





import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset

@pytest.mark.parametrize('dataset_size'	,			[None, 4_00 * 2**20, 6_00 * 2**20] )
@pytest.mark.parametrize('input_in_memory_max_size'	,			['default', 0, 1_00 * 2**20, 9_00 * 2**20] )
def       A__(		__lowerCAmelCase	,			__lowerCAmelCase	,			__lowerCAmelCase ):

				if input_in_memory_max_size != "default":
								monkeypatch.setattr(datasets.config	,			'IN_MEMORY_MAX_SIZE'	,			__lowerCAmelCase )
				_snake_case :			Optional[Any]  						=   datasets.config.IN_MEMORY_MAX_SIZE
				if input_in_memory_max_size == "default":
								assert in_memory_max_size == 0
				else:
								assert in_memory_max_size == input_in_memory_max_size
				if dataset_size and in_memory_max_size:
								_snake_case :			List[Any]  						=   dataset_size < in_memory_max_size
				else:
								_snake_case :			List[Any]  						=   False
				_snake_case :			Any  						=   is_small_dataset(__lowerCAmelCase )
				assert result == expected








import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


lowercase_		:				str				=						logging.get_logger(__name__)


class 			lowercase				(							a_     ):



						"""simple docstring"""

						def __init__(    self			:		int ,				*lowerCamelCase_			:		str ,				**lowerCamelCase_			:		Tuple					):





										'''simple docstring'''







										warnings.warn(
										    'The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
										    ' Please use SegformerImageProcessor instead.' ,				lowerCamelCase_ ,				)
										super().__init__(*lowerCamelCase_ ,				**lowerCamelCase_					)






