





import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class 				_UpperCamelCase       (						lowerCAmelCase_	,    unittest.TestCase  ):
       _UpperCamelCase					:       List[str]       = HerbertTokenizer
       _UpperCamelCase					:       Optional[int]       = HerbertTokenizerFast
       _UpperCamelCase					:       Optional[Any]       = True

       def lowercase			(		self:			Dict		)							->			Dict:




              """simple docstring"""


              super().setUp()

              # Use a simpler test file without japanese/chinese characters
              with open(f'''{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'''       , encoding="utf-8"		) as f_data:
                     UpperCamelCase_ 							=	f_data.read().replace("\n\n"       , "\n"		).strip()

              UpperCamelCase_ 							=	[
                  "<s>",
                  "</s>",
                  "l",
                  "o",
                  "w",
                  "e",
                  "r",
                  "s",
                  "t",
                  "i",
                  "d",
                  "n",
                  "w</w>",
                  "r</w>",
                  "t</w>",
                  "lo",
                  "low",
                  "er</w>",
                  "low</w>",
                  "lowest</w>",
                  "newer</w>",
                  "wider</w>",
                  ",</w>",
                  "<unk>",
              ]
              UpperCamelCase_ 							=	dict(zip(_SCREAMING_SNAKE_CASE       , range(len(_SCREAMING_SNAKE_CASE		)		)		)		)
              UpperCamelCase_ 							=	["l o 123", "lo w 1456", "e r</w> 1789", ""]

              UpperCamelCase_ 							=	os.path.join(self.tmpdirname       , VOCAB_FILES_NAMES["vocab_file"]		)
              UpperCamelCase_ 							=	os.path.join(self.tmpdirname       , VOCAB_FILES_NAMES["merges_file"]		)
              with open(self.vocab_file       , "w"		) as fp:
                     fp.write(json.dumps(_SCREAMING_SNAKE_CASE		)		)
              with open(self.merges_file       , "w"		) as fp:
                     fp.write("\n".join(_SCREAMING_SNAKE_CASE		)		)

       def lowercase			(		self:			Dict       , _SCREAMING_SNAKE_CASE:			int		)							->			List[str]:




              """simple docstring"""


              UpperCamelCase_ 							=	"lower newer"
              UpperCamelCase_ 							=	"lower newer"
              return input_text, output_text

       def lowercase			(		self:			List[Any]		)							->			Any:




              """simple docstring"""


              UpperCamelCase_ 							=	self.tokenizer_class(vocab_file=self.vocab_file       , merges_file=self.merges_file		)

              UpperCamelCase_ 							=	"lower"
              UpperCamelCase_ 							=	["low", "er</w>"]
              UpperCamelCase_ 							=	tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)
              self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)

              UpperCamelCase_ 							=	tokens + ["<unk>"]
              UpperCamelCase_ 							=	[16, 17, 23]
              self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE		)       , _SCREAMING_SNAKE_CASE		)

       def lowercase			(		self:			Union[str, Any]		)							->			int:




              """simple docstring"""


              if not self.test_rust_tokenizer:
                     return

              UpperCamelCase_ 							=	self.get_tokenizer()
              UpperCamelCase_ 							=	self.get_rust_tokenizer()

              UpperCamelCase_ 							=	"lower,newer"

              UpperCamelCase_ 							=	tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	rust_tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)
              self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)

              UpperCamelCase_ 							=	tokenizer.encode(_SCREAMING_SNAKE_CASE       , add_special_tokens=_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	rust_tokenizer.encode(_SCREAMING_SNAKE_CASE       , add_special_tokens=_SCREAMING_SNAKE_CASE		)
              self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)

              UpperCamelCase_ 							=	self.get_rust_tokenizer()
              UpperCamelCase_ 							=	tokenizer.encode(_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	rust_tokenizer.encode(_SCREAMING_SNAKE_CASE		)
              self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)



       @slow
       def lowercase			(		self:			List[str]		)							->			Tuple:




              """simple docstring"""


              UpperCamelCase_ 							=	self.tokenizer_class.from_pretrained("allegro/herbert-base-cased"		)

              UpperCamelCase_ 							=	tokenizer.encode("konstruowanie sekwencji"       , add_special_tokens=_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	tokenizer.encode("konstruowanie wielu sekwencji"       , add_special_tokens=_SCREAMING_SNAKE_CASE		)

              UpperCamelCase_ 							=	tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)

              assert encoded_sentence == [0] + text + [2]
              assert encoded_pair == [0] + text + [2] + text_a + [2]








import warnings

from ...utils import logging
from .image_processing_convnext import ConvNextImageProcessor


_UpperCAmelCase										=					logging.get_logger(__name__)



class 				_UpperCamelCase       (						lowerCAmelCase_  ):

       def __init__(		self:			Tuple       , *_SCREAMING_SNAKE_CASE:			List[Any]       , **_SCREAMING_SNAKE_CASE:			List[Any]		)							->			None:




              """simple docstring"""


              warnings.warn(
                  "The class ConvNextFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
                  " Please use ConvNextImageProcessor instead."       , _SCREAMING_SNAKE_CASE       , )
              super().__init__(*_SCREAMING_SNAKE_CASE       , **_SCREAMING_SNAKE_CASE		)

