
"""simple docstring"""






import json
import os
import unittest

from transformers.models.fsmt.tokenization_fsmt import VOCAB_FILES_NAMES, FSMTTokenizer
from transformers.testing_utils import slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


# using a different tiny model than the one used for default params defined in init to ensure proper testing
UpperCamelCase_						   =   """stas/tiny-wmt19-en-ru"""





class 							snake_case       (     __UpperCAmelCase							,       unittest.TestCase		):
   a_					:		Union[str, Any]     					=     FSMTTokenizer
   a_					:		Optional[int]     					=     False







   def    UpperCAmelCase__	( self)   ->List[Any]:
      super().setUp()

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

      a_						   =     ["en", "ru"]
      a_						   =     {
          "langs": self.langs,
          "src_vocab_size": 10,
          "tgt_vocab_size": 20,
      }

      a_						   =     os.path.join(self.tmpdirname       ,							VOCAB_FILES_NAMES["src_vocab_file"])
      a_						   =     os.path.join(self.tmpdirname       ,							VOCAB_FILES_NAMES["tgt_vocab_file"])
      a_						   =     os.path.join(self.tmpdirname       ,							"tokenizer_config.json")
      a_						   =     os.path.join(self.tmpdirname       ,							VOCAB_FILES_NAMES["merges_file"])
      with open(self.src_vocab_file       ,							"w") as fp:
         fp.write(json.dumps(__UpperCAmelCase))
      with open(self.tgt_vocab_file       ,							"w") as fp:
         fp.write(json.dumps(__UpperCAmelCase))
      with open(self.merges_file       ,							"w") as fp:
         fp.write("\n".join(__UpperCAmelCase))
      with open(__UpperCAmelCase       ,							"w") as fp:
         fp.write(json.dumps(__UpperCAmelCase))







   @cached_property
   def    UpperCAmelCase__	( self)   ->List[Any]:
      return FSMTTokenizer.from_pretrained("facebook/wmt19-ru-en")







   @cached_property
   def    UpperCAmelCase__	( self)   ->Optional[int]:
      return FSMTTokenizer.from_pretrained("facebook/wmt19-en-ru")







   def    UpperCAmelCase__	( self)   ->List[Any]:
      a_						   =     FSMTTokenizer.from_pretrained(__UpperCAmelCase)
      self.assertListEqual([tokenizer.src_lang, tokenizer.tgt_lang]       ,							["en", "ru"])
      self.assertEqual(tokenizer.src_vocab_size       ,							21)
      self.assertEqual(tokenizer.tgt_vocab_size       ,							21)







   def    UpperCAmelCase__	( self)   ->List[str]:
      a_						   =     FSMTTokenizer(self.langs       ,							self.src_vocab_file       ,							self.tgt_vocab_file       ,							self.merges_file)

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

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







   @slow
   def    UpperCAmelCase__	( self)   ->Optional[int]:
      a_						   =     self.tokenizer_ru_en

      a_						   =     tokenizer.encode("sequence builders"       ,							add_special_tokens=__UpperCAmelCase)
      a_						   =     tokenizer.encode("multi-sequence build"       ,							add_special_tokens=__UpperCAmelCase)

      a_						   =     tokenizer.build_inputs_with_special_tokens(__UpperCAmelCase)
      a_						   =     tokenizer.build_inputs_with_special_tokens(__UpperCAmelCase       ,							__UpperCAmelCase)

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







   @slow
   def    UpperCAmelCase__	( self)   ->List[str]:
      a_						   =     self.tokenizer_en_ru
      a_						   =     self.tokenizer_ru_en

      a_						   =     [
          [
              "Here\'s a little song I wrote. Don\'t worry, be happy.",
              [24_70, 39, 11, 23_49, 72_22, 70, 59_79, 7, 84_50, 10_50, 1_31_60, 5, 26, 64_45, 7, 2],
          ],
          ["This is it. No more. I\'m done!", [1_32, 21, 37, 7, 14_34, 86, 7, 70, 64_76, 13_05, 4_27, 2]],
      ]

      # if data needs to be recreated or added, run:
      # import torch
      # model = torch.hub.load("pytorch/fairseq", "transformer.wmt19.en-ru", checkpoint_file="model4.pt", tokenizer="moses", bpe="fastbpe")
      # for src_text, _ in targets: print(f"""[\n"{src_text}",\n {model.encode(src_text).tolist()}\n],""")

      for src_text, tgt_input_ids in targets:
         a_						   =     tokenizer_enc.encode(__UpperCAmelCase       ,							return_tensors=__UpperCAmelCase)
         self.assertListEqual(__UpperCAmelCase       ,							__UpperCAmelCase)

         # and decode backward, using the reversed languages model
         a_						   =     tokenizer_dec.decode(__UpperCAmelCase       ,							skip_special_tokens=__UpperCAmelCase)
         self.assertEqual(__UpperCAmelCase       ,							__UpperCAmelCase)







   @slow
   def    UpperCAmelCase__	( self)   ->str:
      a_						   =     FSMTTokenizer.from_pretrained("facebook/wmt19-ru-en"       ,							do_lower_case=__UpperCAmelCase)
      a_						   =     tokenizer.tokenize("USA is United States of America")
      a_						   =     ["us", "a</w>", "is</w>", "un", "i", "ted</w>", "st", "ates</w>", "of</w>", "am", "er", "ica</w>"]
      self.assertListEqual(__UpperCAmelCase       ,							__UpperCAmelCase)







   @unittest.skip("FSMTConfig.__init__  requires non-optional args")
   def    UpperCAmelCase__	( self)   ->Any:
      pass







   @unittest.skip("FSMTConfig.__init__  requires non-optional args")
   def    UpperCAmelCase__	( self)   ->Optional[int]:
      pass






import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


lowercase     :			str     						=	logging.get_logger(__name__)

class 			__A(    __UpperCAmelCase			):

     def __init__(   self,							*A,							**A   ):





            """simple docstring"""

            warnings.warn(
                '''The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
                ''' Please use MobileNetV2ImageProcessor instead.''',							A,							)
            super().__init__(*A,							**A   )






