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 					_lowercase    (     UpperCAmelCase__ ,  unittest.TestCase			):






    '''simple docstring'''
    SCREAMING_SNAKE_CASE:				int          =    LxmertTokenizer
    SCREAMING_SNAKE_CASE:				Any          =    LxmertTokenizerFast
    SCREAMING_SNAKE_CASE:				Union[str, Any]          =    True
    SCREAMING_SNAKE_CASE:				Dict          =    True




    def      _a    (    self ):
       super().setUp()

       lowerCAmelCase_:							int       =	[
           "[UNK]",
           "[CLS]",
           "[SEP]",
           "want",
           "##want",
           "##ed",
           "wa",
           "un",
           "runn",
           "##ing",
           ",",
           "low",
           "lowest",
       ]
       lowerCAmelCase_:							Dict       =	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      _a    (    self       ,						lowerCamelCase__ ):
       lowerCAmelCase_:							Dict       =	"UNwant\u00E9d,running"
       lowerCAmelCase_:							Optional[int]       =	"unwanted, running"
       return input_text, output_text




    def      _a    (    self ):
       lowerCAmelCase_:							Union[str, Any]       =	self.tokenizer_class(self.vocab_file )

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




    def      _a    (    self ):
       if not self.test_rust_tokenizer:
          return

       lowerCAmelCase_:							str       =	self.get_tokenizer()
       lowerCAmelCase_:							Optional[Any]       =	self.get_rust_tokenizer()

       lowerCAmelCase_:							Any       =	"I was born in 92000, and this is falsé."

       lowerCAmelCase_:							Optional[int]       =	tokenizer.tokenize(lowerCamelCase__ )
       lowerCAmelCase_:							List[str]       =	rust_tokenizer.tokenize(lowerCamelCase__ )
       self.assertListEqual(lowerCamelCase__       ,						lowerCamelCase__ )

       lowerCAmelCase_:							Tuple       =	tokenizer.encode(lowerCamelCase__       ,						add_special_tokens=lowerCamelCase__ )
       lowerCAmelCase_:							Optional[Any]       =	rust_tokenizer.encode(lowerCamelCase__       ,						add_special_tokens=lowerCamelCase__ )
       self.assertListEqual(lowerCamelCase__       ,						lowerCamelCase__ )

       lowerCAmelCase_:							Union[str, Any]       =	self.get_rust_tokenizer()
       lowerCAmelCase_:							Tuple       =	tokenizer.encode(lowerCamelCase__ )
       lowerCAmelCase_:							Dict       =	rust_tokenizer.encode(lowerCamelCase__ )
       self.assertListEqual(lowerCamelCase__       ,						lowerCamelCase__ )
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


a  :      List[str]            =    {
    """configuration_efficientformer""": [
        """EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """EfficientFormerConfig""",
    ]
}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a  :      str            =    ["""EfficientFormerImageProcessor"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a  :      List[str]            =    [
     """EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """EfficientFormerForImageClassification""",
     """EfficientFormerForImageClassificationWithTeacher""",
     """EfficientFormerModel""",
     """EfficientFormerPreTrainedModel""",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a  :      List[Any]            =    [
     """TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """TFEfficientFormerForImageClassification""",
     """TFEfficientFormerForImageClassificationWithTeacher""",
     """TFEfficientFormerModel""",
     """TFEfficientFormerPreTrainedModel""",
 ]

if TYPE_CHECKING:
 from .configuration_efficientformer import EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientFormerConfig

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .image_processing_efficientformer import EfficientFormerImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_efficientformer import (
      EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      EfficientFormerForImageClassification,
      EfficientFormerForImageClassificationWithTeacher,
      EfficientFormerModel,
      EfficientFormerPreTrainedModel,
  )
 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_efficientformer import (
      TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFEfficientFormerForImageClassification,
      TFEfficientFormerForImageClassificationWithTeacher,
      TFEfficientFormerModel,
      TFEfficientFormerPreTrainedModel,
  )

else:
 import sys

 a  :      Tuple            =    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)