_VOCAB, keep_accents=True, sp_model_kwargs=sp_model_kwargs)
tokenizer_bin = pickle.dumps(tokenizer)
tokenizer_new = pickle.loads(tokenizer_bin)

self.assertIsNotNone(tokenizer_new.sp_model_kwargs)
self.assertTrue(isinstance(tokenizer_new.sp_model_kwargs, dict))
self.assertEqual(tokenizer_new.sp_model_kwargs, sp_model_kwargs)

@cached_property
def big_tokenizer(self):
return XLMRobertaTokenizer.from_pretrained("xlm-roberta-base")
Expand Down