

"""simple docstring"""


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

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


if is_sentencepiece_available():
			from .tokenization_pegasus import PegasusTokenizer
else:
			__A						   =			None


__A						   =			logging.get_logger(__name__)


__A						   =			"▁"

__A						   =			{"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

__A						   =			{
    "vocab_file": {"google/pegasus-xsum": "https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model"},
    "tokenizer_file": {
        "google/pegasus-xsum": "https://huggingface.co/google/pegasus-xsum/resolve/main/tokenizer.json"
    },
}

__A						   =			{
    "google/pegasus-xsum": 512,
}





class     snake_case	(				__snake_case  ):
				SCREAMING_SNAKE_CASE_   :      List[str]         =  VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_   :      Any         =  PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_   :      Optional[int]         =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_   :      str         =  PegasusTokenizer
				SCREAMING_SNAKE_CASE_   :      Any         =  ["""input_ids""", """attention_mask"""]

				def __init__(	self							:				str     ,  UpperCamelCase__							:				Tuple=None     ,  UpperCamelCase__							:				int=None     ,  UpperCamelCase__							:				Optional[int]="<pad>"     ,  UpperCamelCase__							:				Tuple="</s>"     ,  UpperCamelCase__							:				Tuple="<unk>"     ,  UpperCamelCase__							:				str="<mask_2>"     ,  UpperCamelCase__							:				str="<mask_1>"     ,  UpperCamelCase__							:				Optional[Any]=None     ,  UpperCamelCase__							:				Tuple=1_0_3     ,  **UpperCamelCase__							:				List[str]     ,  )->   List[str]:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[Any]          =			offset

						if additional_special_tokens is not None:
								if not isinstance(UpperCamelCase__     ,  UpperCamelCase__):
										raise TypeError(
										    f"additional_special_tokens should be of type {type(UpperCamelCase__)}, but is"
										    f" {type(UpperCamelCase__)}")

								__lowerCAmelCase:       Optional[Any]          =			(
								    ([mask_token_sent] + additional_special_tokens)
								    if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
								    else additional_special_tokens
								)
								# fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
								additional_special_tokens_extended += [
								    f"<unk_{i}>" for i in range(len(UpperCamelCase__)     ,  self.offset - 1)
								]

								if len(set(UpperCamelCase__)) != len(UpperCamelCase__):
										raise ValueError(
										    "Please make sure that the provided additional_special_tokens do not contain an incorrectly"
										    f" shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}.")
								__lowerCAmelCase:       List[str]          =			additional_special_tokens_extended
						else:
								__lowerCAmelCase:       Dict          =			[mask_token_sent] if mask_token_sent is not None else []
								additional_special_tokens += [f"<unk_{i}>" for i in range(2     ,  self.offset)]

						super().__init__(
						    UpperCamelCase__     ,  tokenizer_file=UpperCamelCase__     ,  pad_token=UpperCamelCase__     ,  eos_token=UpperCamelCase__     ,  unk_token=UpperCamelCase__     ,  mask_token=UpperCamelCase__     ,  mask_token_sent=UpperCamelCase__     ,  offset=UpperCamelCase__     ,  additional_special_tokens=UpperCamelCase__     ,  **UpperCamelCase__     ,  )
						__lowerCAmelCase:       Dict          =			vocab_file
						__lowerCAmelCase:       List[str]          =			False if not self.vocab_file else True

				def 							lowercase_     (	self							:				Optional[Any]     ,  UpperCamelCase__							:				Tuple)->   str:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			set(self.all_special_ids)  # call it once instead of inside list comp
						all_special_ids.remove(self.unk_token_id)  # <unk> is only sometimes special

						if all_special_ids != set(range(len(self.additional_special_tokens) + 3)):
								raise ValueError(
								    "There should be 3 special tokens: mask_token, pad_token, and eos_token +"
								    f" {len(self.additional_special_tokens)} additional_special_tokens, but got {all_special_ids}")

						return [1 if x in all_special_ids else 0 for x in seq]

				def 							lowercase_     (	self							:				Union[str, Any]     ,  UpperCamelCase__							:				List     ,  UpperCamelCase__							:				Optional[List] = None     ,  UpperCamelCase__							:				bool = False)->   List[int]:



						'''simple docstring'''


						if already_has_special_tokens:
								return self._special_token_mask(UpperCamelCase__)
						elif token_ids_a is None:
								return self._special_token_mask(UpperCamelCase__) + [1]
						else:
								return self._special_token_mask(token_ids_a + token_ids_a) + [1]

				def 							lowercase_     (	self							:				Dict     ,  UpperCamelCase__							:				Any     ,  UpperCamelCase__							:				Tuple=None)->   List[int]:



						'''simple docstring'''


						if token_ids_a is None:
								return token_ids_a + [self.eos_token_id]
						# We don't expect to process pairs, but leave the pair logic for API consistency
						return token_ids_a + token_ids_a + [self.eos_token_id]




				def 							lowercase_     (	self							:				List[str]     ,  UpperCamelCase__							:				str     ,  UpperCamelCase__							:				Optional[str] = None)->   Tuple[str]:



						'''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(UpperCamelCase__):
								logger.error(f"Vocabulary path ({save_directory}) should be a directory")
								return
						__lowerCAmelCase:       Union[str, Any]          =			os.path.join(
						    UpperCamelCase__     ,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"])

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

						return (out_vocab_file,)





"""simple docstring"""


from urllib.parse import quote

import pytest

from datasets.utils.hub import hf_hub_url






@pytest.mark.parametrize("repo_id"					, ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path"					, ["filename.csv", "filename with blanks.csv"] )
@pytest.mark.parametrize("revision"					, [None, "v2"] )
def     a__    (    __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE					, __SCREAMING_SNAKE_CASE )	->	List[str]:
		__lowerCAmelCase:       Optional[Any]          =			hf_hub_url(repo_id=__SCREAMING_SNAKE_CASE					, path=__SCREAMING_SNAKE_CASE					, revision=__SCREAMING_SNAKE_CASE )
		assert url == F"https://huggingface.co/datasets/{repo_id}/resolve/{revision or 'main'}/{quote(__SCREAMING_SNAKE_CASE )}"


