Adding Fast tokenizers for SentencePiece based tokenizers - Breaking: remove Transfo-XL fast tokenizer (#7141)

* [WIP] SP tokenizers

* fixing tests for T5

* WIP tokenizers

* serialization

* update T5

* WIP T5 tokenization

* slow to fast conversion script

* Refactoring to move tokenzier implementations inside transformers

* Adding gpt - refactoring - quality

* WIP adding several tokenizers to the fast world

* WIP Roberta - moving implementations

* update to dev4 switch file loading to in-memory loading

* Updating and fixing

* advancing on the tokenizers - updating do_lower_case

* style and quality

* moving forward with tokenizers conversion and tests

* MBart, T5

* dumping the fast version of transformer XL

* Adding to autotokenizers + style/quality

* update init and space_between_special_tokens

* style and quality

* bump up tokenizers version

* add protobuf

* fix pickle Bert JP with Mecab

* fix newly added tokenizers

* style and quality

* fix bert japanese

* fix funnel

* limite tokenizer warning to one occurence

* clean up file

* fix new tokenizers

* fast tokenizers deep tests

* WIP adding all the special fast tests on the new fast tokenizers

* quick fix

* adding more fast tokenizers in the fast tests

* all tokenizers in fast version tested

* Adding BertGenerationFast

* bump up setup.py for CI

* remove BertGenerationFast (too early)

* bump up tokenizers version

* Clean old docstrings

* Typo

* Update following Lysandre comments

Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>
This commit is contained in:
Thomas Wolf
2020-10-08 11:32:16 +02:00
committed by GitHub
parent 4d04120c6d
commit 9aeacb58ba
60 changed files with 4663 additions and 1207 deletions

View File

@@ -19,7 +19,7 @@ import unittest
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch, slow
from transformers.tokenization_reformer import SPIECE_UNDERLINE, ReformerTokenizer
from transformers.tokenization_reformer import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from .test_tokenization_common import TokenizerTesterMixin
@@ -30,6 +30,8 @@ SAMPLE_VOCAB = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fixture
class ReformerTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer_class = ReformerTokenizer
rust_tokenizer_class = ReformerTokenizerFast
test_rust_tokenizer = True
def setUp(self):
super().setUp()
@@ -37,6 +39,28 @@ class ReformerTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
tokenizer = ReformerTokenizer(SAMPLE_VOCAB, keep_accents=True)
tokenizer.save_pretrained(self.tmpdirname)
def test_rust_and_python_full_tokenizers(self):
if not self.test_rust_tokenizer:
return
tokenizer = self.get_tokenizer()
rust_tokenizer = self.get_rust_tokenizer()
sequence = "I was born in 92000, and this is falsé."
tokens = tokenizer.tokenize(sequence)
rust_tokens = rust_tokenizer.tokenize(sequence)
self.assertListEqual(tokens, rust_tokens)
ids = tokenizer.encode(sequence, add_special_tokens=False)
rust_ids = rust_tokenizer.encode(sequence, add_special_tokens=False)
self.assertListEqual(ids, rust_ids)
rust_tokenizer = self.get_rust_tokenizer()
ids = tokenizer.encode(sequence)
rust_ids = rust_tokenizer.encode(sequence)
self.assertListEqual(ids, rust_ids)
def test_full_tokenizer(self):
tokenizer = ReformerTokenizer(SAMPLE_VOCAB, keep_accents=True)