

import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig


_SCREAMING_SNAKE_CASE					:  str             =      logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE					:  int             =      {
    '''Intel/dpt-large''': '''https://huggingface.co/Intel/dpt-large/resolve/main/config.json''',
    # See all DPT models at https://huggingface.co/models?filter=dpt
}






class 	UpperCAmelCase__		(	A__	):






  """simple docstring"""


  a									= "dpt"






  def __init__(							self						:		List[Any]     ,       __lowerCamelCase						:		Union[str, Any]=768     ,       __lowerCamelCase						:		List[str]=12     ,       __lowerCamelCase						:		Tuple=12     ,       __lowerCamelCase						:		Dict=3072     ,       __lowerCamelCase						:		Tuple="gelu"     ,       __lowerCamelCase						:		Optional[int]=0.0     ,       __lowerCamelCase						:		Any=0.0     ,       __lowerCamelCase						:		List[Any]=0.02     ,       __lowerCamelCase						:		Dict=1e-12     ,       __lowerCamelCase						:		Union[str, Any]=384     ,       __lowerCamelCase						:		List[Any]=16     ,       __lowerCamelCase						:		Optional[int]=3     ,       __lowerCamelCase						:		List[Any]=False     ,       __lowerCamelCase						:		Any=True     ,       __lowerCamelCase						:		Union[str, Any]=[2, 5, 8, 11]     ,       __lowerCamelCase						:		Any="project"     ,       __lowerCamelCase						:		Optional[int]=[4, 2, 1, 0.5]     ,       __lowerCamelCase						:		List[str]=[96, 192, 384, 768]     ,       __lowerCamelCase						:		Optional[int]=256     ,       __lowerCamelCase						:		List[Any]=-1     ,       __lowerCamelCase						:		int=False     ,       __lowerCamelCase						:		Optional[Any]=True     ,       __lowerCamelCase						:		Union[str, Any]=0.4     ,       __lowerCamelCase						:		str=255     ,       __lowerCamelCase						:		int=0.1     ,       __lowerCamelCase						:		List[Any]=[1, 1024, 24, 24]     ,       __lowerCamelCase						:		List[str]=[0, 1]     ,       __lowerCamelCase						:		Tuple=None     ,       **__lowerCamelCase						:		str     ,       )		->							List[Any]:
       super().__init__(**__lowerCamelCase )

       SCREAMING_SNAKE_CASE__   =   hidden_size
       SCREAMING_SNAKE_CASE__   =   is_hybrid

       if self.is_hybrid:
            if backbone_config is None:
                 logger.info('''Initializing the config with a `BiT` backbone.''' )
                 SCREAMING_SNAKE_CASE__   =   {
                     '''global_padding''': '''same''',
                     '''layer_type''': '''bottleneck''',
                     '''depths''': [3, 4, 9],
                     '''out_features''': ['''stage1''', '''stage2''', '''stage3'''],
                     '''embedding_dynamic_padding''': True,
                 }
                 SCREAMING_SNAKE_CASE__   =   BitConfig(**__lowerCamelCase )
            elif isinstance(__lowerCamelCase     ,       __lowerCamelCase ):
                 logger.info('''Initializing the config with a `BiT` backbone.''' )
                 SCREAMING_SNAKE_CASE__   =   BitConfig(**__lowerCamelCase )
            elif isinstance(__lowerCamelCase     ,       __lowerCamelCase ):
                 SCREAMING_SNAKE_CASE__   =   backbone_config
            else:
                 raise ValueError(
                     f'''backbone_config must be a dictionary or a `PretrainedConfig`, got {backbone_config.__class__}.''' )

            SCREAMING_SNAKE_CASE__   =   backbone_featmap_shape
            SCREAMING_SNAKE_CASE__   =   neck_ignore_stages

            if readout_type != "project":
                 raise ValueError('''Readout type must be \'project\' when using `DPT-hybrid` mode.''' )
       else:
            SCREAMING_SNAKE_CASE__   =   None
            SCREAMING_SNAKE_CASE__   =   None
            SCREAMING_SNAKE_CASE__   =   []

       SCREAMING_SNAKE_CASE__   =   num_hidden_layers
       SCREAMING_SNAKE_CASE__   =   num_attention_heads
       SCREAMING_SNAKE_CASE__   =   intermediate_size
       SCREAMING_SNAKE_CASE__   =   hidden_act
       SCREAMING_SNAKE_CASE__   =   hidden_dropout_prob
       SCREAMING_SNAKE_CASE__   =   attention_probs_dropout_prob
       SCREAMING_SNAKE_CASE__   =   initializer_range
       SCREAMING_SNAKE_CASE__   =   layer_norm_eps
       SCREAMING_SNAKE_CASE__   =   image_size
       SCREAMING_SNAKE_CASE__   =   patch_size
       SCREAMING_SNAKE_CASE__   =   num_channels
       SCREAMING_SNAKE_CASE__   =   qkv_bias
       SCREAMING_SNAKE_CASE__   =   backbone_out_indices
       if readout_type not in ["ignore", "add", "project"]:
            raise ValueError('''Readout_type must be one of [\'ignore\', \'add\', \'project\']''' )
       SCREAMING_SNAKE_CASE__   =   readout_type
       SCREAMING_SNAKE_CASE__   =   reassemble_factors
       SCREAMING_SNAKE_CASE__   =   neck_hidden_sizes
       SCREAMING_SNAKE_CASE__   =   fusion_hidden_size
       SCREAMING_SNAKE_CASE__   =   head_in_index
       SCREAMING_SNAKE_CASE__   =   use_batch_norm_in_fusion_residual
       # auxiliary head attributes (semantic segmentation)
       SCREAMING_SNAKE_CASE__   =   use_auxiliary_head
       SCREAMING_SNAKE_CASE__   =   auxiliary_loss_weight
       SCREAMING_SNAKE_CASE__   =   semantic_loss_ignore_index
       SCREAMING_SNAKE_CASE__   =   semantic_classifier_dropout







  def 				lowercase_		(							self						:		Optional[Any] )		->							Tuple:
       SCREAMING_SNAKE_CASE__   =   copy.deepcopy(self.__dict__ )

       if output["backbone_config"] is not None:
            SCREAMING_SNAKE_CASE__   =   self.backbone_config.to_dict()

       SCREAMING_SNAKE_CASE__   =   self.__class__.model_type
       return output





from argparse import ArgumentParser

from .env import EnvironmentCommand
def     UpperCAmelCase_       (						):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   ArgumentParser('''Diffusers CLI tool'''				,		usage='''diffusers-cli <command> [<args>]'''    )
     SCREAMING_SNAKE_CASE__   =   parser.add_subparsers(help='''diffusers-cli command helpers'''    )

     # Register commands
     EnvironmentCommand.register_subcommand(_A    )

     # Let's go
     SCREAMING_SNAKE_CASE__   =   parser.parse_args()

     if not hasattr(_A				,		'''func'''    ):
          parser.print_help()
          exit(1    )

     # Run
     SCREAMING_SNAKE_CASE__   =   args.func(_A    )
     service.run()


if __name__ == "__main__":
       main()


