





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_      (		lowercase__				,  lowercase__						)   ->List[str]:
						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_      (		lowercase__				,  lowercase__				,  lowercase__						)   ->Tuple:
						_snake_case:   Dict  					=		tmp_path / '''cache'''
						_snake_case:   Optional[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():
												_snake_case:   List[Any]  					=		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_      (		lowercase__				,  lowercase__				,  lowercase__						)   ->Any:
						_snake_case:   str  					=		tmp_path / '''cache'''
						_snake_case:   List[Any]  					=		{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						_snake_case:   int  					=		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:   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_      (		lowercase__				,  lowercase__				,  lowercase__						)   ->str:
						_snake_case:   Union[str, Any]  					=		tmp_path / '''cache'''
						_snake_case:   List[Any]  					=		{'''col_3''': '''float64''', '''col_1''': '''string''', '''col_2''': '''int64'''}
						_snake_case:   str  					=		features.copy() if features else default_expected_features
						_snake_case:   Optional[int]  					=		(
						    Features({feature: Value(a_						) for feature, dtype in features.items()}						) if features is not None else None
						)
						_snake_case:   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_3", "col_1", "col_2"]
						for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype





def       lowercase_      (		lowercase__				,  lowercase__						)   ->List[Any]:
						# jsonl_312_path features are {"col_3": "float64", "col_1": "string", "col_2": "int64"}
						_snake_case:   Any  					=		{'''col_2''': '''int64''', '''col_3''': '''float64''', '''col_1''': '''string'''}
						_snake_case:   int  					=		features.copy()
						_snake_case:   Dict  					=		(
						    Features({feature: Value(a_						) for feature, dtype in features.items()}						) if features is not None else None
						)
						_snake_case:   List[str]  					=		tmp_path / '''cache'''
						_snake_case:   List[str]  					=		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_      (		lowercase__				,  lowercase__				,  lowercase__						)   ->Union[str, Any]:
						_snake_case:   Any  					=		tmp_path / '''cache'''
						_snake_case:   Tuple  					=		{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						_snake_case:   Any  					=		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_      (		lowercase__				,  lowercase__				,  lowercase__						)   ->str:
						if issubclass(a_				,  a_						):
												_snake_case:   str  					=		jsonl_path
						elif issubclass(a_				,  a_						):
												_snake_case:   List[Any]  					=		[jsonl_path]
						_snake_case:   Any  					=		tmp_path / '''cache'''
						_snake_case:   List[str]  					=		{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						_snake_case:   Dict  					=		JsonDatasetReader(a_				,  cache_dir=a_						).read()
						_check_json_dataset(a_				,  a_						)





def       lowercase_      (		lowercase__				,  lowercase__				,  lowercase__=("train",)						)   ->Optional[Any]:
						assert isinstance(a_				,  a_						)
						for split in splits:
												_snake_case:   Tuple  					=		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_      (		lowercase__				,  lowercase__				,  lowercase__						)   ->Optional[int]:
						_snake_case:   Dict  					=		tmp_path / '''cache'''
						_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():
												_snake_case:   Union[str, 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_      (		lowercase__				,  lowercase__				,  lowercase__						)   ->str:
						_snake_case:   List[Any]  					=		tmp_path / '''cache'''
						_snake_case:   List[Any]  					=		{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						_snake_case:   List[str]  					=		features.copy() if features else default_expected_features
						_snake_case:   Any  					=		(
						    Features({feature: Value(a_						) for feature, dtype in features.items()}						) if features is not None else None
						)
						_snake_case:   List[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_      (		lowercase__				,  lowercase__				,  lowercase__						)   ->Optional[Any]:
						if split:
												_snake_case:   Any  					=		{split: jsonl_path}
						else:
												_snake_case:   Optional[Any]  					=		'''train'''
												_snake_case:   List[str]  					=		{'''train''': jsonl_path, '''test''': jsonl_path}
						_snake_case:   List[Any]  					=		tmp_path / '''cache'''
						_snake_case:   Tuple  					=		{'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
						_snake_case:   Dict  					=		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_      (		lowercase__						)   ->Tuple:
						return json.load(a_						)





def       lowercase_      (		lowercase__						)   ->Optional[Any]:
						return [json.loads(a_						) for line in buffer]







class 			lowerCamelCase					:


					@pytest.mark.parametrize('lines, load_json_function'       ,     [(True, load_json_lines), (False, load_json)]       )
					def    SCREAMING_SNAKE_CASE_		(					self	:  List[str]       ,     __snake_case	:  Tuple       ,     __snake_case	:  Union[str, Any]       ,     __snake_case	:  str       ):





											'''simple docstring'''





											with io.BytesIO() as buffer:
																	JsonDatasetWriter(__snake_case       ,     __snake_case       ,     lines=__snake_case       ).write()
																	buffer.seek(0       )
																	_snake_case:   Optional[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	:  Optional[Any]       ,     __snake_case	:  int       ,     __snake_case	:  Optional[int]       ,     __snake_case	:  Any       ,     __snake_case	:  Union[str, Any]       ,     __snake_case	:  Any       ):





											'''simple docstring'''





											with io.BytesIO() as buffer:
																	JsonDatasetWriter(__snake_case       ,     __snake_case       ,     lines=__snake_case       ,     orient=__snake_case       ).write()
																	buffer.seek(0       )
																	_snake_case:   str  					=		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	:  Tuple       ,     __snake_case	:  Optional[Any]       ,     __snake_case	:  int       ,     __snake_case	:  List[str]       ):





											'''simple docstring'''





											with io.BytesIO() as buffer:
																	JsonDatasetWriter(__snake_case       ,     __snake_case       ,     lines=__snake_case       ,     num_proc=2       ).write()
																	buffer.seek(0       )
																	_snake_case:   Any  					=		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	:  Any       ,     __snake_case	:  int       ,     __snake_case	:  List[str]       ,     __snake_case	:  str       ,     __snake_case	:  Optional[int]       ,     __snake_case	:  Optional[Any]       ):





											'''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       )
																	_snake_case:   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	:  Optional[Any]       ,     __snake_case	:  Dict       ):





											'''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	:  List[Any]       ,     __snake_case	:  Dict       ,     __snake_case	:  List[Any]       ,     __snake_case	:  Dict       ,     __snake_case	:  List[str]       ,     __snake_case	:  Optional[Any]       ):





											'''simple docstring'''





											_snake_case:   Any  					=		tmp_path_factory.mktemp('data'       ) / f'''test.json.{extension}'''
											_snake_case:   int  					=		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:
																	_snake_case:   List[Any]  					=		f.read()
											with fsspec.open(__snake_case       ,     'rb'       ,     compression='infer'       ) as f:
																	_snake_case:   int  					=		f.read()
											assert exported_content == original_content












'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import logging


A   : Tuple             =			logging.get_logger(__name__)

A   : Any             =			{
    'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}







class 			lowerCamelCase					(						__UpperCAmelCase  ):
					_SCREAMING_SNAKE_CASE							   =    "biogpt"


					def __init__(					self	:  Union[str, Any]       ,     __snake_case	:  Tuple=4_23_84       ,     __snake_case	:  Any=10_24       ,     __snake_case	:  Optional[int]=24       ,     __snake_case	:  int=16       ,     __snake_case	:  str=40_96       ,     __snake_case	:  Dict="gelu"       ,     __snake_case	:  List[str]=0.1       ,     __snake_case	:  List[Any]=0.1       ,     __snake_case	:  List[Any]=10_24       ,     __snake_case	:  Optional[int]=0.02       ,     __snake_case	:  Union[str, Any]=1e-12       ,     __snake_case	:  List[Any]=True       ,     __snake_case	:  Union[str, Any]=True       ,     __snake_case	:  Any=0.0       ,     __snake_case	:  int=0.0       ,     __snake_case	:  Dict=1       ,     __snake_case	:  str=0       ,     __snake_case	:  List[str]=2       ,     **__snake_case	:  Optional[int]       ,     ):





											'''simple docstring'''





											_snake_case:   List[str]  					=		vocab_size
											_snake_case:   Optional[int]  					=		max_position_embeddings
											_snake_case:   Dict  					=		hidden_size
											_snake_case:   Union[str, Any]  					=		num_hidden_layers
											_snake_case:   str  					=		num_attention_heads
											_snake_case:   Any  					=		intermediate_size
											_snake_case:   List[Any]  					=		hidden_act
											_snake_case:   int  					=		hidden_dropout_prob
											_snake_case:   List[str]  					=		attention_probs_dropout_prob
											_snake_case:   Optional[Any]  					=		initializer_range
											_snake_case:   Union[str, Any]  					=		layer_norm_eps
											_snake_case:   Dict  					=		scale_embedding
											_snake_case:   Dict  					=		use_cache
											_snake_case:   List[Any]  					=		layerdrop
											_snake_case:   int  					=		activation_dropout
											super().__init__(pad_token_id=__snake_case       ,     bos_token_id=__snake_case       ,     eos_token_id=__snake_case       ,     **__snake_case       )





