


"""simple docstring"""






from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


_lowerCAmelCase							:    Optional[int]					   =	logging.get_logger(__name__)

_lowerCAmelCase							:    int					   =	{
    '''google/bit-50''': '''https://huggingface.co/google/bit-50/resolve/main/config.json''',
}




class 							A_      (       _a     ,	_a ):
  lowerCAmelCase__      			=	'bit'
  lowerCAmelCase__      			=	['preactivation', 'bottleneck']
  lowerCAmelCase__      			=	['SAME', 'VALID']


  def __init__(			self:						Tuple							,__lowerCAmelCase:						List[Any]=3							,__lowerCAmelCase:						List[str]=64							,__lowerCAmelCase:						Union[str, Any]=[256, 512, 1_024, 2_048]							,__lowerCAmelCase:						Optional[int]=[3, 4, 6, 3]							,__lowerCAmelCase:						str="preactivation"							,__lowerCAmelCase:						Tuple="relu"							,__lowerCAmelCase:						Tuple=None							,__lowerCAmelCase:						Dict=32							,__lowerCAmelCase:						List[str]=0.0							,__lowerCAmelCase:						Optional[Any]=False							,__lowerCAmelCase:						Dict=32							,__lowerCAmelCase:						Dict=1							,__lowerCAmelCase:						List[Any]=None							,__lowerCAmelCase:						str=None							,**__lowerCAmelCase:						Any							,):







     '''simple docstring'''







     super().__init__(**__lowerCAmelCase    )
     if layer_type not in self.layer_types:
        raise ValueError(F"""layer_type={layer_type} is not one of {','.join(self.layer_types    )}"""    )
     if global_padding is not None:
        if global_padding.upper() in self.supported_padding:
           _lowerCamelCase   :				List[Any]							=     global_padding.upper()
        else:
           raise ValueError(F"""Padding strategy {global_padding} not supported"""    )
     _lowerCamelCase   :				str							=     num_channels
     _lowerCamelCase   :				str							=     embedding_size
     _lowerCamelCase   :				Dict							=     hidden_sizes
     _lowerCamelCase   :				str							=     depths
     _lowerCamelCase   :				Any							=     layer_type
     _lowerCamelCase   :				Any							=     hidden_act
     _lowerCamelCase   :				List[str]							=     global_padding
     _lowerCamelCase   :				Tuple							=     num_groups
     _lowerCamelCase   :				Optional[int]							=     drop_path_rate
     _lowerCamelCase   :				List[Any]							=     embedding_dynamic_padding
     _lowerCamelCase   :				Any							=     output_stride
     _lowerCamelCase   :				List[str]							=     width_factor

     _lowerCamelCase   :				List[Any]							=     ["stem"] + [F"""stage{idx}""" for idx in range(1							,len(__lowerCAmelCase    ) + 1    )]
     _lowerCamelCase,					_lowerCamelCase   :				Union[str, Any]							=     get_aligned_output_features_output_indices(
         out_features=__lowerCAmelCase							,out_indices=__lowerCAmelCase							,stage_names=self.stage_names    )





# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

__a							     =					'2.13.1'

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse('3.7'):
     raise ImportWarning(
         'To use `datasets`, Python>=3.7 is required, and the current version of Python doesn\'t match this condition.'
     )

if version.parse(pyarrow.__version__).major < 8:
     raise ImportWarning(
         'To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn\'t match this condition.\n'
         'If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`.'
     )

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

__a							     =					concatenate_datasets
__a							     =					DownloadConfig
__a							     =					DownloadManager
__a							     =					DownloadMode
__a							     =					DownloadConfig
__a							     =					DownloadMode
__a							     =					DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager