



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  snake_case__(lowercase_							,     unittest.TestCase     ):

					"""simple docstring"""






					lowercase_								=						OpenAIGPTTokenizer
					lowercase_								=						OpenAIGPTTokenizerFast
					lowercase_								=						True
					lowercase_								=						False







					def 					snake_case	(				self   :      int	):
									super().setUp()

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

									lowercase__	:       str						=	os.path.join(self.tmpdirname ,  VOCAB_FILES_NAMES["vocab_file"]	)
									lowercase__	:       List[Any]						=	os.path.join(self.tmpdirname ,  VOCAB_FILES_NAMES["merges_file"]	)
									with open(self.vocab_file ,  "w"	) as fp:
													fp.write(json.dumps(_lowercase	)	)
									with open(self.merges_file ,  "w"	) as fp:
													fp.write("\n".join(_lowercase	)	)







					def 					snake_case	(				self   :      int ,  SCREAMING_SNAKE_CASE   :      int	):
									return "lower newer", "lower newer"







					def 					snake_case	(				self   :      List[Any]	):
									lowercase__	:       str						=	OpenAIGPTTokenizer(self.vocab_file ,  self.merges_file	)

									lowercase__	:       Optional[int]						=	"lower"
									lowercase__	:       Union[str, Any]						=	["low", "er</w>"]
									lowercase__	:       Optional[int]						=	tokenizer.tokenize(_lowercase	)
									self.assertListEqual(_lowercase ,  _lowercase	)

									lowercase__	:       int						=	tokens + ["<unk>"]
									lowercase__	:       Optional[Any]						=	[14, 15, 20]
									self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowercase	) ,  _lowercase	)







					def 					snake_case	(				self   :      Optional[Any] ,  SCREAMING_SNAKE_CASE   :      Union[str, Any]=15	):
									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""	):
																	lowercase__	:       Any						=	self.rust_tokenizer_class.from_pretrained(_lowercase ,  **_lowercase	)

																	# Simple input
																	lowercase__	:       str						=	"This is a simple input"
																	lowercase__	:       List[Any]						=	["This is a simple input 1", "This is a simple input 2"]
																	lowercase__	:       Optional[int]						=	("This is a simple input", "This is a pair")
																	lowercase__	:       List[str]						=	[
																	    ("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(_lowercase ,  tokenizer_r.encode ,  _lowercase ,  max_length=_lowercase ,  padding="max_length"	)

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

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

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

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

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







					def 					snake_case	(				self   :      Optional[int]	):
									pass






@require_ftfy
@require_spacy
@require_tokenizers
class  snake_case__(lowercase_     ):

					"""simple docstring"""






					pass







'''simple docstring'''

import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer


SCREAMING_SNAKE_CASE							:				int     	=			logging.get_logger(__name__)


SCREAMING_SNAKE_CASE							:				Dict     	=			{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

# See all BART models at https://huggingface.co/models?filter=bart
SCREAMING_SNAKE_CASE							:				str     	=			{
    "vocab_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/vocab.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/vocab.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json",
    },
    "merges_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/merges.txt",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/merges.txt",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json",
    },
}

SCREAMING_SNAKE_CASE							:				Union[str, Any]     	=			{
    "facebook/bart-base": 1024,
    "facebook/bart-large": 1024,
    "facebook/bart-large-mnli": 1024,
    "facebook/bart-large-cnn": 1024,
    "facebook/bart-large-xsum": 1024,
    "yjernite/bart_eli5": 1024,
}






class    snake_case     (      lowercase_		):






				"""simple docstring"""
				_a    	=     VOCAB_FILES_NAMES
				_a    	=     PRETRAINED_VOCAB_FILES_MAP
				_a    	=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_a    	=     ["""input_ids""", """attention_mask"""]
				_a    	=     BartTokenizer



				def __init__(    self,     _lowercase=None,     _lowercase=None,     _lowercase=None,     _lowercase="replace",     _lowercase="<s>",     _lowercase="</s>",     _lowercase="</s>",     _lowercase="<s>",     _lowercase="<unk>",     _lowercase="<pad>",     _lowercase="<mask>",     _lowercase=False,     _lowercase=True,     **_lowercase,     )     ->							Dict:
											super().__init__(
											    _lowercase,     _lowercase,     tokenizer_file=_lowercase,     errors=_lowercase,     bos_token=_lowercase,     eos_token=_lowercase,     sep_token=_lowercase,     cls_token=_lowercase,     unk_token=_lowercase,     pad_token=_lowercase,     mask_token=_lowercase,     add_prefix_space=_lowercase,     trim_offsets=_lowercase,     **_lowercase,     )

											SCREAMING_SNAKE_CASE_				=				json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()       )
											if pre_tok_state.get('add_prefix_space',     _lowercase       ) != add_prefix_space:
																		SCREAMING_SNAKE_CASE_				=				getattr(_lowercase,     pre_tok_state.pop('type'       )       )
																		SCREAMING_SNAKE_CASE_				=				add_prefix_space
																		SCREAMING_SNAKE_CASE_				=				pre_tok_class(**_lowercase       )

											SCREAMING_SNAKE_CASE_				=				add_prefix_space

											# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
											SCREAMING_SNAKE_CASE_				=				'post_processor'
											SCREAMING_SNAKE_CASE_				=				getattr(self.backend_tokenizer,     _lowercase,     _lowercase       )
											if tokenizer_component_instance:
																		SCREAMING_SNAKE_CASE_				=				json.loads(tokenizer_component_instance.__getstate__()       )

																		# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
																		if "sep" in state:
																									SCREAMING_SNAKE_CASE_				=				tuple(state['sep']       )
																		if "cls" in state:
																									SCREAMING_SNAKE_CASE_				=				tuple(state['cls']       )

																		SCREAMING_SNAKE_CASE_				=				False

																		if state.get('add_prefix_space',     _lowercase       ) != add_prefix_space:
																									SCREAMING_SNAKE_CASE_				=				add_prefix_space
																									SCREAMING_SNAKE_CASE_				=				True

																		if state.get('trim_offsets',     _lowercase       ) != trim_offsets:
																									SCREAMING_SNAKE_CASE_				=				trim_offsets
																									SCREAMING_SNAKE_CASE_				=				True

																		if changes_to_apply:
																									SCREAMING_SNAKE_CASE_				=				getattr(_lowercase,     state.pop('type'       )       )
																									SCREAMING_SNAKE_CASE_				=				component_class(**_lowercase       )
																									setattr(self.backend_tokenizer,     _lowercase,     _lowercase       )



				@property
				def   a__					(    self       )     ->							str:
											if self._mask_token is None:
																		if self.verbose:
																									logger.error('Using mask_token, but it is not set yet.'       )
																		return None
											return str(self._mask_token       )



				@mask_token.setter
				def   a__					(    self,     _lowercase       )     ->							Dict:
											SCREAMING_SNAKE_CASE_				=				AddedToken(_lowercase,     lstrip=_lowercase,     rstrip=_lowercase       ) if isinstance(_lowercase,     _lowercase       ) else value
											SCREAMING_SNAKE_CASE_				=				value



				def   a__					(    self,     *_lowercase,     **_lowercase       )     ->							BatchEncoding:
											SCREAMING_SNAKE_CASE_				=				kwargs.get('is_split_into_words',     _lowercase       )

											if is_split_into_words and not self.add_prefix_space:
																		raise ValueError(
																		    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
																		    'to use it with pretokenized inputs.'       )

											return super()._batch_encode_plus(*_lowercase,     **_lowercase       )



				def   a__					(    self,     *_lowercase,     **_lowercase       )     ->							BatchEncoding:
											SCREAMING_SNAKE_CASE_				=				kwargs.get('is_split_into_words',     _lowercase       )

											if is_split_into_words and not self.add_prefix_space:
																		raise ValueError(
																		    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
																		    'to use it with pretokenized inputs.'       )

											return super()._encode_plus(*_lowercase,     **_lowercase       )



				def   a__					(    self,     _lowercase,     _lowercase = None       )     ->							Tuple[str]:
											SCREAMING_SNAKE_CASE_				=				self._tokenizer.model.save(_lowercase,     name=_lowercase       )
											return tuple(_lowercase       )



				def   a__					(    self,     _lowercase,     _lowercase=None       )     ->							Optional[Any]:
											SCREAMING_SNAKE_CASE_				=				[self.bos_token_id] + token_ids_a + [self.eos_token_id]
											if token_ids_a is None:
																		return output

											return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]





				def   a__					(    self,     _lowercase,     _lowercase = None       )     ->							List[int]:
											SCREAMING_SNAKE_CASE_				=				[self.sep_token_id]
											SCREAMING_SNAKE_CASE_				=				[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 + sep + token_ids_a + sep       ) * [0]





