






import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


class       __lowercase      (	__lowerCAmelCase			,      unittest.TestCase  ):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE   						=				CanineTokenizer
     SCREAMING_SNAKE_CASE   						=				False




     def 		lowerCAmelCase_     (				self       :			Union[str, Any]				):


         """simple docstring"""



         super().setUp()
         __A         =	CanineTokenizer()
         tokenizer.save_pretrained(self.tmpdirname				)




     @cached_property
     def 		lowerCAmelCase_     (				self       :			Any				):


         """simple docstring"""



         return CanineTokenizer.from_pretrained("""google/canine-s"""				)




     def 		lowerCAmelCase_     (				self       :			Optional[Any] ,	**UpperCamelCase_       :			Dict				):


         """simple docstring"""



         __A         =	self.tokenizer_class.from_pretrained(self.tmpdirname ,	**lowerCAmelCase_				)
         __A         =	1_024
         return tokenizer




     @require_torch
     def 		lowerCAmelCase_     (				self       :			Union[str, Any]				):


         """simple docstring"""



         __A         =	self.canine_tokenizer
         __A         =	["""Life is like a box of chocolates.""", """You never know what you're gonna get."""]
         # fmt: off
         __A         =	[57_344, 76, 105, 102, 101, 32, 105, 115, 32, 108, 105, 107, 101, 32, 97, 32, 98, 111, 120, 32, 111, 102, 32, 99, 104, 111, 99, 111, 108, 97, 116, 101, 115, 46, 57_345, 0, 0, 0, 0]
         # fmt: on
         __A         =	tokenizer(lowerCAmelCase_ ,	padding=lowerCAmelCase_ ,	return_tensors="""pt"""				)
         self.assertIsInstance(lowerCAmelCase_ ,	lowerCAmelCase_				)

         __A         =	list(batch.input_ids.numpy()[0]				)

         self.assertListEqual(lowerCAmelCase_ ,	lowerCAmelCase_				)

         self.assertEqual((2, 39) ,	batch.input_ids.shape				)
         self.assertEqual((2, 39) ,	batch.attention_mask.shape				)




     @require_torch
     def 		lowerCAmelCase_     (				self       :			int				):


         """simple docstring"""



         __A         =	self.canine_tokenizer
         __A         =	["""Once there was a man.""", """He wrote a test in HuggingFace Tranformers."""]
         __A         =	tokenizer(lowerCAmelCase_ ,	padding=lowerCAmelCase_ ,	return_tensors="""pt"""				)
         # check if input_ids, attention_mask and token_type_ids are returned
         self.assertIn("""input_ids""" ,	lowerCAmelCase_				)
         self.assertIn("""attention_mask""" ,	lowerCAmelCase_				)
         self.assertIn("""token_type_ids""" ,	lowerCAmelCase_				)




     @require_torch
     def 		lowerCAmelCase_     (				self       :			List[Any]				):


         """simple docstring"""



         __A         =	self.canine_tokenizer
         __A         =	[
             """What's the weater?""",
             """It's about 25 degrees.""",
         ]
         __A         =	tokenizer(
             text_target=lowerCAmelCase_ ,	max_length=32 ,	padding="""max_length""" ,	truncation=lowerCAmelCase_ ,	return_tensors="""pt"""				)
         self.assertEqual(32 ,	targets["""input_ids"""].shape[1]				)




     def 		lowerCAmelCase_     (				self       :			str				):


         """simple docstring"""



         __A         =	self.get_tokenizers()
         for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}"				):
                 self.assertNotEqual(tokenizer.model_max_length ,	42				)

        # Now let's start the test
         __A         =	self.get_tokenizers()
         for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}"				):
                 # Isolate this from the other tests because we save additional tokens/etc
                 __A         =	tempfile.mkdtemp()

                 __A         =	""" He is very happy, UNwant\u00E9d,running"""
                 __A         =	tokenizer.encode(lowerCAmelCase_ ,	add_special_tokens=lowerCAmelCase_				)
                 tokenizer.save_pretrained(lowerCAmelCase_				)

                 __A         =	tokenizer.__class__.from_pretrained(lowerCAmelCase_				)
                 __A         =	after_tokenizer.encode(lowerCAmelCase_ ,	add_special_tokens=lowerCAmelCase_				)
                 self.assertListEqual(lowerCAmelCase_ ,	lowerCAmelCase_				)

                 shutil.rmtree(lowerCAmelCase_				)

         __A         =	self.get_tokenizers(model_max_length=42				)
         for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}"				):
                 # Isolate this from the other tests because we save additional tokens/etc
                 __A         =	tempfile.mkdtemp()

                 __A         =	""" He is very happy, UNwant\u00E9d,running"""

                 __A         =	tokenizer.additional_special_tokens

                 # We can add a new special token for Canine as follows:
                 __A         =	chr(0xE_0_0_7				)
                 additional_special_tokens.append(lowerCAmelCase_				)
                 tokenizer.add_special_tokens({"""additional_special_tokens""": additional_special_tokens}				)
                 __A         =	tokenizer.encode(lowerCAmelCase_ ,	add_special_tokens=lowerCAmelCase_				)
                 tokenizer.save_pretrained(lowerCAmelCase_				)

                 __A         =	tokenizer.__class__.from_pretrained(lowerCAmelCase_				)
                 __A         =	after_tokenizer.encode(lowerCAmelCase_ ,	add_special_tokens=lowerCAmelCase_				)
                 self.assertListEqual(lowerCAmelCase_ ,	lowerCAmelCase_				)
                 self.assertIn(lowerCAmelCase_ ,	after_tokenizer.additional_special_tokens				)
                 self.assertEqual(after_tokenizer.model_max_length ,	42				)

                 __A         =	tokenizer.__class__.from_pretrained(lowerCAmelCase_ ,	model_max_length=43				)
                 self.assertEqual(tokenizer.model_max_length ,	43				)

                 shutil.rmtree(lowerCAmelCase_				)




     def 		lowerCAmelCase_     (				self       :			Optional[int]				):


         """simple docstring"""



         __A         =	self.get_tokenizers(do_lower_case=lowerCAmelCase_				)
         for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}"				):
                 __A    ,	__A         =	self.get_clean_sequence(lowerCAmelCase_				)

                 # a special token for Canine can be defined as follows:
                 __A         =	0xE_0_0_5
                 __A         =	chr(lowerCAmelCase_				)

                 tokenizer.add_special_tokens({"""cls_token""": special_token}				)
                 __A         =	tokenizer.encode(lowerCAmelCase_ ,	add_special_tokens=lowerCAmelCase_				)
                 self.assertEqual(len(lowerCAmelCase_				) ,	1				)

                 __A         =	tokenizer.decode(ids + encoded_special_token ,	clean_up_tokenization_spaces=lowerCAmelCase_				)
                 __A         =	tokenizer.encode(lowerCAmelCase_ ,	add_special_tokens=lowerCAmelCase_				)

                 __A         =	tokenizer.encode(lowerCAmelCase_ ,	add_special_tokens=lowerCAmelCase_				)
                 __A         =	tokenizer.encode(lowerCAmelCase_ ,	add_special_tokens=lowerCAmelCase_				)
                 self.assertEqual(lowerCAmelCase_ ,	input_encoded + special_token_id				)

                 __A         =	tokenizer.decode(lowerCAmelCase_ ,	skip_special_tokens=lowerCAmelCase_				)
                 self.assertTrue(special_token not in decoded				)




     def 		lowerCAmelCase_     (				self       :			Union[str, Any]				):


         """simple docstring"""



         __A         =	self.get_tokenizers(do_lower_case=lowerCAmelCase_				)
         for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}"				):
                 __A         =	chr(0xE_0_0_5				)
                 __A         =	chr(0xE_0_0_6				)

                 # `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
                 tokenizer.add_tokens([SPECIAL_TOKEN_1] ,	special_tokens=lowerCAmelCase_				)
                 # `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
                 # which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
                 tokenizer.add_special_tokens({"""additional_special_tokens""": [SPECIAL_TOKEN_2]}				)

                 __A         =	tokenizer.tokenize(lowerCAmelCase_				)
                 __A         =	tokenizer.tokenize(lowerCAmelCase_				)

                 self.assertEqual(len(lowerCAmelCase_				) ,	1				)
                 self.assertEqual(len(lowerCAmelCase_				) ,	1				)
                 self.assertEqual(token_a[0] ,	lowerCAmelCase_				)
                 self.assertEqual(token_a[0] ,	lowerCAmelCase_				)




     @require_tokenizers
     def 		lowerCAmelCase_     (				self       :			Optional[int]				):


         """simple docstring"""



         __A         =	self.get_tokenizers(do_lower_case=lowerCAmelCase_				)
         for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}"				):
                 # a special token for Canine can be defined as follows:
                 __A         =	0xE_0_0_6
                 __A         =	chr(lowerCAmelCase_				)

                 __A         =	AddedToken(lowerCAmelCase_ ,	lstrip=lowerCAmelCase_				)
                 tokenizer.add_special_tokens({"""additional_special_tokens""": [new_token]}				)

                 with tempfile.TemporaryDirectory() as tmp_dir_name:
                     tokenizer.save_pretrained(lowerCAmelCase_				)
                     tokenizer.from_pretrained(lowerCAmelCase_				)




     def 		lowerCAmelCase_     (				self       :			Optional[int]				):


         """simple docstring"""



         __A         =	[]
         if self.test_slow_tokenizer:
             tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())				)

         if self.test_rust_tokenizer:
             tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())				)

         for tokenizer_class, tokenizer_utils in tokenizer_list:
             with tempfile.TemporaryDirectory() as tmp_dir:
                 tokenizer_utils.save_pretrained(lowerCAmelCase_				)

                 with open(os.path.join(lowerCAmelCase_ ,	"""special_tokens_map.json"""				) ,	encoding="""utf-8"""				) as json_file:
                     __A         =	json.load(lowerCAmelCase_				)

                 with open(os.path.join(lowerCAmelCase_ ,	"""tokenizer_config.json"""				) ,	encoding="""utf-8"""				) as json_file:
                     __A         =	json.load(lowerCAmelCase_				)

                 # a special token for Canine can be defined as follows:
                 __A         =	0xE_0_0_6
                 __A         =	chr(lowerCAmelCase_				)

                 __A         =	[new_token_a]
                 __A         =	[new_token_a]

                 with open(os.path.join(lowerCAmelCase_ ,	"""special_tokens_map.json"""				) ,	"""w""" ,	encoding="""utf-8"""				) as outfile:
                     json.dump(lowerCAmelCase_ ,	lowerCAmelCase_				)
                 with open(os.path.join(lowerCAmelCase_ ,	"""tokenizer_config.json"""				) ,	"""w""" ,	encoding="""utf-8"""				) as outfile:
                     json.dump(lowerCAmelCase_ ,	lowerCAmelCase_				)

                 # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
                 # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
                 # "special_tokens_map.json" files
                 __A         =	tokenizer_class.from_pretrained(lowerCAmelCase_ ,	extra_ids=0				)
                 self.assertIn(lowerCAmelCase_ ,	tokenizer_without_change_in_init.additional_special_tokens				)
                 # self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
                 self.assertEqual(
                     [new_token_a] ,	tokenizer_without_change_in_init.convert_ids_to_tokens(
                         tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]				)				) ,	)

                 __A         =	0xE_0_0_7
                 __A         =	chr(lowerCAmelCase_				)
                 # Now we test that we can change the value of additional_special_tokens in the from_pretrained
                 __A         =	[AddedToken(lowerCAmelCase_ ,	lstrip=lowerCAmelCase_				)]
                 __A         =	tokenizer_class.from_pretrained(
                     lowerCAmelCase_ ,	additional_special_tokens=lowerCAmelCase_ ,	extra_ids=0				)

                 self.assertIn(lowerCAmelCase_ ,	tokenizer.additional_special_tokens				)
                 # self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
                 self.assertEqual(
                     [new_token_a] ,	tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]				)				)				)




     @require_tokenizers
     def 		lowerCAmelCase_     (				self       :			Dict				):


         """simple docstring"""



         __A         =	self.get_tokenizers(do_lower_case=lowerCAmelCase_				)
         for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}"				):
                 __A         =	"""hello world"""
                 if self.space_between_special_tokens:
                     __A         =	"""[CLS] hello world [SEP]"""
                 else:
                     __A         =	input
                 __A         =	tokenizer.encode(lowerCAmelCase_ ,	add_special_tokens=lowerCAmelCase_				)
                 __A         =	tokenizer.decode(lowerCAmelCase_ ,	spaces_between_special_tokens=self.space_between_special_tokens				)
                 self.assertIn(lowerCAmelCase_ ,	[output, output.lower()]				)




     def 		lowerCAmelCase_     (				self       :			Optional[Any]				):


         """simple docstring"""



         __A         =	self.get_tokenizers()
         for tokenizer in tokenizers:
             with self.subTest(F"{tokenizer.__class__.__name__}"				):
                 __A         =	[
                     """bos_token""",
                     """eos_token""",
                     """unk_token""",
                     """sep_token""",
                     """pad_token""",
                     """cls_token""",
                     """mask_token""",
                 ]

         __A         =	"""a"""
         __A         =	ord(lowerCAmelCase_				)

         for attr in attributes_list:
             setattr(lowerCAmelCase_ ,	attr + """_id""" ,	lowerCAmelCase_				)
             self.assertEqual(getattr(lowerCAmelCase_ ,	lowerCAmelCase_				) ,	lowerCAmelCase_				)
             self.assertEqual(getattr(lowerCAmelCase_ ,	attr + """_id"""				) ,	lowerCAmelCase_				)

             setattr(lowerCAmelCase_ ,	attr + """_id""" ,	lowerCAmelCase_				)
             self.assertEqual(getattr(lowerCAmelCase_ ,	lowerCAmelCase_				) ,	lowerCAmelCase_				)
             self.assertEqual(getattr(lowerCAmelCase_ ,	attr + """_id"""				) ,	lowerCAmelCase_				)

         setattr(lowerCAmelCase_ ,	"""additional_special_tokens_ids""" ,	[]				)
         self.assertListEqual(getattr(lowerCAmelCase_ ,	"""additional_special_tokens"""				) ,	[]				)
         self.assertListEqual(getattr(lowerCAmelCase_ ,	"""additional_special_tokens_ids"""				) ,	[]				)

         __A         =	0xE_0_0_6
         __A         =	chr(lowerCAmelCase_				)
         setattr(lowerCAmelCase_ ,	"""additional_special_tokens_ids""" ,	[additional_special_token_id]				)
         self.assertListEqual(getattr(lowerCAmelCase_ ,	"""additional_special_tokens"""				) ,	[additional_special_token]				)
         self.assertListEqual(getattr(lowerCAmelCase_ ,	"""additional_special_tokens_ids"""				) ,	[additional_special_token_id]				)




     def 		lowerCAmelCase_     (				self       :			List[Any]				):


         """simple docstring"""



         pass




     def 		lowerCAmelCase_     (				self       :			Union[str, Any]				):


         """simple docstring"""



         pass




     def 		lowerCAmelCase_     (				self       :			Dict				):


         """simple docstring"""



         pass




     def 		lowerCAmelCase_     (				self       :			Tuple				):


         """simple docstring"""



         pass




     def 		lowerCAmelCase_     (				self       :			Dict				):


         """simple docstring"""



         pass




     def 		lowerCAmelCase_     (				self       :			Union[str, Any]				):


         """simple docstring"""



         pass




     def 		lowerCAmelCase_     (				self       :			Any				):


         """simple docstring"""



         pass





     def 		lowerCAmelCase_     (				self       :			Dict				):


         """simple docstring"""



         pass












from typing import TYPE_CHECKING

from ...utils import _LazyModule


__a      :       Optional[int]				  =   {"tokenization_bertweet": ["BertweetTokenizer"]}


if TYPE_CHECKING:
  from .tokenization_bertweet import BertweetTokenizer

else:
  import sys

  __a      :       int				  =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




