
'''simple docstring'''





import os
import tempfile
import unittest
from typing import List

from transformers.models.esm.tokenization_esm import VOCAB_FILES_NAMES, EsmTokenizer
from transformers.testing_utils import require_tokenizers
from transformers.tokenization_utils import PreTrainedTokenizer
from transformers.tokenization_utils_base import PreTrainedTokenizerBase


@require_tokenizers
class 			UpperCamelCase__	(     unittest.TestCase):
 UpperCAmelCase__     :     Optional[Any]    					=       EsmTokenizer






 def 						lowercase_    (      self	:List[Any]      )					->      Dict:







       '''simple docstring'''



       super().setUp()
       __A													=      tempfile.mkdtemp()
       # fmt: off
       __A													=      ["<cls>", "<pad>", "<eos>", "<unk>", "L", "A", "G", "V", "S", "E", "R", "T", "I", "D", "P", "K", "Q", "N", "F", "Y", "M", "H", "W", "C", "X", "B", "U", "Z", "O", ".", "-", "<null_1>", "<mask>"]  # noqa: E501
       # fmt: on
       __A													=      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 						lowercase_    (      self	:Optional[Any]						,					**_A	:Union[str, Any]      )					->      List[PreTrainedTokenizerBase]:







       '''simple docstring'''



       return [self.get_tokenizer(**_A      )]






 def 						lowercase_    (      self	:Dict						,					**_A	:Union[str, Any]      )					->      PreTrainedTokenizer:







       '''simple docstring'''



       return self.tokenizer_class.from_pretrained(self.tmpdirname						,					**_A      )






 def 						lowercase_    (      self	:int      )					->      int:







       '''simple docstring'''



       __A													=      self.tokenizer_class(self.vocab_file      )

       __A													=      tokenizer.tokenize('LAGVS'      )
       self.assertListEqual(_A						,					['L', 'A', 'G', 'V', 'S']      )
       self.assertListEqual(tokenizer.convert_tokens_to_ids(_A      )						,					[4, 5, 6, 7, 8]      )






 def 						lowercase_    (      self	:Optional[int]      )					->      Optional[Any]:







       '''simple docstring'''



       __A													=      self.tokenizer_class(self.vocab_file      )

       __A													=      'LAGVS'
       self.assertListEqual(tokenizer.encode(_A      )						,					[0, 4, 5, 6, 7, 8, 2]      )






 def 						lowercase_    (      self	:Any      )					->      Dict:







       '''simple docstring'''



       __A													=      self.tokenizer_class(self.vocab_file      )

       __A													=      ['LAGVS', 'WCB']
       __A													=      tokenizer(_A						,					padding=_A      )['input_ids']

       self.assertListEqual(_A						,					[[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2]]      )






 def 						lowercase_    (      self	:List[str]      )					->      Any:







       '''simple docstring'''



       __A													=      self.tokenizer_class(self.vocab_file      )

       __A													=      ['LAGVS', 'WCB']
       __A													=      tokenizer(_A						,					padding=_A      )['input_ids']

       self.assertListEqual(_A						,					[[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2, 1, 1]]      )






 def 						lowercase_    (      self	:Any      )					->      str:







       '''simple docstring'''



       __A													=      self.get_tokenizers(fast=_A      )
       for tokenizer in tokenizers:
             with self.subTest(F'{tokenizer.__class__.__name__}'      ):
                   __A													=      '<unk>'
                   __A													=      '<mask>'

                   __A													=      tokenizer.tokenize(_A      )
                   __A													=      tokenizer.tokenize(_A      )

                   self.assertEqual(len(_A      )						,					1      )
                   self.assertEqual(len(_A      )						,					1      )
                   self.assertEqual(token_a[0]						,					_A      )
                   self.assertEqual(token_a[0]						,					_A      )













# this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus

# 1. pip install sentencepiece
#
# 2. wget https://raw.githubusercontent.com/google/sentencepiece/master/data/botchan.txt

# 3. build
import sentencepiece as spm

# pegasus:
# 1. no bos
# 2. eos_id is 1
# 3. unk_id is 2
# build a sample spm file accordingly
spm.SentencePieceTrainer.train(
    "--input=botchan.txt --model_prefix=test_sentencepiece_no_bos --bos_id=-1 --unk_id=2  --eos_id=1  --vocab_size=1000"
)

# 4. now update the fixture
# mv test_sentencepiece_no_bos.model ../../tests/fixtures/

