


import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
 from .tokenization_albert import AlbertTokenizer
else:
 A	:		Dict    =       None

A	:		Tuple    =       logging.get_logger(__name__)
A	:		Optional[int]    =       {'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

A	:		Optional[Any]    =       {
    'vocab_file': {
        'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/spiece.model',
        'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/spiece.model',
        'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model',
        'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model',
        'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/spiece.model',
        'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/spiece.model',
        'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model',
        'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/tokenizer.json',
        'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/tokenizer.json',
        'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/tokenizer.json',
        'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/tokenizer.json',
        'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/tokenizer.json',
        'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/tokenizer.json',
        'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/tokenizer.json',
        'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/tokenizer.json',
    },
}

A	:		str    =       {
    'albert-base-v1': 5_1_2,
    'albert-large-v1': 5_1_2,
    'albert-xlarge-v1': 5_1_2,
    'albert-xxlarge-v1': 5_1_2,
    'albert-base-v2': 5_1_2,
    'albert-large-v2': 5_1_2,
    'albert-xlarge-v2': 5_1_2,
    'albert-xxlarge-v2': 5_1_2,
}

A	:		Dict    =       '▁'



class 							A   (	_a							):
     '''simple docstring'''






     A__      =			VOCAB_FILES_NAMES
     A__      =			PRETRAINED_VOCAB_FILES_MAP
     A__      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     A__      =			AlbertTokenizer

     def __init__(self   :						int				, _UpperCAmelCase   :						Dict=None				, _UpperCAmelCase   :						str=None				, _UpperCAmelCase   :						Tuple=True				, _UpperCAmelCase   :						int=True				, _UpperCAmelCase   :						Optional[Any]=False				, _UpperCAmelCase   :						Any="[CLS]"				, _UpperCAmelCase   :						Any="[SEP]"				, _UpperCAmelCase   :						Tuple="<unk>"				, _UpperCAmelCase   :						str="[SEP]"				, _UpperCAmelCase   :						Union[str, Any]="<pad>"				, _UpperCAmelCase   :						List[str]="[CLS]"				, _UpperCAmelCase   :						List[str]="[MASK]"				, **_UpperCAmelCase   :						List[Any]				, )						->       Dict:




       """simple docstring"""


       lowercase__					      =		(
           AddedToken(__lowerCAmelCase				, lstrip=__lowerCAmelCase				, rstrip=__lowerCAmelCase				, normalized=__lowerCAmelCase		)
           if isinstance(__lowerCAmelCase				, __lowerCAmelCase		)
           else mask_token
       )

       super().__init__(
           __lowerCAmelCase				, tokenizer_file=__lowerCAmelCase				, do_lower_case=__lowerCAmelCase				, remove_space=__lowerCAmelCase				, keep_accents=__lowerCAmelCase				, bos_token=__lowerCAmelCase				, eos_token=__lowerCAmelCase				, unk_token=__lowerCAmelCase				, sep_token=__lowerCAmelCase				, pad_token=__lowerCAmelCase				, cls_token=__lowerCAmelCase				, mask_token=__lowerCAmelCase				, **__lowerCAmelCase				, )

       lowercase__					      =		do_lower_case
       lowercase__					      =		remove_space
       lowercase__					      =		keep_accents
       lowercase__					      =		vocab_file
       lowercase__					      =		False if not self.vocab_file else True

     def   lowerCamelCase__					(self   :						Optional[Any]				, _UpperCAmelCase   :						Dict				, _UpperCAmelCase   :						Dict = None		)						->       str:




       """simple docstring"""


       lowercase__					      =		[self.sep_token_id]
       lowercase__					      =		[self.cls_token_id]
       if token_ids_a is None:
         return cls + token_ids_a + sep
       return cls + token_ids_a + sep + token_ids_a + sep

     def   lowerCamelCase__					(self   :						Union[str, Any]				, _UpperCAmelCase   :						Optional[int]				, _UpperCAmelCase   :						Optional[Any] = None		)						->       Union[str, Any]:




       """simple docstring"""


       lowercase__					      =		[self.sep_token_id]
       lowercase__					      =		[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   :						List[Any]				, _UpperCAmelCase   :						Dict				, _UpperCAmelCase   :						Tuple = None		)						->       Optional[Any]:




       """simple docstring"""


       if not self.can_save_slow_tokenizer:
         raise ValueError(
             """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
             """tokenizer."""		)

       if not os.path.isdir(__lowerCAmelCase		):
         logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''		)
         return
       lowercase__					      =		os.path.join(
           __lowerCAmelCase				, (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]		)

       if os.path.abspath(self.vocab_file		) != os.path.abspath(__lowerCAmelCase		):
         copyfile(self.vocab_file				, __lowerCAmelCase		)

       return (out_vocab_file,)





import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class 							A   (	UpperCAmelCase__			,  unittest.TestCase							):
					'''simple docstring'''






					A__      =			OpenAIGPTTokenizer
					A__      =			OpenAIGPTTokenizerFast
					A__      =			True
					A__      =			False

					def   lowerCamelCase__					(self   :						List[str]		)						->       int:




							"""simple docstring"""


							super().setUp()

							# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
							lowercase__					      =		[
							    """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>""",
							]
							lowercase__					      =		dict(zip(_UpperCAmelCase				, range(len(_UpperCAmelCase		)		)		)		)
							lowercase__					      =		["""#version: 0.2""", """l o""", """lo w""", """e r</w>""", """"""]

							lowercase__					      =		os.path.join(self.tmpdirname				, VOCAB_FILES_NAMES["""vocab_file"""]		)
							lowercase__					      =		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   lowerCamelCase__					(self   :						Dict				, _UpperCAmelCase   :						List[Any]		)						->       Any:




							"""simple docstring"""


							return "lower newer", "lower newer"

					def   lowerCamelCase__					(self   :						Dict		)						->       Tuple:




							"""simple docstring"""


							lowercase__					      =		OpenAIGPTTokenizer(self.vocab_file				, self.merges_file		)

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

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

					def   lowerCamelCase__					(self   :						Optional[int]				, _UpperCAmelCase   :						Union[str, Any]=15		)						->       Optional[int]:




							"""simple docstring"""


							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
											lowercase__					      =		self.rust_tokenizer_class.from_pretrained(_UpperCAmelCase				, **_UpperCAmelCase		)

											# Simple input
											lowercase__					      =		"""This is a simple input"""
											lowercase__					      =		["""This is a simple input 1""", """This is a simple input 2"""]
											lowercase__					      =		("""This is a simple input""", """This is a pair""")
											lowercase__					      =		[
											    ("""This is a simple input 1""", """This is a simple input 2"""),
											    ("""This is a simple pair 1""", """This is a simple pair 2"""),
											]

											# Simple input tests
											self.assertRaises(_UpperCAmelCase				, tokenizer_r.encode				, _UpperCAmelCase				, max_length=_UpperCAmelCase				, padding="""max_length"""		)

											# Simple input
											self.assertRaises(_UpperCAmelCase				, tokenizer_r.encode_plus				, _UpperCAmelCase				, max_length=_UpperCAmelCase				, padding="""max_length"""		)

											# Simple input
											self.assertRaises(
											    _UpperCAmelCase				, tokenizer_r.batch_encode_plus				, _UpperCAmelCase				, max_length=_UpperCAmelCase				, padding="""max_length"""				, )

											# Pair input
											self.assertRaises(_UpperCAmelCase				, tokenizer_r.encode				, _UpperCAmelCase				, max_length=_UpperCAmelCase				, padding="""max_length"""		)

											# Pair input
											self.assertRaises(_UpperCAmelCase				, tokenizer_r.encode_plus				, _UpperCAmelCase				, max_length=_UpperCAmelCase				, padding="""max_length"""		)

											# Pair input
											self.assertRaises(
											    _UpperCAmelCase				, tokenizer_r.batch_encode_plus				, _UpperCAmelCase				, max_length=_UpperCAmelCase				, padding="""max_length"""				, )


					def   lowerCamelCase__					(self   :						Tuple		)						->       Any:




							"""simple docstring"""


							pass






@require_ftfy
@require_spacy
@require_tokenizers
class 							A   (	UpperCAmelCase__							):
					'''simple docstring'''






					pass

