

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
__A     						=      'stas/tiny-wmt19-en-ru'



class     lowercase_       (    __lowercase  ,				unittest.TestCase	):
      UpperCamelCase_     :						Optional[int]		 =							FSMTTokenizer
      UpperCamelCase_     :						Dict		 =							False



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

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

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

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



      @cached_property
      def 		UpperCamelCase_						(     self :							List[Any]						)       ->	Union[str, Any]:
        return FSMTTokenizer.from_pretrained('''facebook/wmt19-ru-en'''						)



      @cached_property
      def 		UpperCamelCase_						(     self :							Tuple						)       ->	int:
        return FSMTTokenizer.from_pretrained('''facebook/wmt19-en-ru'''						)



      def 		UpperCamelCase_						(     self :							str						)       ->	Optional[int]:
        _snake_case		=				FSMTTokenizer.from_pretrained(_A						)
        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 :							Union[str, Any]						)       ->	Optional[int]:
        _snake_case		=				FSMTTokenizer(self.langs     ,   self.src_vocab_file     ,   self.tgt_vocab_file     ,   self.merges_file						)

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

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



      @slow
      def 		UpperCamelCase_						(     self :							Optional[int]						)       ->	List[Any]:
        _snake_case		=				self.tokenizer_ru_en

        _snake_case		=				tokenizer.encode('''sequence builders'''     ,   add_special_tokens=_A						)
        _snake_case		=				tokenizer.encode('''multi-sequence build'''     ,   add_special_tokens=_A						)

        _snake_case		=				tokenizer.build_inputs_with_special_tokens(_A						)
        _snake_case		=				tokenizer.build_inputs_with_special_tokens(_A     ,   _A						)

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



      @slow
      def 		UpperCamelCase_						(     self :							Any						)       ->	Optional[Any]:
        _snake_case		=				self.tokenizer_en_ru
        _snake_case		=				self.tokenizer_ru_en

        _snake_case		=				[
            [
                "Here's a little song I wrote. Don't worry, be happy.",
                [2470, 39, 11, 2349, 7222, 70, 5979, 7, 8450, 1050, 13160, 5, 26, 6445, 7, 2],
            ],
            ["This is it. No more. I'm done!", [132, 21, 37, 7, 1434, 86, 7, 70, 6476, 1305, 427, 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:
          _snake_case		=				tokenizer_enc.encode(_A     ,   return_tensors=_A						)
          self.assertListEqual(_A     ,   _A						)

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



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



      @unittest.skip('''FSMTConfig.__init__  requires non-optional args'''						)
      def 		UpperCamelCase_						(     self :							Union[str, Any]						)       ->	Any:
        pass







      @unittest.skip('''FSMTConfig.__init__  requires non-optional args'''						)
      def 		UpperCamelCase_						(     self :							Dict						)       ->	str:
        pass






def 						snake_case__							(       __lowercase							)		->		int:







						"""simple docstring"""

						A__						:				Any         =			0
						for plain_chr in plain_text:
												A__						:				List[str]         =			(
												    ord(__lowercase							) + (hash_value << 6) + (hash_value << 1_6) - hash_value
												)
						return hash_value