




'''simple docstring'''







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


A     =logging.get_logger(__name__)

A     ={
    '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 			_a  (	__a							,							__a ):
       __a				:     Optional[Any]   				=					"""swin"""

       __a				:     Optional[Any]   				=					{
           """num_attention_heads""": """num_heads""",
           """num_hidden_layers""": """num_layers""",
       }
       def __init__(	self						:	str   ,				lowercase						:	List[Any]=224   ,				lowercase						:	Union[str, Any]=4   ,				lowercase						:	str=3   ,				lowercase						:	Union[str, Any]=96   ,				lowercase						:	Any=[2, 2, 6, 2]   ,				lowercase						:	Tuple=[3, 6, 12, 24]   ,				lowercase						:	Any=7   ,				lowercase						:	Optional[Any]=4.0   ,				lowercase						:	int=True   ,				lowercase						:	int=0.0   ,				lowercase						:	Optional[int]=0.0   ,				lowercase						:	Dict=0.1   ,				lowercase						:	Tuple="gelu"   ,				lowercase						:	Any=False   ,				lowercase						:	int=0.02   ,				lowercase						:	List[str]=1E-5   ,				lowercase						:	int=32   ,				lowercase						:	Any=None   ,				lowercase						:	str=None   ,				**lowercase						:	List[Any]   ,				):



           '''simple docstring'''

           super().__init__(**lowercase				)

           UpperCAmelCase			       =		image_size
           UpperCAmelCase			       =		patch_size
           UpperCAmelCase			       =		num_channels
           UpperCAmelCase			       =		embed_dim
           UpperCAmelCase			       =		depths
           UpperCAmelCase			       =		len(lowercase				)
           UpperCAmelCase			       =		num_heads
           UpperCAmelCase			       =		window_size
           UpperCAmelCase			       =		mlp_ratio
           UpperCAmelCase			       =		qkv_bias
           UpperCAmelCase			       =		hidden_dropout_prob
           UpperCAmelCase			       =		attention_probs_dropout_prob
           UpperCAmelCase			       =		drop_path_rate
           UpperCAmelCase			       =		hidden_act
           UpperCAmelCase			       =		use_absolute_embeddings
           UpperCAmelCase			       =		layer_norm_eps
           UpperCAmelCase			       =		initializer_range
           UpperCAmelCase			       =		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
           UpperCAmelCase			       =		int(embed_dim * 2 ** (len(lowercase				) - 1)				)
           UpperCAmelCase			       =		['''stem'''] + [f"stage{idx}" for idx in range(1   ,				len(lowercase				) + 1				)]
           UpperCAmelCase       ,     UpperCAmelCase			       =		get_aligned_output_features_output_indices(
               out_features=lowercase   ,				out_indices=lowercase   ,				stage_names=self.stage_names				)






class 			_a  (	__a ):
       __a				:     Optional[Any]   				=					version.parse("""1.11""" )
       @property
       def     A      (	self						:	Tuple				):



           '''simple docstring'''

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







       @property
       def     A      (	self						:	int				):



           '''simple docstring'''

           return 1E-4










'''simple docstring'''







from argparse import ArgumentParser

from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from datasets.utils.logging import set_verbosity_info





def 						snake_case_							(_a	:							Tuple     ):
    return {key.lstrip('''-'''     ): value for key, value in zip(unknown_args[::2]    ,   unknown_args[1::2]     )}





def 						snake_case_							():
    UpperCAmelCase			       =		ArgumentParser(
        '''HuggingFace Datasets CLI tool'''    ,   usage='''datasets-cli <command> [<args>]'''    ,   allow_abbrev=_a     )
    UpperCAmelCase			       =		parser.add_subparsers(help='''datasets-cli command helpers'''     )
    set_verbosity_info()

    # Register commands
    ConvertCommand.register_subcommand(_a     )
    EnvironmentCommand.register_subcommand(_a     )
    TestCommand.register_subcommand(_a     )
    RunBeamCommand.register_subcommand(_a     )
    DummyDataCommand.register_subcommand(_a     )

    # Parse args
    UpperCAmelCase       ,     UpperCAmelCase			       =		parser.parse_known_args()
    if not hasattr(_a    ,   '''func'''     ):
        parser.print_help()
        exit(1     )
    UpperCAmelCase			       =		parse_unknown_args(_a     )

    # Run
    UpperCAmelCase			       =		args.func(_a    ,   **_a     )
    service.run()


if __name__ == "__main__":
   main()




