

from __future__ import annotations

import sys



class 					A__:
						"""simple docstring"""






						def __init__(						self     ,			_lowercase     ,			_lowercase						)    ->   Union[str, Any]:
									a_	:	str          =   letter
									a_	:	int          =   freq
									a_	:	dict[str, str]          =   {}





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







class 					A__:
						"""simple docstring"""






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







def 				_UpperCAmelCase							(	a__):

			'''simple docstring'''



			a_	:	dict[str, int]          =   {}
			with open(a__) as f:
						while True:
									a_	:	Tuple          =   f.read(1)
									if not c:
												break
									a_	:	Any          =   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 				_UpperCAmelCase							(	a__):

			'''simple docstring'''



			a_	:	list[Letter | TreeNode]          =   letters  # type: ignore
			while len(a__) > 1:
						a_	:	Union[str, Any]          =   response.pop(0)
						a_	:	Optional[Any]          =   response.pop(0)
						a_	:	Union[str, Any]          =   left.freq + right.freq
						a_	:	str          =   TreeNode(a__     ,  a__     ,  a__)
						response.append(a__)
						response.sort(key=lambda a__: x.freq)
			return response[0]


def 				_UpperCAmelCase							(	a__     ,  a__):

			'''simple docstring'''



			if isinstance(a__     ,  a__):
						a_	:	List[str]          =   bitstring
						return [root]
			a_	:	TreeNode          =   root  # type: ignore
			a_	:	List[Any]          =   []
			letters += traverse_tree(treenode.left     ,  bitstring + """0""")
			letters += traverse_tree(treenode.right     ,  bitstring + """1""")
			return letters


def 				_UpperCAmelCase							(	a__):

			'''simple docstring'''



			a_	:	int          =   parse_file(a__)
			a_	:	str          =   build_tree(a__)
			a_	:	Any          =   {
			    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:
									a_	:	str          =   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])





import copy
from typing import Dict

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
from ..bit import BitConfig


__snake_case							:			int      		= logging.get_logger(__name__)

__snake_case							:			Dict      		= {
    """google/vit-hybrid-base-bit-384""": """https://huggingface.co/vit-hybrid-base-bit-384/resolve/main/config.json""",
    # See all ViT hybrid models at https://huggingface.co/models?filter=vit
}



class 					A__(a_       ):
						"""simple docstring"""






						_A						:							Dict									= '''vit-hybrid'''





						def __init__(						self     ,			_lowercase=None     ,			_lowercase=768     ,			_lowercase=12     ,			_lowercase=12     ,			_lowercase=3_072     ,			_lowercase="gelu"     ,			_lowercase=0.0     ,			_lowercase=0.0     ,			_lowercase=0.0_2     ,			_lowercase=1e-12     ,			_lowercase=224     ,			_lowercase=1     ,			_lowercase=3     ,			_lowercase=[1, 1_024, 24, 24]     ,			_lowercase=True     ,			**_lowercase     ,			)    ->   Tuple:
									super().__init__(**_lowercase						)

									if backbone_config is None:
												logger.info("""`backbone_config` is `None`. Initializing the config with a `BiT` backbone."""						)
												a_	:	Union[str, Any]          =   {
												    """global_padding""": """same""",
												    """layer_type""": """bottleneck""",
												    """depths""": [3, 4, 9],
												    """out_features""": ["""stage3"""],
												    """embedding_dynamic_padding""": True,
												}

									if isinstance(_lowercase     ,			_lowercase						):
												if "model_type" in backbone_config:
															a_	:	Any          =   CONFIG_MAPPING[backbone_config["""model_type"""]]
												else:
															logger.info(
															    """`model_type` is not found in `backbone_config`. Use `Bit` as the backbone configuration class."""						)
															a_	:	Optional[int]          =   BitConfig
												a_	:	Dict          =   backbone_config_class(**_lowercase						)

									a_	:	List[str]          =   backbone_featmap_shape
									a_	:	int          =   backbone_config
									a_	:	Union[str, Any]          =   hidden_size
									a_	:	Optional[int]          =   num_hidden_layers
									a_	:	Dict          =   num_attention_heads
									a_	:	Optional[int]          =   intermediate_size
									a_	:	Dict          =   hidden_act
									a_	:	Optional[Any]          =   hidden_dropout_prob
									a_	:	List[str]          =   attention_probs_dropout_prob
									a_	:	Tuple          =   initializer_range
									a_	:	Any          =   layer_norm_eps
									a_	:	List[Any]          =   image_size
									a_	:	Optional[Any]          =   patch_size
									a_	:	Optional[Any]          =   num_channels
									a_	:	str          =   qkv_bias





						def  UpperCamelCase__				(						self						)    ->   Dict[str, any]:
									a_	:	List[str]          =   copy.deepcopy(self.__dict__						)
									a_	:	Optional[int]          =   self.backbone_config.to_dict()
									a_	:	List[str]          =   self.__class__.model_type
									return output


