[Patch-t5-tokenizer] Patches the changes on T5 to make sure previous behaviour is still valide for beginning of words (#24622)

* patch `_tokenize` function

* more tests

* properly fix

* fixup

* Update src/transformers/models/t5/tokenization_t5.py

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* fix without ifs

* update

* protect import

* add python processing

* is first needed

* add doc and update with lefacy

* updaate

* fix T5 SPM converter

* styling

* fix T5 warning

* add is_seqio_available

* remove is_first

* revert some changes

* more tests and update

* update llama test batterie

* fixup

* refactor T5 spm common tests

* draft the llama tests

* update

* uopdate test

* nits

* refine

* name nit

* fix t5 tests

* fix T5

* update

* revert convert slow to fast changes that fail lots of tests

* legacy support

* fixup

* nits is first not defined

* don't use legacy behaviour for switch transformers

* style

* My attempt to check.

* nits

* fixes

* update

* fixup

* Apply suggestions from code review

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* updates

* fixup

* add legacy warning

* fixup

* warning_once nit

* update t5 documentation test

* update llama tok documentation

* add space to warning

* nits

* nit

* Apply suggestions from code review

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* last nits

---------

Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

tests/models/llama/test_tokenization_llama.py

@@ -498,3 +498,89 @@ class LlamaIntegrationTest(unittest.TestCase):
                 decoded2 = rust_tokenizer.decode(encoded2, skip_special_tokens=True)
 
                 self.assertEqual(decoded1, decoded2)
+
+
+@require_sentencepiece
+@require_tokenizers
+class CommonSpmIntegrationTests(unittest.TestCase):
+    """
+    A class that regroups important test to make sure that we properly handle the special tokens.
+    """
+
+    @classmethod
+    def setUpClass(cls):
+        tokenizer = LlamaTokenizer(SAMPLE_VOCAB, extra_ids=0, add_bos_token=False, legacy=False)
+        tokenizer.add_special_tokens({"additional_special_tokens": ["<s>"]})
+        tokenizer._create_trie(tokenizer.all_special_tokens)
+        # TODO ArthurZ the above is necessary as addedTokens / intialization sucks. Trie is not correctly created
+        # So the extra ids are split....
+        cls.tokenizer = tokenizer
+        return cls
+
+    def test_add_dummy_prefix(self):
+        # make sure `'▁'` is prepended, and outputs match sp_model's
+        # `sentencepiece.NormalizerSpec.add_dummy_prefix` attribute
+        input_ids = self.tokenizer.encode(". Hello")
+        self.assertEqual(input_ids, [7, 4, 156, 86, 20])
+        sp_encode = self.tokenizer.sp_model.encode(". Hello")
+        self.assertEqual(input_ids, sp_encode)
+        tokens = self.tokenizer.tokenize(". Hello")
+        self.assertEqual(tokens, ["▁", ".", "▁He", "ll", "o"])
+
+    def test_remove_extra_whitespaces(self):
+        # make sure the extra spaces are eaten. Since the sample vocab does not have
+        # `______`. sentencepiece.NormalizerSpec.remove_extra_whitespaces attribute is set to False
+
+        input_ids = self.tokenizer.encode("       . Hello")
+        self.assertEqual(input_ids, [7, 4, 156, 86, 20])
+        sp_encode = self.tokenizer.sp_model.encode("       . Hello")
+        self.assertEqual(input_ids, sp_encode)
+        tokens = self.tokenizer.tokenize(" . Hello")
+        self.assertEqual(tokens, ["▁", ".", "▁He", "ll", "o"])
+
+        # `'▁'` is also a whitespace
+        input_ids = self.tokenizer.encode("▁He is not")
+        self.assertEqual(input_ids, [156, 46, 44])
+        tokens = self.tokenizer.tokenize("▁He is not")
+        sp_encode = self.tokenizer.sp_model.encode("▁He is not")
+        self.assertEqual(input_ids, sp_encode)
+        self.assertEqual(tokens, ["▁He", "▁is", "▁not"])  # no extra space added
+
+        input_ids = self.tokenizer.encode("▁He is not<s>             ▁He")
+        self.assertEqual(input_ids, [156, 46, 44, 1, 156])
+        tokens = self.tokenizer.tokenize("▁He is not<s>              ▁He")
+        self.assertEqual(tokens, ["▁He", "▁is", "▁not", "<s>", "▁He"])  # spaces are eaten by spm + our strip
+        # make sure that the output after the extra id is the same as if
+        # extra_id was not there
+        input_ids = self.tokenizer.encode("▁He is not             ▁He")
+        self.assertEqual(input_ids, [156, 46, 44, 156])
+        tokens = self.tokenizer.tokenize("▁He is not              ▁He")
+        self.assertEqual(tokens, ["▁He", "▁is", "▁not", "▁He"])  # spaces are eaten by spm even if not start
+
+    def test_character_after_special_token(self):
+        # Make sure that `tokenizer.tokenize` is similar to
+        # adding the equivalent special token to the vocab
+        input_ids = self.tokenizer.encode("Hey <s>I")
+        self.assertEqual(input_ids, [156, 30, 1, 100])
+        sp_encode = self.tokenizer.sp_model.encode("Hey .I")
+        # the last token should be 100
+        self.assertEqual(input_ids[-1], sp_encode[-1])
+        tokens = self.tokenizer.tokenize("<s>I")
+        self.assertEqual(tokens, ["<s>", "I"])
+
+        input_ids = self.tokenizer.encode("Hello, <s>,")
+        self.assertEqual(input_ids, [156, 86, 20, 3, 1, 3])
+        tokens = self.tokenizer.tokenize("Hello, <s>,")
+        self.assertEqual(tokens, ["▁He", "ll", "o", ",", "<s>", ","])
+
+    def test_special_tokens_strip(self):
+        input_ids = self.tokenizer.encode(" <s> ,")
+        self.assertEqual(input_ids, [1, 7, 3])
+        tokens = self.tokenizer.tokenize(" <s> ,")
+        # spaces are eaten by rstrip / lstrip + spm sp_model.encode("  ") = []
+        self.assertEqual(tokens, ["<s>", "▁", ","])
+
+        input_ids = self.tokenizer.encode("No <s> ▁He")
+        self.assertEqual(input_ids, [284, 1, 156])
+        tokens = self.tokenizer.tokenize("No <s> ▁He")
+        self.assertEqual(tokens, ["▁No", "<s>", "▁He"])  # spaces are eaten by rstrip / lstrip