





import copy
from typing import Dict, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


UpperCAmelCase_       : Optional[Any]							=    logging.get_logger(__name__)

UpperCAmelCase_       : Optional[int]							=    {
    """shi-labs/oneformer_ade20k_swin_tiny""": (
        """https://huggingface.co/shi-labs/oneformer_ade20k_swin_tiny/blob/main/config.json"""
    ),
    # See all OneFormer models at https://huggingface.co/models?filter=oneformer
}





class   lowercase__     (				__A	):
  __UpperCamelCase						  =	"""oneformer"""
  __UpperCamelCase						  =	{"""hidden_size""": """hidden_dim"""}







  def __init__(						self     ,    _lowercase = None     ,    _lowercase = 255     ,    _lowercase = 150     ,    _lowercase = 0.1     ,    _lowercase = 2.0     ,    _lowercase = 5.0     ,    _lowercase = 5.0     ,    _lowercase = 0.5     ,    _lowercase = 0.07     ,    _lowercase = 12_544     ,    _lowercase = 3.0     ,    _lowercase = 0.75     ,    _lowercase = 0.02     ,    _lowercase = 1.0     ,    _lowercase = 1e-05     ,    _lowercase = False     ,    _lowercase = True     ,    _lowercase = True     ,    _lowercase = [4, 8, 16, 32]     ,    _lowercase = 77     ,    _lowercase = 256     ,    _lowercase = 77     ,    _lowercase = 6     ,    _lowercase = 49_408     ,    _lowercase = 2     ,    _lowercase = 16     ,    _lowercase = 256     ,    _lowercase = 256     ,    _lowercase = 256     ,    _lowercase = 1_024     ,    _lowercase = "GN"     ,    _lowercase = 6     ,    _lowercase = 10     ,    _lowercase = True     ,    _lowercase = 8     ,    _lowercase = 0.1     ,    _lowercase = 2_048     ,    _lowercase = False     ,    _lowercase = False     ,    _lowercase = 2     ,    _lowercase = 4     ,    **_lowercase     ,    ):
       if backbone_config is None:
            logger.info("""`backbone_config` is unset. Initializing the config with the default `Swin` backbone."""    )
            lowerCAmelCase_       :							List[str]			 =		CONFIG_MAPPING["""swin"""](
                image_size=224     ,    in_channels=3     ,    patch_size=4     ,    embed_dim=96     ,    depths=[2, 2, 6, 2]     ,    num_heads=[3, 6, 12, 24]     ,    window_size=7     ,    drop_path_rate=0.3     ,    use_absolute_embeddings=_lowercase     ,    out_features=["""stage1""", """stage2""", """stage3""", """stage4"""]     ,    )
       elif isinstance(_lowercase     ,    _lowercase    ):
            lowerCAmelCase_       :							Any			 =		backbone_config.get("""model_type"""    )
            lowerCAmelCase_       :							int			 =		CONFIG_MAPPING[backbone_model_type]
            lowerCAmelCase_       :							Union[str, Any]			 =		config_class.from_dict(_lowercase    )

       lowerCAmelCase_       :							List[Any]			 =		backbone_config

       lowerCAmelCase_       :							Union[str, Any]			 =		ignore_value
       lowerCAmelCase_       :							List[Any]			 =		num_queries
       lowerCAmelCase_       :							List[str]			 =		no_object_weight
       lowerCAmelCase_       :							int			 =		class_weight
       lowerCAmelCase_       :							Optional[Any]			 =		mask_weight
       lowerCAmelCase_       :							Dict			 =		dice_weight
       lowerCAmelCase_       :							Optional[Any]			 =		contrastive_weight
       lowerCAmelCase_       :							str			 =		contrastive_temperature
       lowerCAmelCase_       :							int			 =		train_num_points
       lowerCAmelCase_       :							Optional[Any]			 =		oversample_ratio
       lowerCAmelCase_       :							Any			 =		importance_sample_ratio
       lowerCAmelCase_       :							List[str]			 =		init_std
       lowerCAmelCase_       :							List[Any]			 =		init_xavier_std
       lowerCAmelCase_       :							List[str]			 =		layer_norm_eps
       lowerCAmelCase_       :							Optional[int]			 =		is_training
       lowerCAmelCase_       :							Dict			 =		use_auxiliary_loss
       lowerCAmelCase_       :							Any			 =		output_auxiliary_logits
       lowerCAmelCase_       :							Optional[Any]			 =		strides
       lowerCAmelCase_       :							Optional[int]			 =		task_seq_len
       lowerCAmelCase_       :							List[str]			 =		text_encoder_width
       lowerCAmelCase_       :							Union[str, Any]			 =		text_encoder_context_length
       lowerCAmelCase_       :							Dict			 =		text_encoder_num_layers
       lowerCAmelCase_       :							List[str]			 =		text_encoder_vocab_size
       lowerCAmelCase_       :							Optional[Any]			 =		text_encoder_proj_layers
       lowerCAmelCase_       :							str			 =		text_encoder_n_ctx
       lowerCAmelCase_       :							Optional[int]			 =		conv_dim
       lowerCAmelCase_       :							Tuple			 =		mask_dim
       lowerCAmelCase_       :							Optional[int]			 =		hidden_dim
       lowerCAmelCase_       :							Optional[Any]			 =		encoder_feedforward_dim
       lowerCAmelCase_       :							Optional[int]			 =		norm
       lowerCAmelCase_       :							str			 =		encoder_layers
       lowerCAmelCase_       :							List[str]			 =		decoder_layers
       lowerCAmelCase_       :							List[str]			 =		use_task_norm
       lowerCAmelCase_       :							Union[str, Any]			 =		num_attention_heads
       lowerCAmelCase_       :							int			 =		dropout
       lowerCAmelCase_       :							Optional[Any]			 =		dim_feedforward
       lowerCAmelCase_       :							Any			 =		pre_norm
       lowerCAmelCase_       :							Optional[Any]			 =		enforce_input_proj
       lowerCAmelCase_       :							str			 =		query_dec_layers
       lowerCAmelCase_       :							Optional[int]			 =		common_stride
       lowerCAmelCase_       :							List[str]			 =		decoder_layers

       super().__init__(**_lowercase    )







  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							str			 =		copy.deepcopy(self.__dict__    )
       lowerCAmelCase_       :							List[str]			 =		self.backbone_config.to_dict()
       lowerCAmelCase_       :							List[str]			 =		self.__class__.model_type
       return output







from __future__ import annotations

import sys





class   lowercase__     :







  def __init__(						self     ,    _lowercase     ,    _lowercase    ):
       lowerCAmelCase_       :							str			 =		letter
       lowerCAmelCase_       :							int			 =		freq
       lowerCAmelCase_       :							dict[str, str]			 =		{}







  def __repr__(						self    ):
       return F'{self.letter}:{self.freq}'





class   lowercase__     :







  def __init__(						self     ,    _lowercase     ,    _lowercase     ,    _lowercase    ):
       lowerCAmelCase_       :							int			 =		freq
       lowerCAmelCase_       :							Letter | TreeNode			 =		left
       lowerCAmelCase_       :							Letter | TreeNode			 =		right






def 				_lowerCAmelCase			(	_a :       str      )						->      list[Letter]:
     lowerCAmelCase_       :							dict[str, int]			 =		{}
     with open(_a      ) as f:
          while True:
               lowerCAmelCase_       :							Any			 =		f.read(1      )
               if not c:
                    break
               lowerCAmelCase_       :							List[str]			 =		chars[c] + 1 if c in chars else 1
     return sorted((Letter(_a       , _a      ) for c, f in chars.items())       , key=lambda _a      : x.freq      )






def 				_lowerCAmelCase			(	_a :       list[Letter]      )						->      Letter | TreeNode:
     lowerCAmelCase_       :							list[Letter | TreeNode]			 =		letters  # type: ignore
     while len(_a      ) > 1:
          lowerCAmelCase_       :							Any			 =		response.pop(0      )
          lowerCAmelCase_       :							int			 =		response.pop(0      )
          lowerCAmelCase_       :							List[Any]			 =		left.freq + right.freq
          lowerCAmelCase_       :							Union[str, Any]			 =		TreeNode(_a       , _a       , _a      )
          response.append(_a      )
          response.sort(key=lambda _a      : x.freq      )
     return response[0]






def 				_lowerCAmelCase			(	_a :       Letter | TreeNode       , _a :       str      )						->      list[Letter]:
     if isinstance(_a       , _a      ):
          lowerCAmelCase_       :							Union[str, Any]			 =		bitstring
          return [root]
     lowerCAmelCase_       :							TreeNode			 =		root  # type: ignore
     lowerCAmelCase_       :							Tuple			 =		[]
     letters += traverse_tree(treenode.left       , bitstring + """0"""      )
     letters += traverse_tree(treenode.right       , bitstring + """1"""      )
     return letters






def 				_lowerCAmelCase			(	_a :       str      )						->      None:
     lowerCAmelCase_       :							Optional[Any]			 =		parse_file(_a      )
     lowerCAmelCase_       :							Optional[int]			 =		build_tree(_a      )
     lowerCAmelCase_       :							str			 =		{
         k: v for letter in traverse_tree(_a       , """"""      ) for k, v in letter.bitstring.items()
     }
     print(F'Huffman Coding  of {file_path}: '      )
     with open(_a      ) as f:
          while True:
               lowerCAmelCase_       :							Optional[Any]			 =		f.read(1      )
               if not c:
                    break
               print(letters[c]       , end=""" """      )
     print()


if __name__ == "__main__":
      # pass the file path to the huffman function
      huffman(sys.argv[1])
