






import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowercase  							=					logging.get_logger(__name__)


lowercase  							=					{"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all BART models at https://huggingface.co/models?filter=bart
lowercase  							=					{
    "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",
    },
}

lowercase  							=					{
    "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,
}





@lru_cache()
def 						__UpperCAmelCase			(     ):
							snake_case_				=							(
							    list(range(ord('!')							,     ord('~') + 1)) + list(range(ord('¡')							,     ord('¬') + 1)) + list(range(ord('®')							,     ord('ÿ') + 1))
							)
							snake_case_				=							bs[:]
							snake_case_				=							0
							for b in range(2**8):
														if b not in bs:
																					bs.append(a_)
																					cs.append(2**8 + n)
																					n += 1
							snake_case_				=							[chr(a_) for n in cs]
							return dict(zip(a_							,     a_))





def 						__UpperCAmelCase			(     a_):
							snake_case_				=							set()
							snake_case_				=							word[0]
							for char in word[1:]:
														pairs.add((prev_char, char))
														snake_case_				=							char
							return pairs




class  UpperCamelCase_      (			snake_case_				):



	'''simple docstring'''




	lowerCAmelCase													= VOCAB_FILES_NAMES
	lowerCAmelCase													= PRETRAINED_VOCAB_FILES_MAP
	lowerCAmelCase													= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	lowerCAmelCase													= ['''input_ids''', '''attention_mask''']




	def __init__(       self       ,			a       ,			a       ,			a="replace"       ,			a="<s>"       ,			a="</s>"       ,			a="</s>"       ,			a="<s>"       ,			a="<unk>"       ,			a="<pad>"       ,			a="<mask>"       ,			a=False       ,			**a       ,			)       ->    List[Any]:
								snake_case_				=							AddedToken(a       ,			lstrip=a       ,			rstrip=a					) if isinstance(a       ,			a					) else bos_token
								snake_case_				=							AddedToken(a       ,			lstrip=a       ,			rstrip=a					) if isinstance(a       ,			a					) else eos_token
								snake_case_				=							AddedToken(a       ,			lstrip=a       ,			rstrip=a					) if isinstance(a       ,			a					) else sep_token
								snake_case_				=							AddedToken(a       ,			lstrip=a       ,			rstrip=a					) if isinstance(a       ,			a					) else cls_token
								snake_case_				=							AddedToken(a       ,			lstrip=a       ,			rstrip=a					) if isinstance(a       ,			a					) else unk_token
								snake_case_				=							AddedToken(a       ,			lstrip=a       ,			rstrip=a					) if isinstance(a       ,			a					) else pad_token

								# Mask token behave like a normal word, i.e. include the space before it
								snake_case_				=							AddedToken(a       ,			lstrip=a       ,			rstrip=a					) if isinstance(a       ,			a					) else mask_token

								super().__init__(
								    errors=a       ,			bos_token=a       ,			eos_token=a       ,			unk_token=a       ,			sep_token=a       ,			cls_token=a       ,			pad_token=a       ,			mask_token=a       ,			add_prefix_space=a       ,			**a       ,			)

								with open(a       ,			encoding='utf-8'					) as vocab_handle:
															snake_case_				=							json.load(a					)
								snake_case_				=							{v: k for k, v in self.encoder.items()}
								snake_case_				=							errors  # how to handle errors in decoding
								snake_case_				=							bytes_to_unicode()
								snake_case_				=							{v: k for k, v in self.byte_encoder.items()}
								with open(a       ,			encoding='utf-8'					) as merges_handle:
															snake_case_				=							merges_handle.read().split('\n'					)[1:-1]
								snake_case_				=							[tuple(merge.split()					) for merge in bpe_merges]
								snake_case_				=							dict(zip(a       ,			range(len(a					)					)					)					)
								snake_case_				=							{}
								snake_case_				=							add_prefix_space

								# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
								snake_case_				=							re.compile(R'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'					)




	@property
	def 							_UpperCamelCase			(       self					)       ->    List[str]:
								return len(self.encoder					)




	def 							_UpperCamelCase			(       self					)       ->    Any:
								return dict(self.encoder       ,			**self.added_tokens_encoder					)




	def 							_UpperCamelCase			(       self       ,			a					)       ->    Union[str, Any]:
								if token in self.cache:
															return self.cache[token]
								snake_case_				=							tuple(a					)
								snake_case_				=							get_pairs(a					)

								if not pairs:
															return token

								while True:
															snake_case_				=							min(a       ,			key=lambda a					: self.bpe_ranks.get(a       ,			float('inf'					)					)					)
															if bigram not in self.bpe_ranks:
																						break
															snake_case_			,		snake_case_				=							bigram
															snake_case_				=							[]
															snake_case_				=							0
															while i < len(a					):
																						try:
																													snake_case_				=							word.index(a       ,			a					)
																						except ValueError:
																													new_word.extend(word[i:]					)
																													break
																						else:
																													new_word.extend(word[i:j]					)
																													snake_case_				=							j

																						if word[i] == first and i < len(a					) - 1 and word[i + 1] == second:
																													new_word.append(first + second					)
																													i += 2
																						else:
																													new_word.append(word[i]					)
																													i += 1
															snake_case_				=							tuple(a					)
															snake_case_				=							new_word
															if len(a					) == 1:
																						break
															else:
																						snake_case_				=							get_pairs(a					)
								snake_case_				=							' '.join(a					)
								snake_case_				=							word
								return word




	def 							_UpperCamelCase			(       self       ,			a					)       ->    str:
								snake_case_				=							[]
								for token in re.findall(self.pat       ,			a					):
															snake_case_				=							''.join(
															    self.byte_encoder[b] for b in token.encode('utf-8'					)					)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
															bpe_tokens.extend(bpe_token for bpe_token in self.bpe(a					).split(' '					)					)
								return bpe_tokens




	def 							_UpperCamelCase			(       self       ,			a					)       ->    Union[str, Any]:
								return self.encoder.get(a       ,			self.encoder.get(self.unk_token					)					)




	def 							_UpperCamelCase			(       self       ,			a					)       ->    Optional[int]:
								return self.decoder.get(a					)




	def 							_UpperCamelCase			(       self       ,			a					)       ->    Optional[Any]:
								snake_case_				=							''.join(a					)
								snake_case_				=							bytearray([self.byte_decoder[c] for c in text]					).decode('utf-8'       ,			errors=self.errors					)
								return text




	def 							_UpperCamelCase			(       self       ,			a       ,			a = None					)       ->    Tuple[str]:
								if not os.path.isdir(a					):
															logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''					)
															return
								snake_case_				=							os.path.join(
								    a       ,			(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']					)
								snake_case_				=							os.path.join(
								    a       ,			(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']					)

								with open(a       ,			'w'       ,			encoding='utf-8'					) as f:
															f.write(json.dumps(self.encoder       ,			indent=2       ,			sort_keys=a       ,			ensure_ascii=a					) + '\n'					)

								snake_case_				=							0
								with open(a       ,			'w'       ,			encoding='utf-8'					) as writer:
															writer.write('#version: 0.2\n'					)
															for bpe_tokens, token_index in sorted(self.bpe_ranks.items()       ,			key=lambda a					: kv[1]					):
																						if index != token_index:
																													logger.warning(
																													    F'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
																													    ' Please check that the tokenizer is not corrupted!'					)
																													snake_case_				=							token_index
																						writer.write(' '.join(a					) + '\n'					)
																						index += 1

								return vocab_file, merge_file




	def 							_UpperCamelCase			(       self       ,			a       ,			a = None					)       ->    List[int]:
								if token_ids_a is None:
															return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								snake_case_				=							[self.cls_token_id]
								snake_case_				=							[self.sep_token_id]
								return cls + token_ids_a + sep + sep + token_ids_a + sep




	def 							_UpperCamelCase			(       self       ,			a       ,			a = None       ,			a = False					)       ->    List[int]:
								if already_has_special_tokens:
															return super().get_special_tokens_mask(
															    token_ids_a=a       ,			token_ids_a=a       ,			already_has_special_tokens=a					)

								if token_ids_a is None:
															return [1] + ([0] * len(a					)) + [1]
								return [1] + ([0] * len(a					)) + [1, 1] + ([0] * len(a					)) + [1]




	def 							_UpperCamelCase			(       self       ,			a       ,			a = None					)       ->    List[int]:
								snake_case_				=							[self.sep_token_id]
								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]






	def 							_UpperCamelCase			(       self       ,			a       ,			a=False       ,			**a					)       ->    Optional[Any]:
								snake_case_				=							kwargs.pop('add_prefix_space'       ,			self.add_prefix_space					)
								if (is_split_into_words or add_prefix_space) and (len(a					) > 0 and not text[0].isspace()):
															snake_case_				=							' ' + text
								return (text, kwargs)













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


lowercase  							=					{
    "configuration_tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig"],
    "tokenization_tapas": ["TapasTokenizer"],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase  							=					[
	    "TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "TapasForMaskedLM",
	    "TapasForQuestionAnswering",
	    "TapasForSequenceClassification",
	    "TapasModel",
	    "TapasPreTrainedModel",
	    "load_tf_weights_in_tapas",
	]
try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowercase  							=					[
	    "TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "TFTapasForMaskedLM",
	    "TFTapasForQuestionAnswering",
	    "TFTapasForSequenceClassification",
	    "TFTapasModel",
	    "TFTapasPreTrainedModel",
	]


if TYPE_CHECKING:
	from .configuration_tapas import TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP, TapasConfig
	from .tokenization_tapas import TapasTokenizer

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tapas import (
		    TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TapasForMaskedLM,
		    TapasForQuestionAnswering,
		    TapasForSequenceClassification,
		    TapasModel,
		    TapasPreTrainedModel,
		    load_tf_weights_in_tapas,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_tapas import (
		    TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFTapasForMaskedLM,
		    TFTapasForQuestionAnswering,
		    TFTapasForSequenceClassification,
		    TFTapasModel,
		    TFTapasPreTrainedModel,
		)


else:
	import sys

	lowercase  							=					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





