




'''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 		snake_case_							(_a			:							str					,     _a			:							List[Any]					,     _a			:							Dict					,     _a			:							Optional[Any]  ):
    if isinstance(_a					,     _a  ):
        UpperCAmelCase     =	np.full((len(_a  ), sequence_length, 2)					,     _a  )
    else:
        UpperCAmelCase     =	np.full((len(_a  ), sequence_length)					,     _a  )

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

    return out_tensor.tolist()





def 		snake_case_							(_a			:							List[Any]  ):
    UpperCAmelCase     =	ord(_a  )
    if (cp >= 3_3 and cp <= 4_7) or (cp >= 5_8 and cp <= 6_4) or (cp >= 9_1 and cp <= 9_6) or (cp >= 1_2_3 and cp <= 1_2_6):
        return True
    UpperCAmelCase     =	unicodedata.category(_a  )
    if cat.startswith('''P'''  ):
        return True
    return False







@dataclass
class     _a						(			__a				):
       __a       :  PreTrainedTokenizerBase
       __a       :  Union[bool, str, PaddingStrategy]            =      True
       __a       :  Optional[int]            =      None
       __a       :  Optional[int]            =      None
       __a       :  int            =      -100
       __a       :  str            =      "pt"
       def 					A   (			self		:			List[str]     ,       lowercase		:			Dict       ):



           '''simple docstring'''

           import torch

           UpperCAmelCase     =	'''label''' if '''label''' in features[0].keys() else '''labels'''
           UpperCAmelCase     =	[feature[label_name] for feature in features] if label_name in features[0].keys() else None
           UpperCAmelCase     =	self.tokenizer.pad(
               lowercase     ,       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

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

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

           return batch










'''simple docstring'''







from typing import Any


class     _a						:
       def __init__(			self		:			int     ,       lowercase		:			Any       ):



           '''simple docstring'''

           UpperCAmelCase     =	data
           UpperCAmelCase     =	None






class     _a						:
       def __init__(			self		:			int       ):



           '''simple docstring'''

           UpperCAmelCase     =	None
       def 					A   (			self		:			int       ):



           '''simple docstring'''

           UpperCAmelCase     =	self.head
           while temp is not None:
               print(temp.data     ,       end=''' '''       )
               UpperCAmelCase     =	temp.next
           print()
       def 					A   (			self		:			List[str]     ,       lowercase		:			Any       ):



           '''simple docstring'''

           UpperCAmelCase     =	Node(lowercase       )
           UpperCAmelCase     =	self.head
           UpperCAmelCase     =	new_node







       def 					A   (			self		:			List[Any]     ,       lowercase		:			List[Any]     ,       lowercase		:			str       ):



           '''simple docstring'''

           if node_data_a == node_data_a:
               return
           else:
               UpperCAmelCase     =	self.head
               while node_a is not None and node_a.data != node_data_a:
                   UpperCAmelCase     =	node_a.next

               UpperCAmelCase     =	self.head
               while node_a is not None and node_a.data != node_data_a:
                   UpperCAmelCase     =	node_a.next

               if node_a is None or node_a is None:
                   return

               UpperCAmelCase ,  UpperCAmelCase     =	node_a.data, node_a.data


if __name__ == "__main__":
   A									=LinkedList()
   for i in range(5, 0, -1):
      ll.push(i)

   ll.print_list()

   ll.swap_nodes(1, 4)
   print('After swapping')
   ll.print_list()




