
import os
import unittest

from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class    _snake_case (						UpperCAmelCase_	,    unittest.TestCase				):
 __lowerCAmelCase	:  int	   =      LxmertTokenizer
 __lowerCAmelCase	:  Any	   =      LxmertTokenizerFast
 __lowerCAmelCase	:  Dict	   =      True
 __lowerCAmelCase	:  List[Any]	   =      True


 def   lowercase__  (       self):


   '''simple docstring'''




   super().setUp()

   lowercase__	: Tuple     		=   [
       """[UNK]""",
       """[CLS]""",
       """[SEP]""",
       """want""",
       """##want""",
       """##ed""",
       """wa""",
       """un""",
       """runn""",
       """##ing""",
       """,""",
       """low""",
       """lowest""",
   ]
   lowercase__	: str     		=   os.path.join(self.tmpdirname       ,	VOCAB_FILES_NAMES["""vocab_file"""])
   with open(self.vocab_file       ,	"""w"""       ,	encoding="""utf-8""") as vocab_writer:
     vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]))


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   lowercase__	: Optional[Any]     		=   """UNwant\u00E9d,running"""
   lowercase__	: Union[str, Any]     		=   """unwanted, running"""
   return input_text, output_text


 def   lowercase__  (       self):


   '''simple docstring'''




   lowercase__	: Dict     		=   self.tokenizer_class(self.vocab_file)

   lowercase__	: List[Any]     		=   tokenizer.tokenize("""UNwant\u00E9d,running""")
   self.assertListEqual(SCREAMING_SNAKE_CASE_       ,	["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""])
   self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_)       ,	[7, 4, 5, 10, 8, 9])



 def   lowercase__  (       self):


   '''simple docstring'''




   if not self.test_rust_tokenizer:
     return

   lowercase__	: Tuple     		=   self.get_tokenizer()
   lowercase__	: Dict     		=   self.get_rust_tokenizer()

   lowercase__	: List[Any]     		=   """I was born in 92000, and this is falsé."""

   lowercase__	: List[str]     		=   tokenizer.tokenize(SCREAMING_SNAKE_CASE_)
   lowercase__	: Any     		=   rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE_)
   self.assertListEqual(SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_)

   lowercase__	: int     		=   tokenizer.encode(SCREAMING_SNAKE_CASE_       ,	add_special_tokens=SCREAMING_SNAKE_CASE_)
   lowercase__	: Union[str, Any]     		=   rust_tokenizer.encode(SCREAMING_SNAKE_CASE_       ,	add_special_tokens=SCREAMING_SNAKE_CASE_)
   self.assertListEqual(SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_)

   lowercase__	: Tuple     		=   self.get_rust_tokenizer()
   lowercase__	: List[Any]     		=   tokenizer.encode(SCREAMING_SNAKE_CASE_)
   lowercase__	: Dict     		=   rust_tokenizer.encode(SCREAMING_SNAKE_CASE_)
   self.assertListEqual(SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_)










"""simple docstring"""


from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case    					=					{
    'configuration_informer': [
        'INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'InformerConfig',
    ],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __snake_case    					=					[
       'INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
       'InformerForPrediction',
       'InformerModel',
       'InformerPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_informer import INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, InformerConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_informer import (
          INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          InformerForPrediction,
          InformerModel,
          InformerPreTrainedModel,
      )

else:
   import sys

   __snake_case    					=					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)