





'''simple docstring'''






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


A_		:  Dict		 =						logging.get_logger(__name__)

A_		:  Optional[Any]		 =						{
    "facebook/convnextv2-tiny-1k-224": "https://huggingface.co/facebook/convnextv2-tiny-1k-224/resolve/main/config.json",
}
class 					__snake_case  (					__SCREAMING_SNAKE_CASE		,				__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   lowerCamelCase__    							=      '''convnextv2'''

   def __init__(							self	,		__SCREAMING_SNAKE_CASE=3	,		__SCREAMING_SNAKE_CASE=4	,		__SCREAMING_SNAKE_CASE=4	,		__SCREAMING_SNAKE_CASE=None	,		__SCREAMING_SNAKE_CASE=None	,		__SCREAMING_SNAKE_CASE="gelu"	,		__SCREAMING_SNAKE_CASE=0.02	,		__SCREAMING_SNAKE_CASE=1e-1_2	,		__SCREAMING_SNAKE_CASE=0.0	,		__SCREAMING_SNAKE_CASE=2_2_4	,		__SCREAMING_SNAKE_CASE=None	,		__SCREAMING_SNAKE_CASE=None	,		**__SCREAMING_SNAKE_CASE	,		):
    super().__init__(**__SCREAMING_SNAKE_CASE       )

    snake_case__     :					Union[str, Any]    =  num_channels
    snake_case__     :					str    =  patch_size
    snake_case__     :					List[Any]    =  num_stages
    snake_case__     :					Optional[Any]    =  [9_6, 1_9_2, 3_8_4, 7_6_8] if hidden_sizes is None else hidden_sizes
    snake_case__     :					Dict    =  [3, 3, 9, 3] if depths is None else depths
    snake_case__     :					List[str]    =  hidden_act
    snake_case__     :					str    =  initializer_range
    snake_case__     :					Tuple    =  layer_norm_eps
    snake_case__     :					int    =  drop_path_rate
    snake_case__     :					Dict    =  image_size
    snake_case__     :					Optional[int]    =  ["""stem"""] + [f"stage{idx}" for idx in range(1	,		len(self.depths       ) + 1       )]
    snake_case__  ,							snake_case__     :					Optional[int]    =  get_aligned_output_features_output_indices(
        out_features=__SCREAMING_SNAKE_CASE	,		out_indices=__SCREAMING_SNAKE_CASE	,		stage_names=self.stage_names       )






'''simple docstring'''
from .data_collator import (
    DataCollatorForLanguageModeling,
    DataCollatorForPermutationLanguageModeling,
    DataCollatorForSeqaSeq,
    DataCollatorForSOP,
    DataCollatorForTokenClassification,
    DataCollatorForWholeWordMask,
    DataCollatorWithPadding,
    DefaultDataCollator,
    default_data_collator,
)
from .metrics import glue_compute_metrics, xnli_compute_metrics
from .processors import (
    DataProcessor,
    InputExample,
    InputFeatures,
    SingleSentenceClassificationProcessor,
    SquadExample,
    SquadFeatures,
    SquadVaProcessor,
    SquadVaProcessor,
    glue_convert_examples_to_features,
    glue_output_modes,
    glue_processors,
    glue_tasks_num_labels,
    squad_convert_examples_to_features,
    xnli_output_modes,
    xnli_processors,
    xnli_tasks_num_labels,
)


