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







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







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







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







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







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







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







def       A__   (						snake_case_			:		List[str]   ):
 return json.load(snake_case_   )







def       A__   (						snake_case_			:		Dict   ):
 return [json.loads(snake_case_   ) for line in buffer]






class 		_lowerCamelCase		:
    @pytest.mark.parametrize('''lines, load_json_function'''			,			[(True, load_json_lines), (False, load_json)] )
    def     UpperCamelCase_					(	self			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase )							->       Dict:
     with io.BytesIO() as buffer:
      JsonDatasetWriter(lowerCAmelCase			,			lowerCAmelCase			,			lines=lowerCAmelCase ).write()
      buffer.seek(0 )
      SCREAMING_SNAKE_CASE__: Optional[Any]=   load_json_function(lowerCAmelCase )
     assert isinstance(lowerCAmelCase			,			lowerCAmelCase )
     assert isinstance(exported_content[0]			,			lowerCAmelCase )
     assert len(lowerCAmelCase ) == 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			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase )							->       Optional[int]:
     with io.BytesIO() as buffer:
      JsonDatasetWriter(lowerCAmelCase			,			lowerCAmelCase			,			lines=lowerCAmelCase			,			orient=lowerCAmelCase ).write()
      buffer.seek(0 )
      SCREAMING_SNAKE_CASE__: int=   load_json(lowerCAmelCase )
     assert isinstance(lowerCAmelCase			,			lowerCAmelCase )
     if keys:
      if container is dict:
       assert exported_content.keys() == keys
      else:
       assert exported_content[0].keys() == keys
     else:
      assert not hasattr(lowerCAmelCase			,			'''keys''' ) and not hasattr(exported_content[0]			,			'''keys''' )
     if len_at:
      assert len(exported_content[len_at] ) == 10
     else:
      assert len(lowerCAmelCase ) == 10
    @pytest.mark.parametrize('''lines, load_json_function'''			,			[(True, load_json_lines), (False, load_json)] )
    def     UpperCamelCase_					(	self			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase )							->       Any:
     with io.BytesIO() as buffer:
      JsonDatasetWriter(lowerCAmelCase			,			lowerCAmelCase			,			lines=lowerCAmelCase			,			num_proc=2 ).write()
      buffer.seek(0 )
      SCREAMING_SNAKE_CASE__: List[str]=   load_json_function(lowerCAmelCase )
     assert isinstance(lowerCAmelCase			,			lowerCAmelCase )
     assert isinstance(exported_content[0]			,			lowerCAmelCase )
     assert len(lowerCAmelCase ) == 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			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase )							->       int:
     with io.BytesIO() as buffer:
      JsonDatasetWriter(lowerCAmelCase			,			lowerCAmelCase			,			lines=lowerCAmelCase			,			orient=lowerCAmelCase			,			num_proc=2 ).write()
      buffer.seek(0 )
      SCREAMING_SNAKE_CASE__: Union[str, Any]=   load_json(lowerCAmelCase )
     assert isinstance(lowerCAmelCase			,			lowerCAmelCase )
     if keys:
      if container is dict:
       assert exported_content.keys() == keys
      else:
       assert exported_content[0].keys() == keys
     else:
      assert not hasattr(lowerCAmelCase			,			'''keys''' ) and not hasattr(exported_content[0]			,			'''keys''' )
     if len_at:
      assert len(exported_content[len_at] ) == 10
     else:
      assert len(lowerCAmelCase ) == 10
    def     UpperCamelCase_					(	self			,			lowerCAmelCase )							->       int:
     with pytest.raises(lowerCAmelCase ):
      with io.BytesIO() as buffer:
       JsonDatasetWriter(lowerCAmelCase			,			lowerCAmelCase			,			num_proc=0 )



    @pytest.mark.parametrize('''compression, extension'''			,			[('''gzip''', '''gz'''), ('''bz2''', '''bz2'''), ('''xz''', '''xz''')] )
    def     UpperCamelCase_					(	self			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase			,			lowerCAmelCase )							->       Optional[int]:
     SCREAMING_SNAKE_CASE__: List[str]=   tmp_path_factory.mktemp('''data''' ) / f'test.json.{extension}'
     SCREAMING_SNAKE_CASE__: Dict=   str(shared_datadir / f'test_file.json.{extension}' )
     JsonDatasetWriter(lowerCAmelCase			,			lowerCAmelCase			,			compression=lowerCAmelCase ).write()

     with fsspec.open(lowerCAmelCase			,			'''rb'''			,			compression='''infer''' ) as f:
      SCREAMING_SNAKE_CASE__: Tuple=   f.read()
     with fsspec.open(lowerCAmelCase			,			'''rb'''			,			compression='''infer''' ) as f:
      SCREAMING_SNAKE_CASE__: Dict=   f.read()
     assert exported_content == original_content



"""simple docstring"""



from ...configuration_utils import PretrainedConfig





class 				a			(					lowercase      ):
      UpperCamelCase							:   Union[str, Any]           =     """bert-generation"""



      def __init__(   self     ,	UpperCamelCase_=50_358     ,	UpperCamelCase_=1_024     ,	UpperCamelCase_=24     ,	UpperCamelCase_=16     ,	UpperCamelCase_=4_096     ,	UpperCamelCase_="gelu"     ,	UpperCamelCase_=0.1     ,	UpperCamelCase_=0.1     ,	UpperCamelCase_=512     ,	UpperCamelCase_=0.02     ,	UpperCamelCase_=1E-12     ,	UpperCamelCase_=0     ,	UpperCamelCase_=2     ,	UpperCamelCase_=1     ,	UpperCamelCase_="absolute"     ,	UpperCamelCase_=True     ,	**UpperCamelCase_     ,	):
          super().__init__(pad_token_id=UpperCamelCase_     ,	bos_token_id=UpperCamelCase_     ,	eos_token_id=UpperCamelCase_     ,	**UpperCamelCase_      )

          UpperCAmelCase__	:      Optional[Any]     							=					vocab_size
          UpperCAmelCase__	:      Union[str, Any]     							=					hidden_size
          UpperCAmelCase__	:      Optional[Any]     							=					num_hidden_layers
          UpperCAmelCase__	:      Dict     							=					num_attention_heads
          UpperCAmelCase__	:      Dict     							=					hidden_act
          UpperCAmelCase__	:      Optional[Any]     							=					intermediate_size
          UpperCAmelCase__	:      Optional[int]     							=					hidden_dropout_prob
          UpperCAmelCase__	:      Tuple     							=					attention_probs_dropout_prob
          UpperCAmelCase__	:      List[Any]     							=					max_position_embeddings
          UpperCAmelCase__	:      Optional[int]     							=					initializer_range
          UpperCAmelCase__	:      Optional[int]     							=					layer_norm_eps
          UpperCAmelCase__	:      Union[str, Any]     							=					position_embedding_type
          UpperCAmelCase__	:      Dict     							=					use_cache

