


from __future__ import annotations

import sys







class      __lowercase  :





							"""simple docstring"""







							def __init__(	self       ,		lowerCAmelCase__       ,		lowerCAmelCase__    ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_						:			str       						= letter
										SCREAMING_SNAKE_CASE_						:			int       						= freq
										SCREAMING_SNAKE_CASE_						:			dict[str, str]       						= {}






							def __repr__(	self    ):





										"""simple docstring"""




										return F'''{self.letter}:{self.freq}'''







class      __lowercase  :





							"""simple docstring"""







							def __init__(	self       ,		lowerCAmelCase__       ,		lowerCAmelCase__       ,		lowerCAmelCase__    ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_						:			int       						= freq
										SCREAMING_SNAKE_CASE_						:			Letter | TreeNode       						= left
										SCREAMING_SNAKE_CASE_						:			Letter | TreeNode       						= right







def 		a__       (							A__							):
			SCREAMING_SNAKE_CASE_						:			dict[str, int]       						= {}
			with open(A__							) as f:
						while True:
									SCREAMING_SNAKE_CASE_						:			Any       						= f.read(1							)
									if not c:
												break
									SCREAMING_SNAKE_CASE_						:			Union[str, 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 		a__       (							A__							):
			SCREAMING_SNAKE_CASE_						:			list[Letter | TreeNode]       						= letters  # type: ignore
			while len(A__							) > 1:
						SCREAMING_SNAKE_CASE_						:			int       						= response.pop(0							)
						SCREAMING_SNAKE_CASE_						:			Dict       						= response.pop(0							)
						SCREAMING_SNAKE_CASE_						:			List[str]       						= left.freq + right.freq
						SCREAMING_SNAKE_CASE_						:			int       						= TreeNode(A__,	A__,	A__							)
						response.append(A__							)
						response.sort(key=lambda A__							: x.freq							)
			return response[0]






def 		a__       (							A__,	A__							):
			if isinstance(A__,	A__							):
						SCREAMING_SNAKE_CASE_						:			Optional[int]       						= bitstring
						return [root]
			SCREAMING_SNAKE_CASE_						:			TreeNode       						= root  # type: ignore
			SCREAMING_SNAKE_CASE_						:			List[str]       						= []
			letters += traverse_tree(treenode.left,	bitstring + '0'							)
			letters += traverse_tree(treenode.right,	bitstring + '1'							)
			return letters






def 		a__       (							A__							):
			SCREAMING_SNAKE_CASE_						:			List[str]       						= parse_file(A__							)
			SCREAMING_SNAKE_CASE_						:			List[Any]       						= build_tree(A__							)
			SCREAMING_SNAKE_CASE_						:			Optional[int]       						= {
			    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:
									SCREAMING_SNAKE_CASE_						:			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])









from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__       :	Any     				=logging.get_logger(__name__)

lowerCAmelCase__       :	Union[str, Any]     				={
    'google/reformer-crime-and-punishment': (
        'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/config.json'
    ),
    'google/reformer-enwik8': 'https://huggingface.co/google/reformer-enwik8/resolve/main/config.json',
}







class      __lowercase  (__SCREAMING_SNAKE_CASE   ):





							"""simple docstring"""







							_UpperCAmelCase     =		"""reformer"""
							_UpperCAmelCase     =		["""past_buckets_states"""]
							_UpperCAmelCase     =		{}






							def __init__(	self       ,		lowerCAmelCase__=6_4       ,		lowerCAmelCase__=["local", "lsh", "local", "lsh", "local", "lsh"]       ,		lowerCAmelCase__=1.0       ,		lowerCAmelCase__=True       ,		lowerCAmelCase__=[6_4, 6_4]       ,		lowerCAmelCase__=[6_4, 1_9_2]       ,		lowerCAmelCase__=0       ,		lowerCAmelCase__=2       ,		lowerCAmelCase__=5_1_2       ,		lowerCAmelCase__=None       ,		lowerCAmelCase__="relu"       ,		lowerCAmelCase__=0.05       ,		lowerCAmelCase__=2_5_6       ,		lowerCAmelCase__=0.02       ,		lowerCAmelCase__=False       ,		lowerCAmelCase__=1E-12       ,		lowerCAmelCase__=1       ,		lowerCAmelCase__=0       ,		lowerCAmelCase__=0.05       ,		lowerCAmelCase__=6_4       ,		lowerCAmelCase__=6_4       ,		lowerCAmelCase__=0.0       ,		lowerCAmelCase__=1       ,		lowerCAmelCase__=0       ,		lowerCAmelCase__=4_0_9_6       ,		lowerCAmelCase__=1_2       ,		lowerCAmelCase__=None       ,		lowerCAmelCase__=1       ,		lowerCAmelCase__=0       ,		lowerCAmelCase__=3_2_0       ,		lowerCAmelCase__=False       ,		lowerCAmelCase__=True       ,		lowerCAmelCase__=None       ,		**lowerCAmelCase__       ,		):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_						:			str       						= hash_seed
										SCREAMING_SNAKE_CASE_						:			Union[str, Any]       						= vocab_size
										SCREAMING_SNAKE_CASE_						:			Any       						= attention_head_size
										SCREAMING_SNAKE_CASE_						:			List[Any]       						= hidden_size
										SCREAMING_SNAKE_CASE_						:			Optional[Any]       						= num_attention_heads
										SCREAMING_SNAKE_CASE_						:			Any       						= num_hashes
										SCREAMING_SNAKE_CASE_						:			int       						= len(lowerCAmelCase__    )
										SCREAMING_SNAKE_CASE_						:			str       						= tuple(lowerCAmelCase__    ) if isinstance(lowerCAmelCase__       ,		lowerCAmelCase__    ) else num_buckets
										SCREAMING_SNAKE_CASE_						:			int       						= lsh_attn_chunk_length
										SCREAMING_SNAKE_CASE_						:			List[str]       						= local_attn_chunk_length
										SCREAMING_SNAKE_CASE_						:			Tuple       						= lsh_num_chunks_after
										SCREAMING_SNAKE_CASE_						:			str       						= lsh_num_chunks_before
										SCREAMING_SNAKE_CASE_						:			List[Any]       						= local_num_chunks_after
										SCREAMING_SNAKE_CASE_						:			Any       						= local_num_chunks_before
										SCREAMING_SNAKE_CASE_						:			Any       						= hidden_act
										SCREAMING_SNAKE_CASE_						:			Dict       						= feed_forward_size
										SCREAMING_SNAKE_CASE_						:			Optional[int]       						= hidden_dropout_prob
										SCREAMING_SNAKE_CASE_						:			Tuple       						= lsh_attention_probs_dropout_prob
										SCREAMING_SNAKE_CASE_						:			Any       						= local_attention_probs_dropout_prob
										SCREAMING_SNAKE_CASE_						:			str       						= max_position_embeddings
										SCREAMING_SNAKE_CASE_						:			Optional[int]       						= initializer_range
										SCREAMING_SNAKE_CASE_						:			Optional[Any]       						= layer_norm_eps
										SCREAMING_SNAKE_CASE_						:			List[str]       						= axial_pos_embds
										SCREAMING_SNAKE_CASE_						:			List[str]       						= tuple(lowerCAmelCase__    )
										SCREAMING_SNAKE_CASE_						:			Tuple       						= tuple(lowerCAmelCase__    )
										SCREAMING_SNAKE_CASE_						:			Dict       						= axial_norm_std
										SCREAMING_SNAKE_CASE_						:			Any       						= chunk_size_lm_head
										SCREAMING_SNAKE_CASE_						:			int       						= attn_layers
										SCREAMING_SNAKE_CASE_						:			Union[str, Any]       						= use_cache
										SCREAMING_SNAKE_CASE_						:			Tuple       						= classifier_dropout
										super().__init__(
										    pad_token_id=lowerCAmelCase__       ,		eos_token_id=lowerCAmelCase__       ,		is_decoder=lowerCAmelCase__       ,		tie_word_embeddings=lowerCAmelCase__       ,		**lowerCAmelCase__       ,		)





