



"""simple docstring"""






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


lowerCAmelCase__              =							logging.get_logger(__name__)






class 			__snake_case			(      _a    ,	_a):
  snake_case__							:  Any         =		'''maskformer-swin'''

  snake_case__							:  Dict         =		{
      '''num_attention_heads''': '''num_heads''',
      '''num_hidden_layers''': '''num_layers''',
  }




  def __init__(					self	:		Tuple		,   __lowerCAmelCase	:		List[Any]=2_2_4		,   __lowerCAmelCase	:		Optional[Any]=4		,   __lowerCAmelCase	:		int=3		,   __lowerCAmelCase	:		Optional[Any]=9_6		,   __lowerCAmelCase	:		Any=[2, 2, 6, 2]		,   __lowerCAmelCase	:		Any=[3, 6, 1_2, 2_4]		,   __lowerCAmelCase	:		str=7		,   __lowerCAmelCase	:		List[str]=4.0		,   __lowerCAmelCase	:		List[str]=True		,   __lowerCAmelCase	:		Tuple=0.0		,   __lowerCAmelCase	:		Tuple=0.0		,   __lowerCAmelCase	:		int=0.1		,   __lowerCAmelCase	:		Optional[Any]="gelu"		,   __lowerCAmelCase	:		Optional[Any]=False		,   __lowerCAmelCase	:		str=0.02		,   __lowerCAmelCase	:		int=1E-5		,   __lowerCAmelCase	:		Optional[Any]=None		,   __lowerCAmelCase	:		Optional[Any]=None		,   **__lowerCAmelCase	:		List[str]		,   ):






         """simple docstring"""






         super().__init__(**__UpperCamelCase						)

         _lowerCamelCase		:							Optional[Any]            =					image_size
         _lowerCamelCase		:							List[str]            =					patch_size
         _lowerCamelCase		:							Any            =					num_channels
         _lowerCamelCase		:							List[str]            =					embed_dim
         _lowerCamelCase		:							Optional[Any]            =					depths
         _lowerCamelCase		:							List[Any]            =					len(__UpperCamelCase						)
         _lowerCamelCase		:							Optional[Any]            =					num_heads
         _lowerCamelCase		:							Any            =					window_size
         _lowerCamelCase		:							Tuple            =					mlp_ratio
         _lowerCamelCase		:							Optional[int]            =					qkv_bias
         _lowerCamelCase		:							Dict            =					hidden_dropout_prob
         _lowerCamelCase		:							Any            =					attention_probs_dropout_prob
         _lowerCamelCase		:							List[str]            =					drop_path_rate
         _lowerCamelCase		:							str            =					hidden_act
         _lowerCamelCase		:							Dict            =					use_absolute_embeddings
         _lowerCamelCase		:							Any            =					layer_norm_eps
         _lowerCamelCase		:							Union[str, Any]            =					initializer_range
         # 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		:							List[Any]            =					int(embed_dim * 2 ** (len(__UpperCamelCase						) - 1)						)
         _lowerCamelCase		:							Optional[Any]            =					['''stem'''] + [f'''stage{idx}''' for idx in range(1		,   len(__UpperCamelCase						) + 1						)]
         _lowerCamelCase     ,       _lowerCamelCase		:							Any            =					get_aligned_output_features_output_indices(
             out_features=__UpperCamelCase		,   out_indices=__UpperCamelCase		,   stage_names=self.stage_names						)




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 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	List[Any]       )  ->     Optional[int]:
						return {key.lstrip("""-"""       ): value for key, value in zip(unknown_args[::2]		,   unknown_args[1::2]       )}




def 	UpperCamelCase__  (     )  ->     Dict:
						_lowercase					       =					ArgumentParser(
						    """HuggingFace Datasets CLI tool"""		,   usage="""datasets-cli <command> [<args>]"""		,   allow_abbrev=SCREAMING_SNAKE_CASE_       )
						_lowercase					       =					parser.add_subparsers(help="""datasets-cli command helpers"""       )
						set_verbosity_info()

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

						# Parse args
						_lowercase       ,						_lowercase					       =					parser.parse_known_args()
						if not hasattr(SCREAMING_SNAKE_CASE_		,   """func"""       ):
												parser.print_help()
												exit(1       )
						_lowercase					       =					parse_unknown_args(SCREAMING_SNAKE_CASE_       )

						# Run
						_lowercase					       =					args.func(SCREAMING_SNAKE_CASE_		,   **SCREAMING_SNAKE_CASE_       )
						service.run()


if __name__ == "__main__":
		main()