Improve bert-japanese tokenizer handling (huggingface#8659)

julien-c · sgugger · web-flow · commit 0cc5ab1333c3 · 2020-11-23T11:15:02.000-05:00
* Make ci fail * Try to make tests actually run? * CI finally failing? * Fix CI * Revert "Fix CI" This reverts commit ca7923b. * Ooops wrong one * one more try * Ok ok let's move this elsewhere * Alternative to globals() (huggingface#8667) * Alternative to globals() * Error is raised later so return None * Sentencepiece not installed make some tokenizers None * Apply Lysandre wisdom * Slightly clearer comment? cc @sgugger Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
diff --git a/.circleci/config.yml b/.circleci/config.yml
@@ -221,7 +221,7 @@ jobs:
     run_tests_custom_tokenizers:
         working_directory: ~/transformers
         docker:
-            - image: circleci/python:3.6
+            - image: circleci/python:3.7
         environment:
             RUN_CUSTOM_TOKENIZERS: yes
         steps:
diff --git a/src/transformers/models/auto/tokenization_auto.py b/src/transformers/models/auto/tokenization_auto.py
@@ -185,8 +185,6 @@
         (LongformerConfig, (LongformerTokenizer, LongformerTokenizerFast)),
         (BartConfig, (BartTokenizer, BartTokenizerFast)),
         (LongformerConfig, (LongformerTokenizer, LongformerTokenizerFast)),
-        (RobertaConfig, (BertweetTokenizer, None)),
-        (RobertaConfig, (PhobertTokenizer, None)),
         (RobertaConfig, (RobertaTokenizer, RobertaTokenizerFast)),
         (ReformerConfig, (ReformerTokenizer, ReformerTokenizerFast)),
         (ElectraConfig, (ElectraTokenizer, ElectraTokenizerFast)),
@@ -195,7 +193,6 @@
         (LayoutLMConfig, (LayoutLMTokenizer, LayoutLMTokenizerFast)),
         (DPRConfig, (DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast)),
         (SqueezeBertConfig, (SqueezeBertTokenizer, SqueezeBertTokenizerFast)),
-        (BertConfig, (HerbertTokenizer, HerbertTokenizerFast)),
         (BertConfig, (BertTokenizer, BertTokenizerFast)),
         (OpenAIGPTConfig, (OpenAIGPTTokenizer, OpenAIGPTTokenizerFast)),
         (GPT2Config, (GPT2Tokenizer, GPT2TokenizerFast)),
@@ -213,13 +210,34 @@
     ]
 )
 
+# For tokenizers which are not directly mapped from a config
+NO_CONFIG_TOKENIZER = [
+    BertJapaneseTokenizer,
+    BertweetTokenizer,
+    HerbertTokenizer,
+    HerbertTokenizerFast,
+    PhobertTokenizer,
+]
+
+
 SLOW_TOKENIZER_MAPPING = {
     k: (v[0] if v[0] is not None else v[1])
     for k, v in TOKENIZER_MAPPING.items()
     if (v[0] is not None or v[1] is not None)
 }
 
 
+def tokenizer_class_from_name(class_name: str):
+    all_tokenizer_classes = (
+        [v[0] for v in TOKENIZER_MAPPING.values() if v[0] is not None]
+        + [v[1] for v in TOKENIZER_MAPPING.values() if v[1] is not None]
+        + NO_CONFIG_TOKENIZER
+    )
+    for c in all_tokenizer_classes:
+        if c.__name__ == class_name:
+            return c
+
+
 class AutoTokenizer:
     r"""
     This is a generic tokenizer class that will be instantiated as one of the tokenizer classes of the library when
@@ -307,17 +325,17 @@ def from_pretrained(cls, pretrained_model_name_or_path, *inputs, **kwargs):
         if not isinstance(config, PretrainedConfig):
             config = AutoConfig.from_pretrained(pretrained_model_name_or_path, **kwargs)
 
-        if "bert-base-japanese" in str(pretrained_model_name_or_path):
-            return BertJapaneseTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
-
         use_fast = kwargs.pop("use_fast", True)
 
         if config.tokenizer_class is not None:
+            tokenizer_class = None
             if use_fast and not config.tokenizer_class.endswith("Fast"):
                 tokenizer_class_candidate = f"{config.tokenizer_class}Fast"
-            else:
+                tokenizer_class = tokenizer_class_from_name(tokenizer_class_candidate)
+            if tokenizer_class is None:
                 tokenizer_class_candidate = config.tokenizer_class
-            tokenizer_class = globals().get(tokenizer_class_candidate)
+                tokenizer_class = tokenizer_class_from_name(tokenizer_class_candidate)
+
             if tokenizer_class is None:
                 raise ValueError(
                     "Tokenizer class {} does not exist or is not currently imported.".format(tokenizer_class_candidate)
diff --git a/tests/test_tokenization_bert_japanese.py b/tests/test_tokenization_bert_japanese.py
@@ -18,6 +18,7 @@
 import pickle
 import unittest
 
+from transformers import AutoTokenizer
 from transformers.models.bert_japanese.tokenization_bert_japanese import (
     VOCAB_FILES_NAMES,
     BertJapaneseTokenizer,
@@ -267,3 +268,11 @@ def test_sequence_builders(self):
         # 2 is for "[CLS]", 3 is for "[SEP]"
         assert encoded_sentence == [2] + text + [3]
         assert encoded_pair == [2] + text + [3] + text_2 + [3]
+
+
+@custom_tokenizers
+class AutoTokenizerCustomTest(unittest.TestCase):
+    def test_tokenizer_bert_japanese(self):
+        EXAMPLE_BERT_JAPANESE_ID = "cl-tohoku/bert-base-japanese"
+        tokenizer = AutoTokenizer.from_pretrained(EXAMPLE_BERT_JAPANESE_ID)
+        self.assertIsInstance(tokenizer, BertJapaneseTokenizer)
