


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


A			:						List[Any]        =  logging.get_logger(__name__)


A			:						Union[str, Any]        =  {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

# See all BART models at https://huggingface.co/models?filter=bart
A			:						str        =  {
    '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',
    },
}

A			:						Union[str, Any]        =  {
    'facebook/bart-base': 1_0_2_4,
    'facebook/bart-large': 1_0_2_4,
    'facebook/bart-large-mnli': 1_0_2_4,
    'facebook/bart-large-cnn': 1_0_2_4,
    'facebook/bart-large-xsum': 1_0_2_4,
    'yjernite/bart_eli5': 1_0_2_4,
}






@lru_cache()
def 					UpperCamelCase   (      )  ->    Optional[int]:
		"""simple docstring"""




		lowercase__	     =						(
		    list(range(ord("""!"""	)       ,       ord("""~"""	) + 1	)	) + list(range(ord("""¡"""	)       ,       ord("""¬"""	) + 1	)	) + list(range(ord("""®"""	)       ,       ord("""ÿ"""	) + 1	)	)
		)
		lowercase__	     =						bs[:]
		lowercase__	     =						0
		for b in range(2**8	):
				if b not in bs:
						bs.append(__magic_name__	)
						cs.append(2**8 + n	)
						n += 1
		lowercase__	     =						[chr(__magic_name__	) for n in cs]
		return dict(zip(__magic_name__       ,       __magic_name__	)	)






def 					UpperCamelCase   (      __magic_name__	:				str	)  ->    Tuple:
		"""simple docstring"""




		lowercase__	     =						set()
		lowercase__	     =						word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)	)
				lowercase__	     =						char
		return pairs







class 				A       (			UpperCAmelCase__				):
					'''simple docstring'''






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

					def __init__(self       :		Union[str, Any] ,   _UpperCAmelCase       :		Dict ,   _UpperCAmelCase       :		Any ,   _UpperCAmelCase       :		Union[str, Any]="replace" ,   _UpperCAmelCase       :		Tuple="<s>" ,   _UpperCAmelCase       :		Dict="</s>" ,   _UpperCAmelCase       :		List[str]="</s>" ,   _UpperCAmelCase       :		Dict="<s>" ,   _UpperCAmelCase       :		int="<unk>" ,   _UpperCAmelCase       :		Any="<pad>" ,   _UpperCAmelCase       :		int="<mask>" ,   _UpperCAmelCase       :		Optional[int]=False ,   **_UpperCAmelCase       :		int ,   )		->  Optional[int]:




							"""simple docstring"""


							lowercase__	     =						AddedToken(_UpperCAmelCase ,   lstrip=_UpperCAmelCase ,   rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase ,   _UpperCAmelCase						) else bos_token
							lowercase__	     =						AddedToken(_UpperCAmelCase ,   lstrip=_UpperCAmelCase ,   rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase ,   _UpperCAmelCase						) else eos_token
							lowercase__	     =						AddedToken(_UpperCAmelCase ,   lstrip=_UpperCAmelCase ,   rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase ,   _UpperCAmelCase						) else sep_token
							lowercase__	     =						AddedToken(_UpperCAmelCase ,   lstrip=_UpperCAmelCase ,   rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase ,   _UpperCAmelCase						) else cls_token
							lowercase__	     =						AddedToken(_UpperCAmelCase ,   lstrip=_UpperCAmelCase ,   rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase ,   _UpperCAmelCase						) else unk_token
							lowercase__	     =						AddedToken(_UpperCAmelCase ,   lstrip=_UpperCAmelCase ,   rstrip=_UpperCAmelCase						) if isinstance(_UpperCAmelCase ,   _UpperCAmelCase						) else pad_token

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

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

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

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

					@property
					def     lowerCamelCase__	(self       :		Tuple						)		->  Tuple:




							"""simple docstring"""


							return len(self.encoder						)

					def     lowerCamelCase__	(self       :		Optional[Any]						)		->  Dict:




							"""simple docstring"""


							return dict(self.encoder ,   **self.added_tokens_encoder						)

					def     lowerCamelCase__	(self       :		str ,   _UpperCAmelCase       :		List[Any]						)		->  str:




							"""simple docstring"""


							if token in self.cache:
									return self.cache[token]
							lowercase__	     =						tuple(_UpperCAmelCase						)
							lowercase__	     =						get_pairs(_UpperCAmelCase						)

							if not pairs:
									return token

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

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

					def     lowerCamelCase__	(self       :		List[str] ,   _UpperCAmelCase       :		Any						)		->  Optional[Any]:




							"""simple docstring"""


							lowercase__	     =						[]
							for token in re.findall(self.pat ,   _UpperCAmelCase						):
									lowercase__	     =						"""""".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(_UpperCAmelCase						).split(""" """						)						)
							return bpe_tokens

					def     lowerCamelCase__	(self       :		int ,   _UpperCAmelCase       :		int						)		->  Any:




							"""simple docstring"""


							return self.encoder.get(_UpperCAmelCase ,   self.encoder.get(self.unk_token						)						)

					def     lowerCamelCase__	(self       :		int ,   _UpperCAmelCase       :		Optional[Any]						)		->  Dict:




							"""simple docstring"""


							return self.decoder.get(_UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		List[Any] ,   _UpperCAmelCase       :		Optional[Any]						)		->  List[Any]:




							"""simple docstring"""


							lowercase__	     =						"""""".join(_UpperCAmelCase						)
							lowercase__	     =						bytearray([self.byte_decoder[c] for c in text]						).decode("""utf-8""" ,   errors=self.errors						)
							return text

					def     lowerCamelCase__	(self       :		Any ,   _UpperCAmelCase       :		str ,   _UpperCAmelCase       :		Optional[str] = None						)		->  Tuple[str]:




							"""simple docstring"""


							if not os.path.isdir(_UpperCAmelCase						):
									logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''						)
									return
							lowercase__	     =						os.path.join(
							    _UpperCAmelCase ,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]						)
							lowercase__	     =						os.path.join(
							    _UpperCAmelCase ,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]						)

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

							lowercase__	     =						0
							with open(_UpperCAmelCase ,   """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 _UpperCAmelCase						: 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!"""						)
													lowercase__	     =						token_index
											writer.write(""" """.join(_UpperCAmelCase						) + """\n"""						)
											index += 1

							return vocab_file, merge_file

					def     lowerCamelCase__	(self       :		Any ,   _UpperCAmelCase       :		List[int] ,   _UpperCAmelCase       :		Optional[List[int]] = None						)		->  List[int]:




							"""simple docstring"""


							if token_ids_a is None:
									return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							lowercase__	     =						[self.cls_token_id]
							lowercase__	     =						[self.sep_token_id]
							return cls + token_ids_a + sep + sep + token_ids_a + sep

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




							"""simple docstring"""


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

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

					def     lowerCamelCase__	(self       :		Dict ,   _UpperCAmelCase       :		List[int] ,   _UpperCAmelCase       :		Optional[List[int]] = None						)		->  List[int]:




							"""simple docstring"""


							lowercase__	     =						[self.sep_token_id]
							lowercase__	     =						[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     lowerCamelCase__	(self       :		Union[str, Any] ,   _UpperCAmelCase       :		str ,   _UpperCAmelCase       :		List[str]=False ,   **_UpperCAmelCase       :		List[Any]						)		->  Any:




							"""simple docstring"""


							lowercase__	     =						kwargs.pop("""add_prefix_space""" ,   self.add_prefix_space						)
							if (is_split_into_words or add_prefix_space) and (len(_UpperCAmelCase						) > 0 and not text[0].isspace()):
									lowercase__	     =						""" """ + text
							return (text, kwargs)




"""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       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__   )			->						Optional[Any]:
 assert isinstance(lowercase__					,					lowercase__   )
 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       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						Any:
 lowerCAmelCase__   :				Optional[int] 			=				tmp_path / "cache"
 lowerCAmelCase__   :				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():
  lowerCAmelCase__   :				Tuple 			=				JsonDatasetReader(lowercase__					,					cache_dir=lowercase__					,					keep_in_memory=lowercase__   ).read()
 _check_json_dataset(lowercase__					,					lowercase__   )



@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       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						Tuple:
 lowerCAmelCase__   :				Union[str, Any] 			=				tmp_path / "cache"
 lowerCAmelCase__   :				Tuple 			=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
 lowerCAmelCase__   :				List[Any] 			=				features.copy() if features else default_expected_features
 lowerCAmelCase__   :				int 			=				(
     Features({feature: Value(lowercase__   ) for feature, dtype in features.items()}   ) if features is not None else None
 )
 lowerCAmelCase__   :				Tuple 			=				JsonDatasetReader(lowercase__					,					features=lowercase__					,					cache_dir=lowercase__   ).read()
 _check_json_dataset(lowercase__					,					lowercase__   )



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



@pytest.mark.parametrize("path_type"					,					[str, list]   )
def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						Optional[Any]:
 if issubclass(lowercase__					,					lowercase__   ):
  lowerCAmelCase__   :				Dict 			=				jsonl_path
 elif issubclass(lowercase__					,					lowercase__   ):
  lowerCAmelCase__   :				Tuple 			=				[jsonl_path]
 lowerCAmelCase__   :				Any 			=				tmp_path / "cache"
 lowerCAmelCase__   :				List[str] 			=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
 lowerCAmelCase__   :				int 			=				JsonDatasetReader(lowercase__					,					cache_dir=lowercase__   ).read()
 _check_json_dataset(lowercase__					,					lowercase__   )



def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__=("train",)   )			->						List[str]:
 assert isinstance(lowercase__					,					lowercase__   )
 for split in splits:
  lowerCAmelCase__   :				Dict 			=				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       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						List[str]:
 lowerCAmelCase__   :				int 			=				tmp_path / "cache"
 lowerCAmelCase__   :				str 			=				{"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__   :				Dict 			=				JsonDatasetReader({"train": jsonl_path}					,					cache_dir=lowercase__					,					keep_in_memory=lowercase__   ).read()
 _check_json_datasetdict(lowercase__					,					lowercase__   )



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



@pytest.mark.parametrize("split"					,					[None, NamedSplit("train"   ), "train", "test"]   )
def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__					,					lowercase__   )			->						Dict:
 if split:
  lowerCAmelCase__   :				int 			=				{split: jsonl_path}
 else:
  lowerCAmelCase__   :				str 			=				"train"
  lowerCAmelCase__   :				Tuple 			=				{"train": jsonl_path, "test": jsonl_path}
 lowerCAmelCase__   :				Any 			=				tmp_path / "cache"
 lowerCAmelCase__   :				Dict 			=				{"col_1": "string", "col_2": "int64", "col_3": "float64"}
 lowerCAmelCase__   :				int 			=				JsonDatasetReader(lowercase__					,					cache_dir=lowercase__   ).read()
 _check_json_datasetdict(lowercase__					,					lowercase__					,					splits=list(path.keys()   )   )
 assert all(dataset[split].split == split for split in path.keys()   )



def       SCREAMING_SNAKE_CASE							( lowercase__   )			->						List[Any]:
 return json.load(lowercase__   )



def       SCREAMING_SNAKE_CASE							( lowercase__   )			->						Optional[int]:
 return [json.loads(lowercase__   ) for line in buffer]






class 			__a					:





       """simple docstring"""


       @pytest.mark.parametrize("lines, load_json_function"			,					[(True, load_json_lines), (False, load_json)]   )
       def 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case			,					snake_case			,					snake_case   ):





        """simple docstring"""

        with io.BytesIO() as buffer:
         JsonDatasetWriter(snake_case			,					snake_case			,					lines=snake_case   ).write()
         buffer.seek(0   )
         lowerCAmelCase__   :				int 			=				load_json_function(snake_case   )
        assert isinstance(snake_case			,					snake_case   )
        assert isinstance(exported_content[0]			,					snake_case   )
        assert len(snake_case   ) == 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 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case			,					snake_case			,					snake_case			,					snake_case			,					snake_case   ):





        """simple docstring"""

        with io.BytesIO() as buffer:
         JsonDatasetWriter(snake_case			,					snake_case			,					lines=snake_case			,					orient=snake_case   ).write()
         buffer.seek(0   )
         lowerCAmelCase__   :				Optional[Any] 			=				load_json(snake_case   )
        assert isinstance(snake_case			,					snake_case   )
        if keys:
         if container is dict:
          assert exported_content.keys() == keys
         else:
          assert exported_content[0].keys() == keys
        else:
         assert not hasattr(snake_case			,					"keys"   ) and not hasattr(exported_content[0]			,					"keys"   )
        if len_at:
         assert len(exported_content[len_at]   ) == 10
        else:
         assert len(snake_case   ) == 10






       @pytest.mark.parametrize("lines, load_json_function"			,					[(True, load_json_lines), (False, load_json)]   )
       def 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case			,					snake_case			,					snake_case   ):





        """simple docstring"""

        with io.BytesIO() as buffer:
         JsonDatasetWriter(snake_case			,					snake_case			,					lines=snake_case			,					num_proc=2   ).write()
         buffer.seek(0   )
         lowerCAmelCase__   :				int 			=				load_json_function(snake_case   )
        assert isinstance(snake_case			,					snake_case   )
        assert isinstance(exported_content[0]			,					snake_case   )
        assert len(snake_case   ) == 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 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case			,					snake_case			,					snake_case			,					snake_case			,					snake_case   ):





        """simple docstring"""

        with io.BytesIO() as buffer:
         JsonDatasetWriter(snake_case			,					snake_case			,					lines=snake_case			,					orient=snake_case			,					num_proc=2   ).write()
         buffer.seek(0   )
         lowerCAmelCase__   :				Tuple 			=				load_json(snake_case   )
        assert isinstance(snake_case			,					snake_case   )
        if keys:
         if container is dict:
          assert exported_content.keys() == keys
         else:
          assert exported_content[0].keys() == keys
        else:
         assert not hasattr(snake_case			,					"keys"   ) and not hasattr(exported_content[0]			,					"keys"   )
        if len_at:
         assert len(exported_content[len_at]   ) == 10
        else:
         assert len(snake_case   ) == 10






       def 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case   ):





        """simple docstring"""

        with pytest.raises(snake_case   ):
         with io.BytesIO() as buffer:
          JsonDatasetWriter(snake_case			,					snake_case			,					num_proc=0   )






       @pytest.mark.parametrize("compression, extension"			,					[("gzip", "gz"), ("bz2", "bz2"), ("xz", "xz")]   )
       def 			SCREAMING_SNAKE_CASE_	(   self			,					snake_case			,					snake_case			,					snake_case			,					snake_case			,					snake_case   ):





        """simple docstring"""

        lowerCAmelCase__   :				Any 			=				tmp_path_factory.mktemp("data"   ) / F"""test.json.{extension}"""
        lowerCAmelCase__   :				str 			=				str(shared_datadir / F"""test_file.json.{extension}"""   )
        JsonDatasetWriter(snake_case			,					snake_case			,					compression=snake_case   ).write()

        with fsspec.open(snake_case			,					"rb"			,					compression="infer"   ) as f:
         lowerCAmelCase__   :				Optional[int] 			=				f.read()
        with fsspec.open(snake_case			,					"rb"			,					compression="infer"   ) as f:
         lowerCAmelCase__   :				Optional[int] 			=				f.read()
        assert exported_content == original_content






