


'''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       (				UpperCamelCase__       :					Tuple,				UpperCamelCase__       :					Any			):
 assert isinstance(lowerCAmelCase__,				lowerCAmelCase__			)
 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       (				UpperCamelCase__       :					int,				UpperCamelCase__       :					int,				UpperCamelCase__       :					int			):
 __A  :		int       =			tmp_path / 'cache'
 __A  :		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():
  __A  :		Union[str, Any]       =			JsonDatasetReader(lowerCAmelCase__,				cache_dir=lowerCAmelCase__,				keep_in_memory=lowerCAmelCase__			).read()
 _check_json_dataset(lowerCAmelCase__,				lowerCAmelCase__			)


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


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


@pytest.mark.parametrize('path_type',				[str, list]			)
def 			_lowercase       (				UpperCamelCase__       :					List[Any],				UpperCamelCase__       :					List[Any],				UpperCamelCase__       :					List[Any]			):
 if issubclass(lowerCAmelCase__,				lowerCAmelCase__			):
  __A  :		Optional[Any]       =			jsonl_path
 elif issubclass(lowerCAmelCase__,				lowerCAmelCase__			):
  __A  :		Optional[Any]       =			[jsonl_path]
 __A  :		Optional[Any]       =			tmp_path / 'cache'
 __A  :		Dict       =			{'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'}
 __A  :		List[str]       =			JsonDatasetReader(lowerCAmelCase__,				cache_dir=lowerCAmelCase__			).read()
 _check_json_dataset(lowerCAmelCase__,				lowerCAmelCase__			)


def 			_lowercase       (				UpperCamelCase__       :					List[Any],				UpperCamelCase__       :					List[str],				UpperCamelCase__       :					Dict=("train",)			):
 assert isinstance(lowerCAmelCase__,				lowerCAmelCase__			)
 for split in splits:
  __A  :		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       (				UpperCamelCase__       :					str,				UpperCamelCase__       :					Optional[Any],				UpperCamelCase__       :					Dict			):
 __A  :		List[str]       =			tmp_path / 'cache'
 __A  :		List[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():
  __A  :		List[Any]       =			JsonDatasetReader({'train': jsonl_path},				cache_dir=lowerCAmelCase__,				keep_in_memory=lowerCAmelCase__			).read()
 _check_json_datasetdict(lowerCAmelCase__,				lowerCAmelCase__			)


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


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


def 			_lowercase       (				UpperCamelCase__       :					List[Any]			):
 return json.load(lowerCAmelCase__			)


def 			_lowercase       (				UpperCamelCase__       :					List[Any]			):
 return [json.loads(lowerCAmelCase__			) for line in buffer]


class 						_lowerCamelCase					:




 '''simple docstring'''


 @pytest.mark.parametrize('lines, load_json_function'      ,      [(True, load_json_lines), (False, load_json)]						)
 def  snake_case__   (      self      ,      __lowercase      ,      __lowercase      ,      __lowercase						):

  """simple docstring"""







  with io.BytesIO() as buffer:
   JsonDatasetWriter(snake_case__      ,      snake_case__      ,      lines=snake_case__						).write()
   buffer.seek(0						)
   __A  :		Tuple       =			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  snake_case__   (      self      ,      __lowercase      ,      __lowercase      ,      __lowercase      ,      __lowercase      ,      __lowercase						):

  """simple docstring"""







  with io.BytesIO() as buffer:
   JsonDatasetWriter(snake_case__      ,      snake_case__      ,      lines=snake_case__      ,      orient=snake_case__						).write()
   buffer.seek(0						)
   __A  :		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  snake_case__   (      self      ,      __lowercase      ,      __lowercase      ,      __lowercase						):

  """simple docstring"""







  with io.BytesIO() as buffer:
   JsonDatasetWriter(snake_case__      ,      snake_case__      ,      lines=snake_case__      ,      num_proc=2						).write()
   buffer.seek(0						)
   __A  :		Tuple       =			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  snake_case__   (      self      ,      __lowercase      ,      __lowercase      ,      __lowercase      ,      __lowercase      ,      __lowercase						):

  """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						)
   __A  :		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  snake_case__   (      self      ,      __lowercase						):

  """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  snake_case__   (      self      ,      __lowercase      ,      __lowercase      ,      __lowercase      ,      __lowercase      ,      __lowercase						):

  """simple docstring"""







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










'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_ :     Dict								=      logging.get_logger(__name__)

UpperCAmelCase_ :     Optional[int]								=      {
    'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}

class 						_lowerCamelCase					(    snake_case_				):




 '''simple docstring'''
 __lowercase				:		Tuple    							=						'''vit_msn'''


 def __init__(      self      ,      __lowercase=768      ,      __lowercase=12      ,      __lowercase=12      ,      __lowercase=3_072      ,      __lowercase="gelu"      ,      __lowercase=0.0      ,      __lowercase=0.0      ,      __lowercase=0.0_2      ,      __lowercase=1E-06      ,      __lowercase=224      ,      __lowercase=16      ,      __lowercase=3      ,      __lowercase=True      ,      **__lowercase      ,      ):

  """simple docstring"""







  super().__init__(**__lowercase						)

  __A  :		Tuple       =			hidden_size
  __A  :		Optional[int]       =			num_hidden_layers
  __A  :		str       =			num_attention_heads
  __A  :		Dict       =			intermediate_size
  __A  :		Optional[Any]       =			hidden_act
  __A  :		Union[str, Any]       =			hidden_dropout_prob
  __A  :		Optional[Any]       =			attention_probs_dropout_prob
  __A  :		List[str]       =			initializer_range
  __A  :		Dict       =			layer_norm_eps
  __A  :		List[Any]       =			image_size
  __A  :		Optional[int]       =			patch_size
  __A  :		List[Any]       =			num_channels
  __A  :		Optional[Any]       =			qkv_bias






