
"""simple docstring"""







import collections
import os
from typing import List, Optional, Tuple

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
       import jieba

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


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

lowerCamelCase_       :       List[Any]      						=  {"""vocab_file""": """vocab.txt"""}

lowerCamelCase_       :       List[Any]      						=  {
    """vocab_file""": {
        """openbmb/cpm-ant-10b""": """https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt""",
    },
}

lowerCamelCase_       :       Union[str, Any]      						=  {
    """openbmb/cpm-ant-10b""": 1_0_2_4,
}
def _A						(						lowercase		):







    """simple docstring"""
    a					=collections.OrderedDict()
    with open(lowercase	,   '''r'''	,   encoding='''utf-8'''		) as reader:
        a					=reader.readlines()
    for index, token in enumerate(lowercase		):
        a					=token.rstrip('''\n'''		)
        a					=index
    return vocab






class 				__A    (	_SCREAMING_SNAKE_CASE      ):






 """simple docstring"""




 def __init__(		self			,   __A			,   __A="<unk>"			,   __A=200						) ->					int:
     a					=vocab
     a					=unk_token
     a					=max_input_chars_per_word





 def 				SCREAMING_SNAKE_CASE							(		self			,   __A						) ->					List[Any]:
     a					=list(_SCREAMING_SNAKE_CASE						)
     if len(_SCREAMING_SNAKE_CASE						) > self.max_input_chars_per_word:
         return [self.unk_token]

     a					=0
     a					=[]
     while start < len(_SCREAMING_SNAKE_CASE						):
         a					=len(_SCREAMING_SNAKE_CASE						)
         a					=None
         while start < end:
             a					=''''''.join(chars[start:end]						)
             if substr in self.vocab:
                 a					=substr
                 break
             end -= 1
         if cur_substr is None:
             sub_tokens.append(self.unk_token						)
             start += 1
         else:
             sub_tokens.append(_SCREAMING_SNAKE_CASE						)
             a					=end

     return sub_tokens






class 				__A    (	_SCREAMING_SNAKE_CASE      ):






 """simple docstring"""




 __lowerCAmelCase			 =  VOCAB_FILES_NAMES
 __lowerCAmelCase			 =  PRETRAINED_VOCAB_FILES_MAP
 __lowerCAmelCase			 =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowerCAmelCase			 =  ["input_ids", "attention_mask"]
 __lowerCAmelCase			 =  False


 def __init__(		self			,   __A			,   __A="<d>"			,   __A="</d>"			,   __A="<s>"			,   __A="</s>"			,   __A="<pad>"			,   __A="<unk>"			,   __A="</n>"			,   __A="</_>"			,   __A="left"			,   **__A			,   ) ->					Optional[Any]:
     requires_backends(self			,   ['''jieba''']						)
     super().__init__(
         bod_token=_SCREAMING_SNAKE_CASE			,   eod_token=_SCREAMING_SNAKE_CASE			,   bos_token=_SCREAMING_SNAKE_CASE			,   eos_token=_SCREAMING_SNAKE_CASE			,   pad_token=_SCREAMING_SNAKE_CASE			,   unk_token=_SCREAMING_SNAKE_CASE			,   line_token=_SCREAMING_SNAKE_CASE			,   space_token=_SCREAMING_SNAKE_CASE			,   padding_side=_SCREAMING_SNAKE_CASE			,   **_SCREAMING_SNAKE_CASE			,   )
     a					=bod_token
     a					=eod_token
     a					=load_vocab(_SCREAMING_SNAKE_CASE						)
     a					=self.encoder[space_token]
     a					=self.encoder[line_token]

     del self.encoder[space_token]
     del self.encoder[line_token]

     a					=collections.OrderedDict(sorted(self.encoder.items()			,   key=lambda __A						: x[1]						)						)
     a					={v: k for k, v in self.encoder.items()}

     a					=WordpieceTokenizer(vocab=self.encoder			,   unk_token=self.unk_token						)


 @property
 def 				SCREAMING_SNAKE_CASE							(		self						) ->					Optional[Any]:
     return self.encoder[self.bod_token]


 @property
 def 				SCREAMING_SNAKE_CASE							(		self						) ->					List[str]:
     return self.encoder[self.eod_token]


 @property
 def 				SCREAMING_SNAKE_CASE							(		self						) ->					Any:
     return self.encoder["\n"]


 @property
 def 				SCREAMING_SNAKE_CASE							(		self						) ->					int:
     return len(self.encoder						)


 def 				SCREAMING_SNAKE_CASE							(		self						) ->					Any:
     return dict(self.encoder			,   **self.added_tokens_encoder						)


 def 				SCREAMING_SNAKE_CASE							(		self			,   __A						) ->					Optional[Any]:
     a					=[]
     for x in jieba.cut(_SCREAMING_SNAKE_CASE			,   cut_all=_SCREAMING_SNAKE_CASE						):
         output_tokens.extend(self.wordpiece_tokenizer.tokenize(_SCREAMING_SNAKE_CASE						)						)
     return output_tokens


 def 				SCREAMING_SNAKE_CASE							(		self			,   __A			,   **__A						) ->					str:
     a					=[i for i in token_ids if i >= 0]
     a					=[
         x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
     ]
     return super()._decode(_SCREAMING_SNAKE_CASE			,   **_SCREAMING_SNAKE_CASE						)


 def 				SCREAMING_SNAKE_CASE							(		self			,   __A						) ->					List[str]:
     return token in self.encoder


 def 				SCREAMING_SNAKE_CASE							(		self			,   __A						) ->					str:
     return "".join(_SCREAMING_SNAKE_CASE						)


 def 				SCREAMING_SNAKE_CASE							(		self			,   __A						) ->					Tuple:
     return self.encoder.get(_SCREAMING_SNAKE_CASE			,   self.encoder.get(self.unk_token						)						)


 def 				SCREAMING_SNAKE_CASE							(		self			,   __A						) ->					Dict:
     return self.decoder.get(_SCREAMING_SNAKE_CASE			,   self.unk_token						)


 def 				SCREAMING_SNAKE_CASE							(		self			,   __A			,   __A = None						) ->					Tuple[str]:





     if os.path.isdir(_SCREAMING_SNAKE_CASE						):
         a					=os.path.join(
             _SCREAMING_SNAKE_CASE			,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']						)
     else:
         a					=(filename_prefix + '''-''' if filename_prefix else '''''') + save_directory
     a					=0
     if " " in self.encoder:
         a					=self.encoder[''' ''']
         del self.encoder[" "]
     if "\n" in self.encoder:
         a					=self.encoder['''\n''']
         del self.encoder["\n"]
     a					=collections.OrderedDict(sorted(self.encoder.items()			,   key=lambda __A						: x[1]						)						)
     with open(_SCREAMING_SNAKE_CASE			,   '''w'''			,   encoding='''utf-8'''						) as writer:
         for token, token_index in self.encoder.items():
             if index != token_index:
                 logger.warning(
                     f'''Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive.'''
                     ''' Please check that the vocabulary is not corrupted!'''						)
                 a					=token_index
             writer.write(token + '''\n'''						)
             index += 1
     return (vocab_file,)


 def 				SCREAMING_SNAKE_CASE							(		self			,   __A			,   __A = None						) ->					List[int]:





     if token_ids_a is None:
         return [self.bos_token_id] + token_ids_a
     return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a





 def 				SCREAMING_SNAKE_CASE							(		self			,   __A			,   __A = None			,   __A = False						) ->					List[int]:





     if already_has_special_tokens:
         return super().get_special_tokens_mask(
             token_ids_a=_SCREAMING_SNAKE_CASE			,   token_ids_a=_SCREAMING_SNAKE_CASE			,   already_has_special_tokens=_SCREAMING_SNAKE_CASE						)

     if token_ids_a is not None:
         return [1] + ([0] * len(_SCREAMING_SNAKE_CASE						)) + [1] + ([0] * len(_SCREAMING_SNAKE_CASE						))
     return [1] + ([0] * len(_SCREAMING_SNAKE_CASE						))



"""simple docstring"""







from __future__ import annotations

from typing import Generic, TypeVar

lowerCamelCase_       :       List[Any]      						=  TypeVar("""T""")






class 				__A    (	Generic[T]      ):






 """simple docstring"""




 def __init__(		self			,   __A						) ->					None:
     a					=data
     a					=self
     a					=0






class 				__A    (	Generic[T]      ):






 """simple docstring"""




 def __init__(		self						) ->					None:
     # map from node name to the node object
     a					={}


 def 				SCREAMING_SNAKE_CASE							(		self			,   __A						) ->					None:
     # create a new set with x as its member
     a					=DisjointSetTreeNode(__A						)


 def 				SCREAMING_SNAKE_CASE							(		self			,   __A						) ->					DisjointSetTreeNode[T]:
     # find the set x belongs to (with path-compression)
     a					=self.map[data]
     if elem_ref != elem_ref.parent:
         a					=self.find_set(elem_ref.parent.data						)
     return elem_ref.parent


 def 				SCREAMING_SNAKE_CASE							(		self			,   __A			,   __A						) ->					None:
     # helper function for union operation
     if nodea.rank > nodea.rank:
         a					=nodea
     else:
         a					=nodea
         if nodea.rank == nodea.rank:
             nodea.rank += 1





 def 				SCREAMING_SNAKE_CASE							(		self			,   __A			,   __A						) ->					None:
     # merge 2 disjoint sets
     self.link(self.find_set(__A						)			,   self.find_set(__A						)						)






class 				__A    (	Generic[T]      ):






 """simple docstring"""




 def __init__(		self						) ->					None:
     # connections: map from the node to the neighbouring nodes (with weights)
     a					={}


 def 				SCREAMING_SNAKE_CASE							(		self			,   __A						) ->					None:
     # add a node ONLY if its not present in the graph
     if node not in self.connections:
         a					={}


 def 				SCREAMING_SNAKE_CASE							(		self			,   __A			,   __A			,   __A						) ->					None:
     # add an edge with the given weight
     self.add_node(__A						)
     self.add_node(__A						)
     a					=weight
     a					=weight





 def 				SCREAMING_SNAKE_CASE							(		self						) ->					GraphUndirectedWeighted[T]:
     a					=[]
     a					=set()
     for start in self.connections:
         for end in self.connections[start]:
             if (start, end) not in seen:
                 seen.add((end, start)						)
                 edges.append((start, end, self.connections[start][end])						)
     edges.sort(key=lambda __A						: x[2]						)

     # creating the disjoint set
     a					=DisjointSetTree[T]()
     for node in self.connections:
         disjoint_set.make_set(__A						)

     # MST generation
     a					=0
     a					=0
     a					=GraphUndirectedWeighted[T]()
     while num_edges < len(self.connections						) - 1:
         a		,				a		,				a					=edges[index]
         index += 1
         a					=disjoint_set.find_set(__A						)
         a					=disjoint_set.find_set(__A						)
         if parent_u != parent_v:
             num_edges += 1
             graph.add_edge(__A			,   __A			,   __A						)
             disjoint_set.union(__A			,   __A						)
     return graph