
'''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  snake_case_		(    __SCREAMING_SNAKE_CASE :			Optional[int]				,				__SCREAMING_SNAKE_CASE :			Optional[int]				,				__SCREAMING_SNAKE_CASE :			List[Any]							):



						"""simple docstring"""





						lowercase_     :					Any													=	hf_hub_url(repo_id=_A				,				path=_A				,				revision=_A							)
						assert url == F'''https://huggingface.co/datasets/{repo_id}/resolve/{revision or 'main'}/{quote(_A							)}'''





'''simple docstring'''







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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_lowercase			:  Optional[Any]   							=	logging.get_logger(__name__)

_lowercase			:  str   							=	"▁"

_lowercase			:  Optional[int]   							=	{"vocab_file": "sentencepiece.bpe.model"}

_lowercase			:  Dict   							=	{
    "vocab_file": {
        "facebook/xglm-564M": "https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model",
    }
}

_lowercase			:  Optional[Any]   							=	{
    "facebook/xglm-564M": 2_0_4_8,
}






class 			lowerCAmelCase__       (  lowerCamelCase_					):
					lowerCAmelCase_					       =					VOCAB_FILES_NAMES
					lowerCAmelCase_					       =					PRETRAINED_VOCAB_FILES_MAP
					lowerCAmelCase_					       =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowerCAmelCase_					       =					['''input_ids''', '''attention_mask''']






					def __init__(       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE="<s>"    ,							__SCREAMING_SNAKE_CASE="</s>"    ,							__SCREAMING_SNAKE_CASE="</s>"    ,							__SCREAMING_SNAKE_CASE="<s>"    ,							__SCREAMING_SNAKE_CASE="<unk>"    ,							__SCREAMING_SNAKE_CASE="<pad>"    ,							__SCREAMING_SNAKE_CASE = None    ,							**__SCREAMING_SNAKE_CASE    ,							):


											"""simple docstring"""





											lowercase_     :					Any													=	{} if sp_model_kwargs is None else sp_model_kwargs

											# Compatibility with the original tokenizer
											lowercase_     :					Optional[Any]													=	7
											lowercase_     :					List[Any]													=	[F'''<madeupword{i}>''' for i in range(self.num_madeup_words		)]

											lowercase_     :					Tuple													=	kwargs.get('''additional_special_tokens'''    ,							[]		)
											kwargs["additional_special_tokens"] += [
											    word for word in madeup_words if word not in kwargs["additional_special_tokens"]
											]

											super().__init__(
											    bos_token=__SCREAMING_SNAKE_CASE    ,							eos_token=__SCREAMING_SNAKE_CASE    ,							unk_token=__SCREAMING_SNAKE_CASE    ,							sep_token=__SCREAMING_SNAKE_CASE    ,							cls_token=__SCREAMING_SNAKE_CASE    ,							pad_token=__SCREAMING_SNAKE_CASE    ,							sp_model_kwargs=self.sp_model_kwargs    ,							**__SCREAMING_SNAKE_CASE    ,							)

											lowercase_     :					int													=	spm.SentencePieceProcessor(**self.sp_model_kwargs		)
											self.sp_model.Load(str(__SCREAMING_SNAKE_CASE		)		)
											lowercase_     :					Dict													=	vocab_file

											# Original fairseq vocab and spm vocab must be "aligned":
											# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
											# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
											# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
											# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

											# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
											lowercase_     :					List[Any]													=	1

											# Mimic fairseq token-to-id alignment for the first 4 token
											lowercase_     :					Optional[Any]													=	{'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

											lowercase_     :					Dict													=	len(self.sp_model		)
											lowercase_     :					int													=	{F'''<madeupword{i}>''': sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words		)}
											self.fairseq_tokens_to_ids.update(__SCREAMING_SNAKE_CASE		)

											lowercase_     :					List[str]													=	{v: k for k, v in self.fairseq_tokens_to_ids.items()}






					def __getstate__(       self		):


											"""simple docstring"""





											lowercase_     :					List[Any]													=	self.__dict__.copy()
											lowercase_     :					Optional[Any]													=	None
											lowercase_     :					List[Any]													=	self.sp_model.serialized_model_proto()
											return state






					def __setstate__(       self    ,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											lowercase_     :					List[Any]													=	d

											# for backward compatibility
											if not hasattr(self    ,							'''sp_model_kwargs'''		):
																	lowercase_     :					Optional[Any]													=	{}

											lowercase_     :					int													=	spm.SentencePieceProcessor(**self.sp_model_kwargs		)
											self.sp_model.LoadFromSerializedProto(self.sp_model_proto		)






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE = None		):


											"""simple docstring"""





											if token_ids_a is None:
																	return [self.sep_token_id] + token_ids_a
											lowercase_     :					Optional[Any]													=	[self.sep_token_id]
											return sep + token_ids_a + sep + sep + token_ids_a






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE = None    ,							__SCREAMING_SNAKE_CASE = False		):


											"""simple docstring"""





											if already_has_special_tokens:
																	return super().get_special_tokens_mask(
																	    token_ids_a=__SCREAMING_SNAKE_CASE    ,							token_ids_a=__SCREAMING_SNAKE_CASE    ,							already_has_special_tokens=__SCREAMING_SNAKE_CASE		)

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






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE = None		):


											"""simple docstring"""





											lowercase_     :					List[Any]													=	[self.sep_token_id]

											if token_ids_a is None:
																	return len(sep + token_ids_a		) * [0]
											return len(sep + token_ids_a + sep + sep + token_ids_a		) * [0]






					@property
					def      _snake_case   (       self		):


											"""simple docstring"""





											return len(self.sp_model		) + self.fairseq_offset + self.num_madeup_words






					def      _snake_case   (       self		):


											"""simple docstring"""





											lowercase_     :					Any													=	{self.convert_ids_to_tokens(__SCREAMING_SNAKE_CASE		): i for i in range(self.vocab_size		)}
											vocab.update(self.added_tokens_encoder		)
											return vocab






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											return self.sp_model.encode(__SCREAMING_SNAKE_CASE    ,							out_type=__SCREAMING_SNAKE_CASE		)






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											if token in self.fairseq_tokens_to_ids:
																	return self.fairseq_tokens_to_ids[token]
											lowercase_     :					str													=	self.sp_model.PieceToId(__SCREAMING_SNAKE_CASE		)

											# Need to return unknown token if the SP model returned 0
											return spm_id + self.fairseq_offset if spm_id else self.unk_token_id






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											if index in self.fairseq_ids_to_tokens:
																	return self.fairseq_ids_to_tokens[index]
											return self.sp_model.IdToPiece(index - self.fairseq_offset		)






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE		):


											"""simple docstring"""





											lowercase_     :					Dict													=	''''''.join(__SCREAMING_SNAKE_CASE		).replace(__SCREAMING_SNAKE_CASE    ,							''' '''		).strip()
											return out_string






					def      _snake_case   (       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE = None		):


											"""simple docstring"""





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

											if os.path.abspath(self.vocab_file		) != os.path.abspath(__SCREAMING_SNAKE_CASE		) and os.path.isfile(self.vocab_file		):
																	copyfile(self.vocab_file    ,							__SCREAMING_SNAKE_CASE		)
											elif not os.path.isfile(self.vocab_file		):
																	with open(__SCREAMING_SNAKE_CASE    ,							'''wb'''		) as fi:
																							lowercase_     :					Optional[int]													=	self.sp_model.serialized_model_proto()
																							fi.write(__SCREAMING_SNAKE_CASE		)

											return (out_vocab_file,)



