

'''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   _UpperCamelCase	(		__UpperCamelCase    ,__UpperCamelCase	)       ->			int:
					assert isinstance(__UpperCamelCase    ,__UpperCamelCase	)
					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   _UpperCamelCase	(		__UpperCamelCase    ,__UpperCamelCase    ,__UpperCamelCase	)       ->			List[str]:
					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(__UpperCamelCase    ,cache_dir=__UpperCamelCase    ,keep_in_memory=__UpperCamelCase	).read()
					_check_json_dataset(__UpperCamelCase    ,__UpperCamelCase	)







@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   _UpperCamelCase	(		__UpperCamelCase    ,__UpperCamelCase    ,__UpperCamelCase	)       ->			Dict:
					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(__UpperCamelCase	) for feature, dtype in features.items()}	) if features is not None else None
					)
					lowerCamelCase_  				=      JsonDatasetReader(__UpperCamelCase    ,features=__UpperCamelCase    ,cache_dir=__UpperCamelCase	).read()
					_check_json_dataset(__UpperCamelCase    ,__UpperCamelCase	)







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







@pytest.mark.parametrize('path_type'    ,[str, list]	)
def   _UpperCamelCase	(		__UpperCamelCase    ,__UpperCamelCase    ,__UpperCamelCase	)       ->			Optional[Any]:
					if issubclass(__UpperCamelCase    ,__UpperCamelCase	):
										lowerCamelCase_  				=      jsonl_path
					elif issubclass(__UpperCamelCase    ,__UpperCamelCase	):
										lowerCamelCase_  				=      [jsonl_path]
					lowerCamelCase_  				=      tmp_path / 'cache'
					lowerCamelCase_  				=      {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
					lowerCamelCase_  				=      JsonDatasetReader(__UpperCamelCase    ,cache_dir=__UpperCamelCase	).read()
					_check_json_dataset(__UpperCamelCase    ,__UpperCamelCase	)







def   _UpperCamelCase	(		__UpperCamelCase    ,__UpperCamelCase    ,__UpperCamelCase=("train",)	)       ->			Optional[int]:
					assert isinstance(__UpperCamelCase    ,__UpperCamelCase	)
					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   _UpperCamelCase	(		__UpperCamelCase    ,__UpperCamelCase    ,__UpperCamelCase	)       ->			Dict:
					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=__UpperCamelCase    ,keep_in_memory=__UpperCamelCase	).read()
					_check_json_datasetdict(__UpperCamelCase    ,__UpperCamelCase	)







@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   _UpperCamelCase	(		__UpperCamelCase    ,__UpperCamelCase    ,__UpperCamelCase	)       ->			Any:
					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(__UpperCamelCase	) for feature, dtype in features.items()}	) if features is not None else None
					)
					lowerCamelCase_  				=      JsonDatasetReader({'train': jsonl_path}    ,features=__UpperCamelCase    ,cache_dir=__UpperCamelCase	).read()
					_check_json_datasetdict(__UpperCamelCase    ,__UpperCamelCase	)







@pytest.mark.parametrize('split'    ,[None, NamedSplit('train'	), 'train', 'test']	)
def   _UpperCamelCase	(		__UpperCamelCase    ,__UpperCamelCase    ,__UpperCamelCase	)       ->			Any:
					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(__UpperCamelCase    ,cache_dir=__UpperCamelCase	).read()
					_check_json_datasetdict(__UpperCamelCase    ,__UpperCamelCase    ,splits=list(path.keys()	)	)
					assert all(dataset[split].split == split for split in path.keys()	)







def   _UpperCamelCase	(		__UpperCamelCase	)       ->			Union[str, Any]:
					return json.load(__UpperCamelCase	)







def   _UpperCamelCase	(		__UpperCamelCase	)       ->			List[str]:
					return [json.loads(__UpperCamelCase	) for line in buffer]







class  UpperCAmelCase :

		'''simple docstring'''






		@pytest.mark.parametrize('lines, load_json_function'   ,			[(True, load_json_lines), (False, load_json)]		)
		def 			UpperCamelCase(					self   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)  ->     Optional[int]:






							'''simple docstring'''



							with io.BytesIO() as buffer:
												JsonDatasetWriter(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			lines=SCREAMING_SNAKE_CASE_		).write()
												buffer.seek(0		)
												lowerCamelCase_  				=      load_json_function(SCREAMING_SNAKE_CASE_		)
							assert isinstance(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)
							assert isinstance(exported_content[0]   ,			SCREAMING_SNAKE_CASE_		)
							assert len(SCREAMING_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 			UpperCamelCase(					self   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)  ->     str:






							'''simple docstring'''



							with io.BytesIO() as buffer:
												JsonDatasetWriter(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			lines=SCREAMING_SNAKE_CASE_   ,			orient=SCREAMING_SNAKE_CASE_		).write()
												buffer.seek(0		)
												lowerCamelCase_  				=      load_json(SCREAMING_SNAKE_CASE_		)
							assert isinstance(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)
							if keys:
												if container is dict:
																	assert exported_content.keys() == keys
												else:
																	assert exported_content[0].keys() == keys
							else:
												assert not hasattr(SCREAMING_SNAKE_CASE_   ,			'keys'		) and not hasattr(exported_content[0]   ,			'keys'		)
							if len_at:
												assert len(exported_content[len_at]		) == 10
							else:
												assert len(SCREAMING_SNAKE_CASE_		) == 10
		@pytest.mark.parametrize('lines, load_json_function'   ,			[(True, load_json_lines), (False, load_json)]		)
		def 			UpperCamelCase(					self   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)  ->     int:






							'''simple docstring'''



							with io.BytesIO() as buffer:
												JsonDatasetWriter(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			lines=SCREAMING_SNAKE_CASE_   ,			num_proc=2		).write()
												buffer.seek(0		)
												lowerCamelCase_  				=      load_json_function(SCREAMING_SNAKE_CASE_		)
							assert isinstance(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)
							assert isinstance(exported_content[0]   ,			SCREAMING_SNAKE_CASE_		)
							assert len(SCREAMING_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 			UpperCamelCase(					self   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)  ->     Any:






							'''simple docstring'''



							with io.BytesIO() as buffer:
												JsonDatasetWriter(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			lines=SCREAMING_SNAKE_CASE_   ,			orient=SCREAMING_SNAKE_CASE_   ,			num_proc=2		).write()
												buffer.seek(0		)
												lowerCamelCase_  				=      load_json(SCREAMING_SNAKE_CASE_		)
							assert isinstance(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)
							if keys:
												if container is dict:
																	assert exported_content.keys() == keys
												else:
																	assert exported_content[0].keys() == keys
							else:
												assert not hasattr(SCREAMING_SNAKE_CASE_   ,			'keys'		) and not hasattr(exported_content[0]   ,			'keys'		)
							if len_at:
												assert len(exported_content[len_at]		) == 10
							else:
												assert len(SCREAMING_SNAKE_CASE_		) == 10
		def 			UpperCamelCase(					self   ,			SCREAMING_SNAKE_CASE_		)  ->     Optional[Any]:






							'''simple docstring'''



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






		@pytest.mark.parametrize('compression, extension'   ,			[('gzip', 'gz'), ('bz2', 'bz2'), ('xz', 'xz')]		)
		def 			UpperCamelCase(					self   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)  ->     Tuple:






							'''simple docstring'''



							lowerCamelCase_  				=      tmp_path_factory.mktemp('data'		) / f'''test.json.{extension}'''
							lowerCamelCase_  				=      str(shared_datadir / f'''test_file.json.{extension}'''		)
							JsonDatasetWriter(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_   ,			compression=SCREAMING_SNAKE_CASE_		).write()

							with fsspec.open(SCREAMING_SNAKE_CASE_   ,			'rb'   ,			compression='infer'		) as f:
												lowerCamelCase_  				=      f.read()
							with fsspec.open(SCREAMING_SNAKE_CASE_   ,			'rb'   ,			compression='infer'		) as f:
												lowerCamelCase_  				=      f.read()
							assert exported_content == original_content









"""simple docstring"""

from datetime import datetime

import matplotlib.pyplot as plt
import torch






def 		_snake_case	(   _snake_case				:   Dict				)       ->   Optional[Any]:






      '''simple docstring'''


      for param in module.parameters():
            _A     =  False






def 		_snake_case	(   )       ->   Tuple:






      '''simple docstring'''


      _A     =  'cuda' if torch.cuda.is_available() else 'cpu'
      if torch.backends.mps.is_available() and torch.backends.mps.is_built():
            _A     =  'mps'
      if device == "mps":
            print(
                'WARNING: MPS currently doesn\'t seem to work, and messes up backpropagation without any visible torch'
                ' errors. I recommend using CUDA on a colab notebook or CPU instead if you\'re facing inexplicable issues'
                ' with generations.'				)
      return device






def 		_snake_case	(   _snake_case				:   Dict				)       ->   Optional[Any]:






      '''simple docstring'''


      _A     =  plt.imshow(_snake_case				)
      fig.axes.get_xaxis().set_visible(_snake_case				)
      fig.axes.get_yaxis().set_visible(_snake_case				)
      plt.show()







def 		_snake_case	(   )       ->   Optional[Any]:






      '''simple docstring'''


      _A     =  datetime.now()
      _A     =  current_time.strftime('%H:%M:%S'				)
      return timestamp

