


'''simple docstring'''
import warnings

from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor


__snake_case											=					logging.get_logger(__name__)
class        lowercase     (							SCREAMING_SNAKE_CASE_ ):

		"""simple docstring"""

		def __init__(		self   ,       *UpperCamelCase_   ,       **UpperCamelCase_							):

							'''simple docstring'''


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






'''simple docstring'''
from math import ceil


def       a				(      __a			, __a       )  ->     Any:



					'''simple docstring'''






					UpperCamelCase__       :str							 =			list(range(0			, __a       )       )

					UpperCamelCase__       :Optional[int]							 =			[item for sublist in list(device_map.values()       ) for item in sublist]

					# Duplicate check
					UpperCamelCase__       :Optional[int]							 =			[]
					for i in device_map_blocks:
										if device_map_blocks.count(__a       ) > 1 and i not in duplicate_blocks:
															duplicate_blocks.append(__a       )
    # Missing blocks
					UpperCamelCase__       :List[str]							 =			[i for i in blocks if i not in device_map_blocks]
					UpperCamelCase__       :Optional[Any]							 =			[i for i in device_map_blocks if i not in blocks]

					if len(__a       ) != 0:
										raise ValueError(
										    '''Duplicate attention blocks specified in device_map. Attention blocks must be specified to one device.'''
										    ''' These attention blocks were specified more than once: ''' + str(__a       )       )
					if len(__a       ) != 0:
										raise ValueError(
										    '''There are attention blocks for this model that are not specified in the device_map. Add these attention '''
										    '''blocks to a device on the device_map: ''' + str(__a       )       )
					if len(__a       ) != 0:
										raise ValueError(
										    '''The device_map contains more attention blocks than this model has. Remove these from the device_map:'''
										    + str(__a       )       )







def       a				(      __a			, __a       )  ->     Tuple:



					'''simple docstring'''






					UpperCamelCase__       :Optional[Any]							 =			list(range(__a       )       )
					UpperCamelCase__       :Any							 =			int(ceil(n_layers / len(__a       )       )       )
					UpperCamelCase__       :List[Any]							 =			[layers[i : i + n_blocks] for i in range(0			, __a			, __a       )]

					return dict(zip(__a			, __a       )       )