import warnings

from ...utils import logging
from .image_processing_deit import DeiTImageProcessor


_lowercase							:      str      							=logging.get_logger(__name__)



class  SCREAMING_SNAKE_CASE_ (					lowerCAmelCase_			):
  '''simple docstring'''


  def __init__(				self    :					Tuple      ,	*SCREAMING_SNAKE_CASE__    :					List[Any]      ,	**SCREAMING_SNAKE_CASE__    :					Any     )    ->				None:
         warnings.warn(
             'The class DeiTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
             ' use DeiTImageProcessor instead.'      ,	SCREAMING_SNAKE_CASE__      ,	)
         super().__init__(*SCREAMING_SNAKE_CASE__      ,	**SCREAMING_SNAKE_CASE__     )







_lowercase							:      Dict      							='''0.21.0'''

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
    from .utils import rich






