



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

import sentencepiece as spm

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


lowerCAmelCase	:		str				=   logging.get_logger(__name__)

lowerCAmelCase	:		int				=   {'''vocab_file''': '''sentencepiece.model'''}

lowerCAmelCase	:		Tuple				=   {
    '''vocab_file''': {
        '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/sentencepiece.model''',
    },
}

lowerCAmelCase	:		Optional[int]				=   {
    '''google/rembert''': 2_5_6,
}






class 					UpperCAmelCase__	(		UpperCamelCase__ ):
					a      :     List[Any]        =							VOCAB_FILES_NAMES
					a      :     Optional[Any]        =							PRETRAINED_VOCAB_FILES_MAP
					a      :     Any        =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES



					def __init__(    self			,				UpperCamelCase			,				UpperCamelCase=False			,				UpperCamelCase=True			,				UpperCamelCase=True			,				UpperCamelCase="[CLS]"			,				UpperCamelCase="[SEP]"			,				UpperCamelCase="[UNK]"			,				UpperCamelCase="[SEP]"			,				UpperCamelCase="[PAD]"			,				UpperCamelCase="[CLS]"			,				UpperCamelCase="[MASK]"			,				**UpperCamelCase			,				)     ->			Union[str, Any]:
						super().__init__(
						    do_lower_case=UpperCamelCase			,				remove_space=UpperCamelCase			,				keep_accents=UpperCamelCase			,				bos_token=UpperCamelCase			,				eos_token=UpperCamelCase			,				unk_token=UpperCamelCase			,				sep_token=UpperCamelCase			,				pad_token=UpperCamelCase			,				cls_token=UpperCamelCase			,				mask_token=UpperCamelCase			,				**UpperCamelCase			,				)

						__lowerCAmelCase												=  do_lower_case
						__lowerCAmelCase												=  remove_space
						__lowerCAmelCase												=  keep_accents
						__lowerCAmelCase												=  vocab_file

						__lowerCAmelCase												=  spm.SentencePieceProcessor()
						self.sp_model.Load(UpperCamelCase     )



					@property
					def        UpperCAmelCase_ (    self     )     ->			Optional[Any]:
						return len(self.sp_model     )



					def        UpperCAmelCase_ (    self     )     ->			Optional[int]:
						__lowerCAmelCase												=  {self.convert_ids_to_tokens(UpperCamelCase     ): i for i in range(self.vocab_size     )}
						vocab.update(self.added_tokens_encoder     )
						return vocab



					def __getstate__(    self     )     ->			List[str]:
						__lowerCAmelCase												=  self.__dict__.copy()
						__lowerCAmelCase												=  None
						return state



					def __setstate__(    self			,				UpperCamelCase     )     ->			Optional[Any]:
						__lowerCAmelCase												=  d
						__lowerCAmelCase												=  spm.SentencePieceProcessor()
						self.sp_model.Load(self.vocab_file     )



					def        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase=False     )     ->			Any:
						__lowerCAmelCase												=  self.sp_model.EncodeAsPieces(UpperCamelCase     )
						return pieces



					def        UpperCAmelCase_ (    self			,				UpperCamelCase     )     ->			List[Any]:
						return self.sp_model.PieceToId(UpperCamelCase     )



					def        UpperCAmelCase_ (    self			,				UpperCamelCase     )     ->			Tuple:
						return self.sp_model.IdToPiece(UpperCamelCase     )



					def        UpperCAmelCase_ (    self			,				UpperCamelCase     )     ->			str:
						__lowerCAmelCase												=  self.sp_model.decode_pieces(UpperCamelCase     )
						return out_string



					def        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase = None     )     ->			List[int]:
						__lowerCAmelCase												=  [self.sep_token_id]
						__lowerCAmelCase												=  [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        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase = None			,				UpperCamelCase = False     )     ->			List[int]:

						if already_has_special_tokens:
							if token_ids_a is not None:
								raise ValueError(
								    "You should not supply a second sequence if the provided sequence of "
								    "ids is already formatted with special tokens for the model."     )
							return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

						if token_ids_a is not None:
							return [1] + ([0] * len(UpperCamelCase     )) + [1] + ([0] * len(UpperCamelCase     )) + [1]
						return [1] + ([0] * len(UpperCamelCase     )) + [1]



					def        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase = None     )     ->			List[int]:
						__lowerCAmelCase												=  [self.sep_token_id]
						__lowerCAmelCase												=  [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        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase = None     )     ->			Tuple[str]:
						if not os.path.isdir(UpperCamelCase     ):
							logger.error("Vocabulary path ({}) should be a directory".format(UpperCamelCase     )     )
							return
						__lowerCAmelCase												=  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'''



import io
import json

import fsspec
import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases



def   __lowerCAmelCase					(							lowerCamelCase   :						str				,		lowerCamelCase   :						Union[str, Any]					):






	'''simple docstring'''




	assert isinstance(lowerCamelCase				,		lowerCamelCase					)
	assert dataset.num_rows == 4
	assert dataset.num_columns == 3
	assert dataset.column_names == ["col_1", "col_2", "col_3"]
	for feature, expected_dtype in expected_features.items():
		assert dataset.features[feature].dtype == expected_dtype



@pytest.mark.parametrize("keep_in_memory"				,		[False, True]					)
def   __lowerCAmelCase					(							lowerCamelCase   :						Tuple				,		lowerCamelCase   :						int				,		lowerCamelCase   :						Optional[int]					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
		__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		cache_dir=lowerCamelCase				,		keep_in_memory=lowerCamelCase					).read()
	_check_json_dataset(lowerCamelCase				,		lowerCamelCase					)



@pytest.mark.parametrize(
    "features"				,		[
        None,
        {"col_1": "string", "col_2": "int64", "col_3": "float64"},
        {"col_1": "string", "col_2": "string", "col_3": "string"},
        {"col_1": "int32", "col_2": "int32", "col_3": "int32"},
        {"col_1": "float32", "col_2": "float32", "col_3": "float32"},
    ]				,		)
def   __lowerCAmelCase					(							lowerCamelCase   :						List[Any]				,		lowerCamelCase   :						int				,		lowerCamelCase   :						Dict					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	__lowerCAmelCase												=  features.copy() if features else default_expected_features
	__lowerCAmelCase												=  (
	    Features({feature: Value(lowerCamelCase					) for feature, dtype in features.items()}					) if features is not None else None
	)
	__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		features=lowerCamelCase				,		cache_dir=lowerCamelCase					).read()
	_check_json_dataset(lowerCamelCase				,		lowerCamelCase					)



@pytest.mark.parametrize(
    "features"				,		[
        None,
        {"col_3": "float64", "col_1": "string", "col_2": "int64"},
    ]				,		)
def   __lowerCAmelCase					(							lowerCamelCase   :						List[Any]				,		lowerCamelCase   :						Optional[int]				,		lowerCamelCase   :						Any					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_3": "float64", "col_1": "string", "col_2": "int64"}
	__lowerCAmelCase												=  features.copy() if features else default_expected_features
	__lowerCAmelCase												=  (
	    Features({feature: Value(lowerCamelCase					) for feature, dtype in features.items()}					) if features is not None else None
	)
	__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		features=lowerCamelCase				,		cache_dir=lowerCamelCase					).read()
	assert isinstance(lowerCamelCase				,		lowerCamelCase					)
	assert dataset.num_rows == 2
	assert dataset.num_columns == 3
	assert dataset.column_names == ["col_3", "col_1", "col_2"]
	for feature, expected_dtype in expected_features.items():
		assert dataset.features[feature].dtype == expected_dtype



def   __lowerCAmelCase					(							lowerCamelCase   :						Any				,		lowerCamelCase   :						Optional[int]					):






	'''simple docstring'''




	__lowerCAmelCase												=  {"col_2": "int64", "col_3": "float64", "col_1": "string"}
	__lowerCAmelCase												=  features.copy()
	__lowerCAmelCase												=  (
	    Features({feature: Value(lowerCamelCase					) for feature, dtype in features.items()}					) if features is not None else None
	)
	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		features=lowerCamelCase				,		cache_dir=lowerCamelCase					).read()
	assert isinstance(lowerCamelCase				,		lowerCamelCase					)
	assert dataset.num_rows == 2
	assert dataset.num_columns == 3
	assert dataset.column_names == ["col_2", "col_3", "col_1"]
	for feature, expected_dtype in expected_features.items():
		assert dataset.features[feature].dtype == expected_dtype



@pytest.mark.parametrize("split"				,		[None, NamedSplit("train"					), "train", "test"]					)
def   __lowerCAmelCase					(							lowerCamelCase   :						List[Any]				,		lowerCamelCase   :						Optional[Any]				,		lowerCamelCase   :						Union[str, Any]					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		cache_dir=lowerCamelCase				,		split=lowerCamelCase					).read()
	_check_json_dataset(lowerCamelCase				,		lowerCamelCase					)
	assert dataset.split == split if split else "train"



@pytest.mark.parametrize("path_type"				,		[str, list]					)
def   __lowerCAmelCase					(							lowerCamelCase   :						Any				,		lowerCamelCase   :						List[str]				,		lowerCamelCase   :						Optional[int]					):






	'''simple docstring'''




	if issubclass(lowerCamelCase				,		lowerCamelCase					):
		__lowerCAmelCase												=  jsonl_path
	elif issubclass(lowerCamelCase				,		lowerCamelCase					):
		__lowerCAmelCase												=  [jsonl_path]
	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		cache_dir=lowerCamelCase					).read()
	_check_json_dataset(lowerCamelCase				,		lowerCamelCase					)



def   __lowerCAmelCase					(							lowerCamelCase   :						Optional[int]				,		lowerCamelCase   :						int				,		lowerCamelCase   :						str=("train",)					):






	'''simple docstring'''




	assert isinstance(lowerCamelCase				,		lowerCamelCase					)
	for split in splits:
		__lowerCAmelCase												=  dataset_dict[split]
		assert dataset.num_rows == 4
		assert dataset.num_columns == 3
		assert dataset.column_names == ["col_1", "col_2", "col_3"]
		for feature, expected_dtype in expected_features.items():
			assert dataset.features[feature].dtype == expected_dtype



@pytest.mark.parametrize("keep_in_memory"				,		[False, True]					)
def   __lowerCAmelCase					(							lowerCamelCase   :						Dict				,		lowerCamelCase   :						int				,		lowerCamelCase   :						List[str]					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
		__lowerCAmelCase												=  JsonDatasetReader({"train": jsonl_path}				,		cache_dir=lowerCamelCase				,		keep_in_memory=lowerCamelCase					).read()
	_check_json_datasetdict(lowerCamelCase				,		lowerCamelCase					)



@pytest.mark.parametrize(
    "features"				,		[
        None,
        {"col_1": "string", "col_2": "int64", "col_3": "float64"},
        {"col_1": "string", "col_2": "string", "col_3": "string"},
        {"col_1": "int32", "col_2": "int32", "col_3": "int32"},
        {"col_1": "float32", "col_2": "float32", "col_3": "float32"},
    ]				,		)
def   __lowerCAmelCase					(							lowerCamelCase   :						int				,		lowerCamelCase   :						Any				,		lowerCamelCase   :						Dict					):






	'''simple docstring'''




	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	__lowerCAmelCase												=  features.copy() if features else default_expected_features
	__lowerCAmelCase												=  (
	    Features({feature: Value(lowerCamelCase					) for feature, dtype in features.items()}					) if features is not None else None
	)
	__lowerCAmelCase												=  JsonDatasetReader({"train": jsonl_path}				,		features=lowerCamelCase				,		cache_dir=lowerCamelCase					).read()
	_check_json_datasetdict(lowerCamelCase				,		lowerCamelCase					)



@pytest.mark.parametrize("split"				,		[None, NamedSplit("train"					), "train", "test"]					)
def   __lowerCAmelCase					(							lowerCamelCase   :						int				,		lowerCamelCase   :						Optional[int]				,		lowerCamelCase   :						int					):






	'''simple docstring'''




	if split:
		__lowerCAmelCase												=  {split: jsonl_path}
	else:
		__lowerCAmelCase												=  "train"
		__lowerCAmelCase												=  {"train": jsonl_path, "test": jsonl_path}
	__lowerCAmelCase												=  tmp_path / "cache"
	__lowerCAmelCase												=  {"col_1": "string", "col_2": "int64", "col_3": "float64"}
	__lowerCAmelCase												=  JsonDatasetReader(lowerCamelCase				,		cache_dir=lowerCamelCase					).read()
	_check_json_datasetdict(lowerCamelCase				,		lowerCamelCase				,		splits=list(path.keys()					)					)
	assert all(dataset[split].split == split for split in path.keys()					)



def   __lowerCAmelCase					(							lowerCamelCase   :						Optional[Any]					):






	'''simple docstring'''




	return json.load(lowerCamelCase					)



def   __lowerCAmelCase					(							lowerCamelCase   :						Tuple					):






	'''simple docstring'''




	return [json.loads(lowerCamelCase					) for line in buffer]






class 					UpperCAmelCase__	:



					@pytest.mark.parametrize("lines, load_json_function"			,				[(True, load_json_lines), (False, load_json)]     )
					def        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase     )     ->			int:
						with io.BytesIO() as buffer:
							JsonDatasetWriter(UpperCamelCase			,				UpperCamelCase			,				lines=UpperCamelCase     ).write()
							buffer.seek(0     )
							__lowerCAmelCase												=  load_json_function(UpperCamelCase     )
						assert isinstance(UpperCamelCase			,				UpperCamelCase     )
						assert isinstance(exported_content[0]			,				UpperCamelCase     )
						assert len(UpperCamelCase     ) == 10



					@pytest.mark.parametrize(
					    "orient, container, keys, len_at"			,				[
					        ("records", list, {"tokens", "labels", "answers", "id"}, None),
					        ("split", dict, {"columns", "data"}, "data"),
					        ("index", dict, set("0123456789"     ), None),
					        ("columns", dict, {"tokens", "labels", "answers", "id"}, "tokens"),
					        ("values", list, None, None),
					        ("table", dict, {"schema", "data"}, "data"),
					    ]			,				)
					def        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase     )     ->			int:
						with io.BytesIO() as buffer:
							JsonDatasetWriter(UpperCamelCase			,				UpperCamelCase			,				lines=UpperCamelCase			,				orient=UpperCamelCase     ).write()
							buffer.seek(0     )
							__lowerCAmelCase												=  load_json(UpperCamelCase     )
						assert isinstance(UpperCamelCase			,				UpperCamelCase     )
						if keys:
							if container is dict:
								assert exported_content.keys() == keys
							else:
								assert exported_content[0].keys() == keys
						else:
							assert not hasattr(UpperCamelCase			,				"keys"     ) and not hasattr(exported_content[0]			,				"keys"     )
						if len_at:
							assert len(exported_content[len_at]     ) == 10
						else:
							assert len(UpperCamelCase     ) == 10



					@pytest.mark.parametrize("lines, load_json_function"			,				[(True, load_json_lines), (False, load_json)]     )
					def        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase     )     ->			str:
						with io.BytesIO() as buffer:
							JsonDatasetWriter(UpperCamelCase			,				UpperCamelCase			,				lines=UpperCamelCase			,				num_proc=2     ).write()
							buffer.seek(0     )
							__lowerCAmelCase												=  load_json_function(UpperCamelCase     )
						assert isinstance(UpperCamelCase			,				UpperCamelCase     )
						assert isinstance(exported_content[0]			,				UpperCamelCase     )
						assert len(UpperCamelCase     ) == 10



					@pytest.mark.parametrize(
					    "orient, container, keys, len_at"			,				[
					        ("records", list, {"tokens", "labels", "answers", "id"}, None),
					        ("split", dict, {"columns", "data"}, "data"),
					        ("index", dict, set("0123456789"     ), None),
					        ("columns", dict, {"tokens", "labels", "answers", "id"}, "tokens"),
					        ("values", list, None, None),
					        ("table", dict, {"schema", "data"}, "data"),
					    ]			,				)
					def        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase     )     ->			Union[str, Any]:
						with io.BytesIO() as buffer:
							JsonDatasetWriter(UpperCamelCase			,				UpperCamelCase			,				lines=UpperCamelCase			,				orient=UpperCamelCase			,				num_proc=2     ).write()
							buffer.seek(0     )
							__lowerCAmelCase												=  load_json(UpperCamelCase     )
						assert isinstance(UpperCamelCase			,				UpperCamelCase     )
						if keys:
							if container is dict:
								assert exported_content.keys() == keys
							else:
								assert exported_content[0].keys() == keys
						else:
							assert not hasattr(UpperCamelCase			,				"keys"     ) and not hasattr(exported_content[0]			,				"keys"     )
						if len_at:
							assert len(exported_content[len_at]     ) == 10
						else:
							assert len(UpperCamelCase     ) == 10



					def        UpperCAmelCase_ (    self			,				UpperCamelCase     )     ->			Any:
						with pytest.raises(UpperCamelCase     ):
							with io.BytesIO() as buffer:
								JsonDatasetWriter(UpperCamelCase			,				UpperCamelCase			,				num_proc=0     )



					@pytest.mark.parametrize("compression, extension"			,				[("gzip", "gz"), ("bz2", "bz2"), ("xz", "xz")]     )
					def        UpperCAmelCase_ (    self			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase			,				UpperCamelCase     )     ->			Tuple:
						__lowerCAmelCase												=  tmp_path_factory.mktemp("data"     ) / F'''test.json.{extension}'''
						__lowerCAmelCase												=  str(shared_datadir / F'''test_file.json.{extension}'''     )
						JsonDatasetWriter(UpperCamelCase			,				UpperCamelCase			,				compression=UpperCamelCase     ).write()

						with fsspec.open(UpperCamelCase			,				"rb"			,				compression="infer"     ) as f:
							__lowerCAmelCase												=  f.read()
						with fsspec.open(UpperCamelCase			,				"rb"			,				compression="infer"     ) as f:
							__lowerCAmelCase												=  f.read()
						assert exported_content == original_content