


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case            =   {
    "configuration_swinv2": ["SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Swinv2Config"],
}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __snake_case            =   [
       "SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST",
       "Swinv2ForImageClassification",
       "Swinv2ForMaskedImageModeling",
       "Swinv2Model",
       "Swinv2PreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_swinva import (
          SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
          SwinvaForImageClassification,
          SwinvaForMaskedImageModeling,
          SwinvaModel,
          SwinvaPreTrainedModel,
      )


else:
   import sys

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








import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin




class    UpperCAmelCase					(       __snake_case      , unittest.TestCase    ):
			lowercase						= XLMTokenizer
			lowercase						= False




			def   lowerCamelCase_					(						self							:		Optional[int]						):







						"""simple docstring"""







						super().setUp()

						# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
						UpperCamelCase         =					[
						    """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>""",
						    """<unk>""",
						]
						UpperCamelCase         =					dict(zip(__magic_name__       ,       range(len(__magic_name__						)						)						)						)
						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(__magic_name__						)						)
						with open(self.merges_file       ,       """w"""						) as fp:
									fp.write("""\n""".join(__magic_name__						)						)




			def   lowerCamelCase_					(						self							:		Any       ,       __magic_name__							:		List[str]						):







						"""simple docstring"""







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




			def   lowerCamelCase_					(						self							:		List[str]						):







						"""simple docstring"""







						UpperCamelCase         =					XLMTokenizer(self.vocab_file       ,       self.merges_file						)

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

						UpperCamelCase         =					tokens + ["""<unk>"""]
						UpperCamelCase         =					[1_4, 1_5, 2_0]
						self.assertListEqual(tokenizer.convert_tokens_to_ids(__magic_name__						)       ,       __magic_name__						)





			@slow
			def   lowerCamelCase_					(						self							:		Optional[int]						):







						"""simple docstring"""







						UpperCamelCase         =					XLMTokenizer.from_pretrained("""xlm-mlm-en-2048"""						)

						UpperCamelCase         =					tokenizer.encode("""sequence builders"""       ,       add_special_tokens=__magic_name__						)
						UpperCamelCase         =					tokenizer.encode("""multi-sequence build"""       ,       add_special_tokens=__magic_name__						)

						UpperCamelCase         =					tokenizer.build_inputs_with_special_tokens(__magic_name__						)
						UpperCamelCase         =					tokenizer.build_inputs_with_special_tokens(__magic_name__       ,       __magic_name__						)

						assert encoded_sentence == [0] + text + [1]
						assert encoded_pair == [0] + text + [1] + text_a + [1]




