


"""simple docstring"""







import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin






class 						_A  (  _a   ,unittest.TestCase  ):







    """simple docstring"""




    UpperCAmelCase	:							Any     =	BioGptTokenizer
    UpperCAmelCase	:							List[Any]     =	False






    def      __snake_case							( self    :   Union[str, Any]):
      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      a						:		List[str]											=      [
          "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>",
      ]
      a						:		Union[str, Any]											=      dict(zip(__UpperCAmelCase    ,			range(len(__UpperCAmelCase))))
      a						:		Tuple											=      ["l o 123", "lo w 1456", "e r</w> 1789", ""]

      a						:		Tuple											=      os.path.join(self.tmpdirname    ,			VOCAB_FILES_NAMES["vocab_file"])
      a						:		List[Any]											=      os.path.join(self.tmpdirname    ,			VOCAB_FILES_NAMES["merges_file"])
      with open(self.vocab_file    ,			"w") as fp:
        fp.write(json.dumps(__UpperCAmelCase))
      with open(self.merges_file    ,			"w") as fp:
        fp.write("\n".join(__UpperCAmelCase))






    def      __snake_case							( self    :   Tuple    ,			__UpperCAmelCase    :   List[Any]):
      a						:		Dict											=      "lower newer"
      a						:		Union[str, Any]											=      "lower newer"
      return input_text, output_text






    def      __snake_case							( self    :   Optional[Any]):
      a						:		List[str]											=      BioGptTokenizer(self.vocab_file    ,			self.merges_file)

      a						:		Optional[int]											=      "lower"
      a						:		str											=      ["low", "er</w>"]
      a						:		List[str]											=      tokenizer.tokenize(__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)

      a						:		int											=      tokens + ["<unk>"]
      a						:		Dict											=      [14, 15, 20]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase)    ,			__UpperCAmelCase)






    @slow
    def      __snake_case							( self    :   str):
      a						:		str											=      BioGptTokenizer.from_pretrained("microsoft/biogpt")

      a						:		List[Any]											=      tokenizer.encode("sequence builders"    ,			add_special_tokens=__UpperCAmelCase)
      a						:		Dict											=      tokenizer.encode("multi-sequence build"    ,			add_special_tokens=__UpperCAmelCase)

      a						:		str											=      tokenizer.build_inputs_with_special_tokens(__UpperCAmelCase)
      a						:		List[str]											=      tokenizer.build_inputs_with_special_tokens(__UpperCAmelCase    ,			__UpperCAmelCase)

      self.assertTrue(encoded_sentence == [2] + text)
      self.assertTrue(encoded_pair == [2] + text + [2] + text_a)








"""simple docstring"""







import warnings

from ...utils import logging
from .image_processing_dpt import DPTImageProcessor


__lowercase    =				logging.get_logger(__name__)






class 						_A  (  _a  ):







    """simple docstring"""




    def __init__( self    :   List[Any]    ,			*__UpperCAmelCase    :   int    ,			**__UpperCAmelCase    :   List[Any]):
      warnings.warn(
          "The class DPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
          " use DPTImageProcessor instead."    ,			__UpperCAmelCase    ,			)
      super().__init__(*__UpperCAmelCase    ,			**__UpperCAmelCase)






