Add sentencepiece to the CI and fix tests (#8672)

* Fix the CI and tests

* Fix quality

* Remove that m form nowhere

.circleci/config.yml

@@ -77,7 +77,7 @@ jobs:
                       - v0.4-torch_and_tf-{{ checksum "setup.py" }}
                       - v0.4-{{ checksum "setup.py" }}
             - run: pip install --upgrade pip
-            - run: pip install .[sklearn,tf-cpu,torch,testing]
+            - run: pip install .[sklearn,tf-cpu,torch,testing,sentencepiece]
             - save_cache:
                 key: v0.4-{{ checksum "setup.py" }}
                 paths:
@@ -103,7 +103,7 @@ jobs:
                       - v0.4-torch-{{ checksum "setup.py" }}
                       - v0.4-{{ checksum "setup.py" }}
             - run: pip install --upgrade pip
-            - run: pip install .[sklearn,torch,testing]
+            - run: pip install .[sklearn,torch,testing,sentencepiece]
             - save_cache:
                   key: v0.4-torch-{{ checksum "setup.py" }}
                   paths:
@@ -129,7 +129,7 @@ jobs:
                       - v0.4-tf-{{ checksum "setup.py" }}
                       - v0.4-{{ checksum "setup.py" }}
             - run: pip install --upgrade pip
-            - run: pip install .[sklearn,tf-cpu,testing]
+            - run: pip install .[sklearn,tf-cpu,testing,sentencepiece]
             - save_cache:
                   key: v0.4-tf-{{ checksum "setup.py" }}
                   paths:
@@ -155,7 +155,7 @@ jobs:
                     - v0.4-flax-{{ checksum "setup.py" }}
                     - v0.4-{{ checksum "setup.py" }}
             - run: pip install --upgrade pip
-            - run: sudo pip install .[flax,sklearn,torch,testing]
+            - run: sudo pip install .[flax,sklearn,torch,testing,sentencepiece]
             - save_cache:
                   key: v0.4-flax-{{ checksum "setup.py" }}
                   paths:
@@ -181,7 +181,7 @@ jobs:
                       - v0.4-torch-{{ checksum "setup.py" }}
                       - v0.4-{{ checksum "setup.py" }}
             - run: pip install --upgrade pip
-            - run: pip install .[sklearn,torch,testing]
+            - run: pip install .[sklearn,torch,testing,sentencepiece]
             - save_cache:
                   key: v0.4-torch-{{ checksum "setup.py" }}
                   paths:
@@ -207,7 +207,7 @@ jobs:
                       - v0.4-tf-{{ checksum "setup.py" }}
                       - v0.4-{{ checksum "setup.py" }}
             - run: pip install --upgrade pip
-            - run: pip install .[sklearn,tf-cpu,testing]
+            - run: pip install .[sklearn,tf-cpu,testing,sentencepiece]
             - save_cache:
                   key: v0.4-tf-{{ checksum "setup.py" }}
                   paths:
@@ -231,7 +231,7 @@ jobs:
                       - v0.4-custom_tokenizers-{{ checksum "setup.py" }}
                       - v0.4-{{ checksum "setup.py" }}
             - run: pip install --upgrade pip
-            - run: pip install .[ja,testing]
+            - run: pip install .[ja,testing,sentencepiece]
             - run: python -m unidic download
             - save_cache:
                   key: v0.4-custom_tokenizers-{{ checksum "setup.py" }}
@@ -258,7 +258,7 @@ jobs:
                       - v0.4-torch_examples-{{ checksum "setup.py" }}
                       - v0.4-{{ checksum "setup.py" }}
             - run: pip install --upgrade pip
-            - run: pip install .[sklearn,torch,testing]
+            - run: pip install .[sklearn,torch,sentencepiece,testing]
             - run: pip install -r examples/requirements.txt
             - save_cache:
                   key: v0.4-torch_examples-{{ checksum "setup.py" }}
@@ -324,7 +324,7 @@ jobs:
                       - v0.4-{{ checksum "setup.py" }}
             - run: pip install --upgrade pip
             - run: pip install isort
-            - run: pip install .[tf,torch,flax,quality]
+            - run: pip install .[all,quality]
             - save_cache:
                   key: v0.4-code_quality-{{ checksum "setup.py" }}
                   paths:

src/transformers/models/mbart/tokenization_mbart.py

@@ -188,7 +188,7 @@ class MBartTokenizer(XLMRobertaTokenizer):
         **kwargs,
     ) -> BatchEncoding:
         if max_length is None:
-            max_length = self.max_len
+            max_length = self.model_max_length
         self.set_src_lang_special_tokens(src_lang)
         model_inputs: BatchEncoding = self(
             src_texts,

src/transformers/models/mbart/tokenization_mbart_fast.py

@@ -185,7 +185,7 @@ class MBartTokenizerFast(XLMRobertaTokenizerFast):
         **kwargs,
     ) -> BatchEncoding:
         if max_length is None:
-            max_length = self.max_len
+            max_length = self.model_max_length
         self.set_src_lang_special_tokens(src_lang)
         model_inputs: BatchEncoding = self(
             src_texts,

src/transformers/models/t5/tokenization_t5.py

@@ -309,7 +309,7 @@ class T5Tokenizer(PreTrainedTokenizer):
         **kwargs,
     ) -> BatchEncoding:
         if max_length is None:
-            max_length = self.max_len
+            max_length = self.model_max_length
         model_inputs = self(
             src_texts,
             add_special_tokens=True,

src/transformers/models/t5/tokenization_t5_fast.py

@@ -226,7 +226,7 @@ class T5TokenizerFast(PreTrainedTokenizerFast):
         **kwargs,
     ) -> BatchEncoding:
         if max_length is None:
-            max_length = self.max_len
+            max_length = self.model_max_length
         self.prefix_tokens = []
         model_inputs = self(
             src_texts,

tests/test_tokenization_mbart.py

 import tempfile
 import unittest
 
-from transformers import (
-    SPIECE_UNDERLINE,
-    AutoTokenizer,
-    BatchEncoding,
-    MBartTokenizer,
-    MBartTokenizerFast,
-    is_torch_available,
-)
+from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
 from transformers.testing_utils import (
     _sentencepiece_available,
     require_sentencepiece,
@@ -138,7 +131,7 @@ class MBartEnroIntegrationTest(unittest.TestCase):
 
     @classmethod
     def setUpClass(cls):
-        cls.tokenizer: MBartTokenizer = AutoTokenizer.from_pretrained(cls.checkpoint_name)
+        cls.tokenizer: MBartTokenizer = MBartTokenizer.from_pretrained(cls.checkpoint_name)
         cls.pad_token_id = 1
         return cls