



"""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 __lowercase			(							_a		,			_a    ):
    assert isinstance(_a		,			_a    )
    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 __lowercase			(							_a		,			_a		,			_a    ):
    snake_case_ :     Tuple				=	tmp_path / '''cache'''
    snake_case_ :     Union[str, Any]				=	{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
    with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
        snake_case_ :     Optional[int]				=	JsonDatasetReader(_a		,			cache_dir=_a		,			keep_in_memory=_a    ).read()
    _check_json_dataset(_a		,			_a    )




@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 __lowercase			(							_a		,			_a		,			_a    ):
    snake_case_ :     Optional[Any]				=	tmp_path / '''cache'''
    snake_case_ :     Optional[int]				=	{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
    snake_case_ :     Optional[int]				=	features.copy() if features else default_expected_features
    snake_case_ :     str				=	(
        Features({feature: Value(_a    ) for feature, dtype in features.items()}    ) if features is not None else None
    )
    snake_case_ :     Optional[Any]				=	JsonDatasetReader(_a		,			features=_a		,			cache_dir=_a    ).read()
    _check_json_dataset(_a		,			_a    )




@pytest.mark.parametrize(
    '''features'''		,			[
        None,
        {'''col_3''': '''float64''', '''col_1''': '''string''', '''col_2''': '''int64'''},
    ]		,			)
def __lowercase			(							_a		,			_a		,			_a    ):
    snake_case_ :     List[str]				=	tmp_path / '''cache'''
    snake_case_ :     Tuple				=	{'''col_3''': '''float64''', '''col_1''': '''string''', '''col_2''': '''int64'''}
    snake_case_ :     str				=	features.copy() if features else default_expected_features
    snake_case_ :     Dict				=	(
        Features({feature: Value(_a    ) for feature, dtype in features.items()}    ) if features is not None else None
    )
    snake_case_ :     Any				=	JsonDatasetReader(_a		,			features=_a		,			cache_dir=_a    ).read()
    assert isinstance(_a		,			_a    )
    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 __lowercase			(							_a		,			_a    ):
    # jsonl_312_path features are {"col_3": "float64", "col_1": "string", "col_2": "int64"}
    snake_case_ :     Tuple				=	{'''col_2''': '''int64''', '''col_3''': '''float64''', '''col_1''': '''string'''}
    snake_case_ :     List[str]				=	features.copy()
    snake_case_ :     str				=	(
        Features({feature: Value(_a    ) for feature, dtype in features.items()}    ) if features is not None else None
    )
    snake_case_ :     int				=	tmp_path / '''cache'''
    snake_case_ :     Optional[int]				=	JsonDatasetReader(_a		,			features=_a		,			cache_dir=_a    ).read()
    assert isinstance(_a		,			_a    )
    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 __lowercase			(							_a		,			_a		,			_a    ):
    snake_case_ :     Optional[int]				=	tmp_path / '''cache'''
    snake_case_ :     List[str]				=	{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
    snake_case_ :     Optional[int]				=	JsonDatasetReader(_a		,			cache_dir=_a		,			split=_a    ).read()
    _check_json_dataset(_a		,			_a    )
    assert dataset.split == split if split else "train"




@pytest.mark.parametrize('''path_type'''		,			[str, list]    )
def __lowercase			(							_a		,			_a		,			_a    ):
    if issubclass(_a		,			_a    ):
        snake_case_ :     Optional[int]				=	jsonl_path
    elif issubclass(_a		,			_a    ):
        snake_case_ :     Optional[Any]				=	[jsonl_path]
    snake_case_ :     int				=	tmp_path / '''cache'''
    snake_case_ :     int				=	{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
    snake_case_ :     Tuple				=	JsonDatasetReader(_a		,			cache_dir=_a    ).read()
    _check_json_dataset(_a		,			_a    )




def __lowercase			(							_a		,			_a		,			_a=("train",)    ):
    assert isinstance(_a		,			_a    )
    for split in splits:
        snake_case_ :     str				=	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 __lowercase			(							_a		,			_a		,			_a    ):
    snake_case_ :     List[str]				=	tmp_path / '''cache'''
    snake_case_ :     Dict				=	{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
    with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
        snake_case_ :     Optional[Any]				=	JsonDatasetReader({'''train''': jsonl_path}		,			cache_dir=_a		,			keep_in_memory=_a    ).read()
    _check_json_datasetdict(_a		,			_a    )




@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 __lowercase			(							_a		,			_a		,			_a    ):
    snake_case_ :     Union[str, Any]				=	tmp_path / '''cache'''
    snake_case_ :     str				=	{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
    snake_case_ :     List[Any]				=	features.copy() if features else default_expected_features
    snake_case_ :     Dict				=	(
        Features({feature: Value(_a    ) for feature, dtype in features.items()}    ) if features is not None else None
    )
    snake_case_ :     str				=	JsonDatasetReader({'''train''': jsonl_path}		,			features=_a		,			cache_dir=_a    ).read()
    _check_json_datasetdict(_a		,			_a    )




@pytest.mark.parametrize('''split'''		,			[None, NamedSplit('''train'''    ), '''train''', '''test''']    )
def __lowercase			(							_a		,			_a		,			_a    ):
    if split:
        snake_case_ :     List[str]				=	{split: jsonl_path}
    else:
        snake_case_ :     List[str]				=	'''train'''
        snake_case_ :     Optional[int]				=	{'''train''': jsonl_path, '''test''': jsonl_path}
    snake_case_ :     List[Any]				=	tmp_path / '''cache'''
    snake_case_ :     Any				=	{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
    snake_case_ :     int				=	JsonDatasetReader(_a		,			cache_dir=_a    ).read()
    _check_json_datasetdict(_a		,			_a		,			splits=list(path.keys()    )    )
    assert all(dataset[split].split == split for split in path.keys()    )




def __lowercase			(							_a    ):
    return json.load(_a    )




def __lowercase			(							_a    ):
    return [json.loads(_a    ) for line in buffer]






class        _UpperCAmelCase       :

 @pytest.mark.parametrize('''lines, load_json_function'''  ,     [(True, load_json_lines), (False, load_json)]				)
 def 						_snake_case					(     self		:       List[str]  ,     lowercase_		:       Any  ,     lowercase_		:       List[Any]  ,     lowercase_		:       Optional[int]				):
     with io.BytesIO() as buffer:
         JsonDatasetWriter(lowercase_  ,     lowercase_  ,     lines=lowercase_				).write()
         buffer.seek(0				)
         snake_case_ :     List[str]				=	load_json_function(lowercase_				)
     assert isinstance(lowercase_  ,     lowercase_				)
     assert isinstance(exported_content[0]  ,     lowercase_				)
     assert len(lowercase_				) == 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 						_snake_case					(     self		:       str  ,     lowercase_		:       Dict  ,     lowercase_		:       Union[str, Any]  ,     lowercase_		:       Union[str, Any]  ,     lowercase_		:       Optional[int]  ,     lowercase_		:       Dict				):
     with io.BytesIO() as buffer:
         JsonDatasetWriter(lowercase_  ,     lowercase_  ,     lines=lowercase_  ,     orient=lowercase_				).write()
         buffer.seek(0				)
         snake_case_ :     str				=	load_json(lowercase_				)
     assert isinstance(lowercase_  ,     lowercase_				)
     if keys:
         if container is dict:
             assert exported_content.keys() == keys
         else:
             assert exported_content[0].keys() == keys
     else:
         assert not hasattr(lowercase_  ,     '''keys'''				) and not hasattr(exported_content[0]  ,     '''keys'''				)
     if len_at:
         assert len(exported_content[len_at]				) == 10
     else:
         assert len(lowercase_				) == 10

 @pytest.mark.parametrize('''lines, load_json_function'''  ,     [(True, load_json_lines), (False, load_json)]				)
 def 						_snake_case					(     self		:       str  ,     lowercase_		:       Tuple  ,     lowercase_		:       Optional[Any]  ,     lowercase_		:       Union[str, Any]				):
     with io.BytesIO() as buffer:
         JsonDatasetWriter(lowercase_  ,     lowercase_  ,     lines=lowercase_  ,     num_proc=2				).write()
         buffer.seek(0				)
         snake_case_ :     Optional[Any]				=	load_json_function(lowercase_				)
     assert isinstance(lowercase_  ,     lowercase_				)
     assert isinstance(exported_content[0]  ,     lowercase_				)
     assert len(lowercase_				) == 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 						_snake_case					(     self		:       List[Any]  ,     lowercase_		:       Union[str, Any]  ,     lowercase_		:       List[str]  ,     lowercase_		:       List[Any]  ,     lowercase_		:       List[str]  ,     lowercase_		:       str				):
     with io.BytesIO() as buffer:
         JsonDatasetWriter(lowercase_  ,     lowercase_  ,     lines=lowercase_  ,     orient=lowercase_  ,     num_proc=2				).write()
         buffer.seek(0				)
         snake_case_ :     str				=	load_json(lowercase_				)
     assert isinstance(lowercase_  ,     lowercase_				)
     if keys:
         if container is dict:
             assert exported_content.keys() == keys
         else:
             assert exported_content[0].keys() == keys
     else:
         assert not hasattr(lowercase_  ,     '''keys'''				) and not hasattr(exported_content[0]  ,     '''keys'''				)
     if len_at:
         assert len(exported_content[len_at]				) == 10
     else:
         assert len(lowercase_				) == 10

 def 						_snake_case					(     self		:       str  ,     lowercase_		:       Optional[Any]				):
     with pytest.raises(lowercase_				):
         with io.BytesIO() as buffer:
             JsonDatasetWriter(lowercase_  ,     lowercase_  ,     num_proc=0				)






 @pytest.mark.parametrize('''compression, extension'''  ,     [('''gzip''', '''gz'''), ('''bz2''', '''bz2'''), ('''xz''', '''xz''')]				)
 def 						_snake_case					(     self		:       Optional[Any]  ,     lowercase_		:       int  ,     lowercase_		:       List[str]  ,     lowercase_		:       Tuple  ,     lowercase_		:       Union[str, Any]  ,     lowercase_		:       Optional[int]				):
     snake_case_ :     Any				=	tmp_path_factory.mktemp('''data'''				) / f"test.json.{extension}"
     snake_case_ :     Tuple				=	str(shared_datadir / f"test_file.json.{extension}"				)
     JsonDatasetWriter(lowercase_  ,     lowercase_  ,     compression=lowercase_				).write()

     with fsspec.open(lowercase_  ,     '''rb'''  ,     compression='''infer'''				) as f:
         snake_case_ :     Optional[Any]				=	f.read()
     with fsspec.open(lowercase_  ,     '''rb'''  ,     compression='''infer'''				) as f:
         snake_case_ :     Optional[Any]				=	f.read()
     assert exported_content == original_content










"""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:
     lowercase__    :  int							    =	None


lowercase__    :  Any							    =	logging.get_logger(__name__)


lowercase__    :  List[str]							    =	'''▁'''

lowercase__    :  Optional[int]							    =	{'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowercase__    :  str							    =	{
    '''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'''
    },
}

lowercase__    :  List[Any]							    =	{
    '''google/pegasus-xsum''': 5_12,
}




class        _UpperCAmelCase       (			lowerCAmelCase__):
 _lowerCAmelCase   :			List[str]							=		VOCAB_FILES_NAMES
 _lowerCAmelCase   :			List[str]							=		PRETRAINED_VOCAB_FILES_MAP
 _lowerCAmelCase   :			Any							=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCAmelCase   :			Tuple							=		PegasusTokenizer
 _lowerCAmelCase   :			str							=		["""input_ids""", """attention_mask"""]

 def __init__(     self		:       Any  ,     lowercase_		:       Optional[Any]=None  ,     lowercase_		:       int=None  ,     lowercase_		:       Tuple="<pad>"  ,     lowercase_		:       int="</s>"  ,     lowercase_		:       Tuple="<unk>"  ,     lowercase_		:       str="<mask_2>"  ,     lowercase_		:       Optional[Any]="<mask_1>"  ,     lowercase_		:       str=None  ,     lowercase_		:       List[str]=103  ,     **lowercase_		:       List[Any]  ,     ):
     snake_case_ :     Dict				=	offset

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

         snake_case_ :     str				=	(
             ([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(lowercase_				)  ,     self.offset - 1				)
         ]

         if len(set(lowercase_				)				) != len(lowercase_				):
             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}."				)
         snake_case_ :     Union[str, Any]				=	additional_special_tokens_extended
     else:
         snake_case_ :     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__(
         lowercase_  ,     tokenizer_file=lowercase_  ,     pad_token=lowercase_  ,     eos_token=lowercase_  ,     unk_token=lowercase_  ,     mask_token=lowercase_  ,     mask_token_sent=lowercase_  ,     offset=lowercase_  ,     additional_special_tokens=lowercase_  ,     **lowercase_  ,     )
     snake_case_ :     List[Any]				=	vocab_file
     snake_case_ :     List[Any]				=	False if not self.vocab_file else True

 def 						_snake_case					(     self		:       str  ,     lowercase_		:       Union[str, Any]				):
     snake_case_ :     Any				=	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 						_snake_case					(     self		:       int  ,     lowercase_		:       List  ,     lowercase_		:       Optional[List] = None  ,     lowercase_		:       bool = False				):
     if already_has_special_tokens:
         return self._special_token_mask(lowercase_				)
     elif token_ids_a is None:
         return self._special_token_mask(lowercase_				) + [1]
     else:
         return self._special_token_mask(token_ids_a + token_ids_a				) + [1]

 def 						_snake_case					(     self		:       List[Any]  ,     lowercase_		:       Optional[int]  ,     lowercase_		:       str=None				):
     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 						_snake_case					(     self		:       Optional[Any]  ,     lowercase_		:       str  ,     lowercase_		:       Optional[str] = None				):
     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(lowercase_				):
         logger.error(f"Vocabulary path ({save_directory}) should be a directory"				)
         return
     snake_case_ :     Dict				=	os.path.join(
         lowercase_  ,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']				)

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

     return (out_vocab_file,)





