





'''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 					SCREAMING_SNAKE_CASE       (a__   ,						unittest.TestCase				):
     lowerCAmelCase						     =			BioGptTokenizer
     lowerCAmelCase						     =			False


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          super().setUp()

          # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
          __A		:					Optional[int]						=			[
              '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		:					str						=			['l o 123', 'lo w 1456', 'e r</w> 1789', '']

          __A		:					Optional[Any]						=			os.path.join(self.tmpdirname		,      VOCAB_FILES_NAMES['vocab_file'])
          __A		:					Dict						=			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 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase):

          '''simple docstring'''






          __A		:					int						=			'lower newer'
          __A		:					int						=			'lower newer'
          return input_text, output_text


     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					Tuple						=			BioGptTokenizer(self.vocab_file		,      self.merges_file)

          __A		:					List[Any]						=			'lower'
          __A		:					Optional[int]						=			['low', 'er</w>']
          __A		:					Optional[Any]						=			tokenizer.tokenize(_UpperCAmelCase)
          self.assertListEqual(_UpperCAmelCase		,      _UpperCAmelCase)

          __A		:					List[Any]						=			tokens + ['<unk>']
          __A		:					Optional[int]						=			[14, 15, 20]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCAmelCase)		,      _UpperCAmelCase)


     @slow
     def 				SCREAMING_SNAKE_CASE    (		self):

          '''simple docstring'''






          __A		:					Any						=			BioGptTokenizer.from_pretrained('microsoft/biogpt')

          __A		:					Union[str, Any]						=			tokenizer.encode('sequence builders'		,      add_special_tokens=_UpperCAmelCase)
          __A		:					Any						=			tokenizer.encode('multi-sequence build'		,      add_special_tokens=_UpperCAmelCase)

          __A		:					Any						=			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 json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer


__lowerCamelCase							=  logging.get_logger(__name__)

__lowerCamelCase							=  {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

__lowerCamelCase							=  {
    'vocab_file': {
        'squeezebert/squeezebert-uncased': (
            'https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/vocab.txt'
        ),
        'squeezebert/squeezebert-mnli': 'https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/vocab.txt',
        'squeezebert/squeezebert-mnli-headless': (
            'https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/vocab.txt'
        ),
    },
    'tokenizer_file': {
        'squeezebert/squeezebert-uncased': (
            'https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/tokenizer.json'
        ),
        'squeezebert/squeezebert-mnli': (
            'https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/tokenizer.json'
        ),
        'squeezebert/squeezebert-mnli-headless': (
            'https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/tokenizer.json'
        ),
    },
}

__lowerCamelCase							=  {
    'squeezebert/squeezebert-uncased': 5_12,
    'squeezebert/squeezebert-mnli': 5_12,
    'squeezebert/squeezebert-mnli-headless': 5_12,
}


__lowerCamelCase							=  {
    'squeezebert/squeezebert-uncased': {'do_lower_case': True},
    'squeezebert/squeezebert-mnli': {'do_lower_case': True},
    'squeezebert/squeezebert-mnli-headless': {'do_lower_case': True},
}



class       __A		(   SCREAMING_SNAKE_CASE_			):
					UpperCAmelCase__								=				VOCAB_FILES_NAMES
					UpperCAmelCase__								=				PRETRAINED_VOCAB_FILES_MAP
					UpperCAmelCase__								=				PRETRAINED_INIT_CONFIGURATION
					UpperCAmelCase__								=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					UpperCAmelCase__								=				SqueezeBertTokenizer

					def __init__(			self  :      Tuple     ,		__snake_case  :      str=None     ,		__snake_case  :      Optional[Any]=None     ,		__snake_case  :      str=True     ,		__snake_case  :      str="[UNK]"     ,		__snake_case  :      int="[SEP]"     ,		__snake_case  :      int="[PAD]"     ,		__snake_case  :      Any="[CLS]"     ,		__snake_case  :      List[Any]="[MASK]"     ,		__snake_case  :      Union[str, Any]=True     ,		__snake_case  :      Dict=None     ,		**__snake_case  :      str     ,		)			->							List[Any]:
											super().__init__(
											    __snake_case     ,		tokenizer_file=__snake_case     ,		do_lower_case=__snake_case     ,		unk_token=__snake_case     ,		sep_token=__snake_case     ,		pad_token=__snake_case     ,		cls_token=__snake_case     ,		mask_token=__snake_case     ,		tokenize_chinese_chars=__snake_case     ,		strip_accents=__snake_case     ,		**__snake_case     ,		)

											__magic_name__:	List[Any]							=       json.loads(self.backend_tokenizer.normalizer.__getstate__()					)
											if (
											    normalizer_state.get("""lowercase"""     ,		__snake_case					) != do_lower_case
											    or normalizer_state.get("""strip_accents"""     ,		__snake_case					) != strip_accents
											    or normalizer_state.get("""handle_chinese_chars"""     ,		__snake_case					) != tokenize_chinese_chars
											):
																	__magic_name__:	Dict							=       getattr(__snake_case     ,		normalizer_state.pop("""type"""					)					)
																	__magic_name__:	Optional[Any]							=       do_lower_case
																	__magic_name__:	Any							=       strip_accents
																	__magic_name__:	Any							=       tokenize_chinese_chars
																	__magic_name__:	Union[str, Any]							=       normalizer_class(**__snake_case					)

											__magic_name__:	Optional[Any]							=       do_lower_case

					def   lowerCamelCase__   (			self  :      Optional[Any]     ,		__snake_case  :      List[Any]     ,		__snake_case  :      int=None					)			->							Optional[int]:
											__magic_name__:	int							=       [self.cls_token_id] + token_ids_a + [self.sep_token_id]

											if token_ids_a:
																	output += token_ids_a + [self.sep_token_id]

											return output

					def   lowerCamelCase__   (			self  :      Any     ,		__snake_case  :      List[int]     ,		__snake_case  :      Optional[List[int]] = None					)			->							List[int]:
											__magic_name__:	Dict							=       [self.sep_token_id]
											__magic_name__:	List[str]							=       [self.cls_token_id]
											if token_ids_a is None:
																	return len(cls + token_ids_a + sep					) * [0]
											return len(cls + token_ids_a + sep					) * [0] + len(token_ids_a + sep					) * [1]






					def   lowerCamelCase__   (			self  :      Dict     ,		__snake_case  :      str     ,		__snake_case  :      Optional[str] = None					)			->							Tuple[str]:
											__magic_name__:	Any							=       self._tokenizer.model.save(__snake_case     ,		name=__snake_case					)
											return tuple(__snake_case					)



