from collections import OrderedDict
from typing import Mapping

from packaging import version

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


snake_case__				= logging.get_logger(__name__)

snake_case__				= {
    'microsoft/swin-tiny-patch4-window7-224': (
        'https://huggingface.co/microsoft/swin-tiny-patch4-window7-224/resolve/main/config.json'
    ),
    # See all Swin models at https://huggingface.co/models?filter=swin
}



class  UpperCamelCase				( __lowercase   ,  __lowercase ):

     '''simple docstring'''

     A_										=  'swin'

     A_										=  {
         'num_attention_heads': 'num_heads',
         'num_hidden_layers': 'num_layers',
     }



     def __init__(					self				,				A_=2_24				,				A_=4				,				A_=3				,				A_=96				,				A_=[2, 2, 6, 2]				,				A_=[3, 6, 12, 24]				,				A_=7				,				A_=4.0				,				A_=True				,				A_=0.0				,				A_=0.0				,				A_=0.1				,				A_="gelu"				,				A_=False				,				A_=0.02				,				A_=1E-5				,				A_=32				,				A_=None				,				A_=None				,				**A_				,				) ->				List[Any]:






           """simple docstring"""
           super().__init__(**A_						)

           _lowerCamelCase			    =				image_size
           _lowerCamelCase			    =				patch_size
           _lowerCamelCase			    =				num_channels
           _lowerCamelCase			    =				embed_dim
           _lowerCamelCase			    =				depths
           _lowerCamelCase			    =				len(A_						)
           _lowerCamelCase			    =				num_heads
           _lowerCamelCase			    =				window_size
           _lowerCamelCase			    =				mlp_ratio
           _lowerCamelCase			    =				qkv_bias
           _lowerCamelCase			    =				hidden_dropout_prob
           _lowerCamelCase			    =				attention_probs_dropout_prob
           _lowerCamelCase			    =				drop_path_rate
           _lowerCamelCase			    =				hidden_act
           _lowerCamelCase			    =				use_absolute_embeddings
           _lowerCamelCase			    =				layer_norm_eps
           _lowerCamelCase			    =				initializer_range
           _lowerCamelCase			    =				encoder_stride
           # we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
           # this indicates the channel dimension after the last stage of the model
           _lowerCamelCase			    =				int(embed_dim * 2 ** (len(A_						) - 1)						)
           _lowerCamelCase			    =				['''stem'''] + [F'stage{idx}' for idx in range(1				,				len(A_						) + 1						)]
           _lowerCamelCase    ,					_lowerCamelCase			    =				get_aligned_output_features_output_indices(
               out_features=A_				,				out_indices=A_				,				stage_names=self.stage_names						)





class  UpperCamelCase				( __lowercase ):

     '''simple docstring'''

     A_										=  version.parse('1.11' )



     @property
     def 		UpperCamelCase_						(					self						) ->				Mapping[str, Mapping[int, str]]:






           """simple docstring"""
           return OrderedDict(
               [
                   ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
               ]						)





     @property
     def 		UpperCamelCase_						(					self						) ->				float:






           """simple docstring"""
           return 1E-4
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,
)