

"""simple docstring"""





import unicodedata
from dataclasses import dataclass
from typing import Optional, Union

import numpy as np

from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase




def   _A  (  UpperCamelCase_     :       int,			UpperCamelCase_     :       List[Any],			UpperCamelCase_     :       Any,			UpperCamelCase_     :       List[str])	->						Optional[int]:
   '''simple docstring'''


   if isinstance(UpperCamelCase_,			UpperCamelCase_):
      __lowercase								=						np.full((len(UpperCamelCase_), sequence_length, 2),			UpperCamelCase_)
   else:
      __lowercase								=						np.full((len(UpperCamelCase_), sequence_length),			UpperCamelCase_)

   for i, tensor in enumerate(UpperCamelCase_):
      if padding_side == "right":
         if isinstance(UpperCamelCase_,			UpperCamelCase_):
            __lowercase								=						tensor[:sequence_length]
         else:
            __lowercase								=						tensor[:sequence_length]
      else:
         if isinstance(UpperCamelCase_,			UpperCamelCase_):
            __lowercase								=						tensor[:sequence_length]
         else:
            __lowercase								=						tensor[:sequence_length]

   return out_tensor.tolist()




def   _A  (  UpperCamelCase_     :       Dict)	->						str:
   '''simple docstring'''


   __lowercase								=						ord(UpperCamelCase_)
   if (cp >= 33 and cp <= 47) or (cp >= 58 and cp <= 64) or (cp >= 91 and cp <= 96) or (cp >= 123 and cp <= 126):
      return True
   __lowercase								=						unicodedata.category(UpperCamelCase_)
   if cat.startswith("P"):
      return True
   return False




@dataclass
class 					_lowerCAmelCase  (	lowercase   ):







 """simple docstring"""







 __UpperCAmelCase	:					PreTrainedTokenizerBase
 __UpperCAmelCase	:					Union[bool, str, PaddingStrategy]   		=	True
 __UpperCAmelCase	:					Optional[int]   		=	None
 __UpperCAmelCase	:					Optional[int]   		=	None
 __UpperCAmelCase	:					int   		=	-1_0_0
 __UpperCAmelCase	:					str   		=	"pt"


 def 					_lowercase (			self							:			str,					UpperCAmelCase__							:			List[str]	):
    import torch

    __lowercase								=						"label" if "label" in features[0].keys() else "labels"
    __lowercase								=						[feature[label_name] for feature in features] if label_name in features[0].keys() else None
    __lowercase								=						self.tokenizer.pad(
        UpperCAmelCase__,					padding=self.padding,					max_length=self.max_length,					pad_to_multiple_of=self.pad_to_multiple_of,					return_tensors="pt" if labels is None else None,					)

    if labels is None:
       return batch

    __lowercase								=						torch.tensor(batch["entity_ids"]	).shape[1]
    __lowercase								=						self.tokenizer.padding_side
    if padding_side == "right":
       __lowercase								=						[
           list(UpperCAmelCase__	) + [self.label_pad_token_id] * (sequence_length - len(UpperCAmelCase__	)) for label in labels
       ]
    else:
       __lowercase								=						[
           [self.label_pad_token_id] * (sequence_length - len(UpperCAmelCase__	)) + list(UpperCAmelCase__	) for label in labels
       ]

    __lowercase								=						[feature["ner_tags"] for feature in features]
    __lowercase								=						padding_tensor(UpperCAmelCase__,					-1,					UpperCAmelCase__,					UpperCAmelCase__	)
    __lowercase								=						[feature["original_entity_spans"] for feature in features]
    __lowercase								=						padding_tensor(UpperCAmelCase__,					(-1, -1),					UpperCAmelCase__,					UpperCAmelCase__	)
    __lowercase								=						{k: torch.tensor(UpperCAmelCase__,					dtype=torch.intaa	) for k, v in batch.items()}

    return batch







"""simple docstring"""





from __future__ import annotations

from typing import Any




class 					_lowerCAmelCase  :







 """simple docstring"""







 def __init__(			self							:			Any,					UpperCAmelCase__							:			int	):
    __lowercase								=						num_of_nodes
    __lowercase								=						[]
    __lowercase								=						{}


 def 					_lowercase (			self							:			Optional[Any],					UpperCAmelCase__							:			int,					UpperCAmelCase__							:			int,					UpperCAmelCase__							:			int	):
    self.m_edges.append([u_node, v_node, weight]	)


 def 					_lowercase (			self							:			Union[str, Any],					UpperCAmelCase__							:			int	):

    if self.m_component[u_node] == u_node:
       return u_node
    return self.find_component(self.m_component[u_node]	)


 def 					_lowercase (			self							:			List[Any],					UpperCAmelCase__							:			int	):

    if self.m_component[u_node] != u_node:
       for k in self.m_component:
          __lowercase								=						self.find_component(UpperCAmelCase__	)


 def 					_lowercase (			self							:			Union[str, Any],					UpperCAmelCase__							:			list[int],					UpperCAmelCase__							:			int,					UpperCAmelCase__							:			int	):

    if component_size[u_node] <= component_size[v_node]:
       __lowercase								=						v_node
       component_size[v_node] += component_size[u_node]
       self.set_component(UpperCAmelCase__	)

    elif component_size[u_node] >= component_size[v_node]:
       __lowercase								=						self.find_component(UpperCAmelCase__	)
       component_size[u_node] += component_size[v_node]
       self.set_component(UpperCAmelCase__	)



 def 					_lowercase (			self							:			Any	):
    __lowercase								=						[]
    __lowercase								=						0

    __lowercase								=						[-1] * self.m_num_of_nodes

    # A list of components (initialized to all of the nodes)
    for node in range(self.m_num_of_nodes	):
       self.m_component.update({node: node}	)
       component_size.append(1	)

    __lowercase								=						self.m_num_of_nodes

    while num_of_components > 1:
       for edge in self.m_edges:
          __lowercase		,__lowercase		,__lowercase								=						edge

          __lowercase								=						self.m_component[u]
          __lowercase								=						self.m_component[v]

          if u_component != v_component:

             for component in (u_component, v_component):
                if (
                    minimum_weight_edge[component] == -1
                    or minimum_weight_edge[component][2] > w
                ):
                   __lowercase								=						[u, v, w]

       for edge in minimum_weight_edge:
          if isinstance(UpperCAmelCase__,					UpperCAmelCase__	):
             __lowercase		,__lowercase		,__lowercase								=						edge

             __lowercase								=						self.m_component[u]
             __lowercase								=						self.m_component[v]

             if u_component != v_component:
                mst_weight += w
                self.union(UpperCAmelCase__,					UpperCAmelCase__,					UpperCAmelCase__	)
                print(F"""Added edge [{u} - {v}]\nAdded weight: {w}\n"""	)
                num_of_components -= 1

       __lowercase								=						[-1] * self.m_num_of_nodes
    print(F"""The total weight of the minimal spanning tree is: {mst_weight}"""	)







def   _A  (  )	->						None:
   '''simple docstring'''




if __name__ == "__main__":
   import doctest

   doctest.testmod()




