





import os
from typing import List, Union

import tensorflow as tf
from tensorflow_text import BertTokenizer as BertTokenizerLayer
from tensorflow_text import FastBertTokenizer, ShrinkLongestTrimmer, case_fold_utfa, combine_segments, pad_model_inputs

from .tokenization_bert import BertTokenizer
class SCREAMING_SNAKE_CASE_    (       tf.keras.layers.Layer       ):






						def __init__(   self   :   List[Any]		, _A   :   List		, _A   :   bool		, _A   :   int = None		, _A   :   int = None		, _A   :   int = None		, _A   :   str = "longest"		, _A   :   bool = True		, _A   :   int = 512		, _A   :   int = None		, _A   :   bool = True		, _A   :   bool = True		, _A   :   bool = True		, **_A   :   Any		, )				->     Tuple:







							"""simple docstring"""


							super().__init__()
							if use_fast_bert_tokenizer:
								snake_case_		:      Any           =						FastBertTokenizer(
								    _A		, token_out_type=tf.intaa		, lower_case_nfd_strip_accents=_A		, **_A						)
							else:
								snake_case_		:      int           =						tf.lookup.StaticVocabularyTable(
								    tf.lookup.KeyValueTensorInitializer(
								        keys=_A		, key_dtype=tf.string		, values=tf.range(tf.size(_A		, out_type=tf.intaa						)		, dtype=tf.intaa						)		, value_dtype=tf.intaa		, )		, num_oov_buckets=1		, )
								snake_case_		:      Any           =						BertTokenizerLayer(
								    _A		, token_out_type=tf.intaa		, lower_case=_A		, **_A						)

							snake_case_		:      Optional[int]           =						vocab_list
							snake_case_		:      int           =						do_lower_case
							snake_case_		:      Optional[Any]           =						cls_token_id or vocab_list.index('[CLS]'						)
							snake_case_		:      Any           =						sep_token_id or vocab_list.index('[SEP]'						)
							snake_case_		:      Union[str, Any]           =						pad_token_id or vocab_list.index('[PAD]'						)
							snake_case_		:      List[Any]           =						ShrinkLongestTrimmer(max_length - 3		, axis=1						)  # Allow room for special tokens
							snake_case_		:      Tuple           =						max_length
							snake_case_		:      Optional[int]           =						padding
							snake_case_		:      List[Any]           =						truncation
							snake_case_		:      int           =						pad_to_multiple_of
							snake_case_		:      Optional[int]           =						return_token_type_ids
							snake_case_		:      str           =						return_attention_mask






						@classmethod
						def UpperCAmelCase_					(   cls   :   Any		, _A   :   "PreTrainedTokenizerBase"		, **_A   :   str						)				->     List[str]:  # noqa: F821







							"""simple docstring"""


							snake_case_		:      Union[str, Any]           =						kwargs.pop('do_lower_case'		, _A						)
							snake_case_		:      Tuple           =						tokenizer.do_lower_case if do_lower_case is None else do_lower_case
							snake_case_		:      List[str]           =						kwargs.pop('cls_token_id'		, _A						)
							snake_case_		:      Any           =						tokenizer.cls_token_id if cls_token_id is None else cls_token_id
							snake_case_		:      Tuple           =						kwargs.pop('sep_token_id'		, _A						)
							snake_case_		:      Tuple           =						tokenizer.sep_token_id if sep_token_id is None else sep_token_id
							snake_case_		:      List[str]           =						kwargs.pop('pad_token_id'		, _A						)
							snake_case_		:      List[str]           =						tokenizer.pad_token_id if pad_token_id is None else pad_token_id

							snake_case_		:      Union[str, Any]           =						tokenizer.get_vocab()
							snake_case_		:      Optional[int]           =						sorted([(wordpiece, idx) for wordpiece, idx in vocab.items()]		, key=lambda _A						: x[1]						)
							snake_case_		:      Optional[int]           =						[entry[0] for entry in vocab]
							return cls(
							    vocab_list=_A		, do_lower_case=_A		, cls_token_id=_A		, sep_token_id=_A		, pad_token_id=_A		, **_A		, )






						@classmethod
						def UpperCAmelCase_					(   cls   :   Union[str, Any]		, _A   :   Union[str, os.PathLike]		, *_A   :   int		, **_A   :   List[str]						)				->     Tuple:







							"""simple docstring"""


							try:
								snake_case_		:      Any           =						BertTokenizer.from_pretrained(_A		, *_A		, **_A						)
							except:  # noqa: E722
								from .tokenization_bert_fast import BertTokenizerFast

								snake_case_		:      int           =						BertTokenizerFast.from_pretrained(_A		, *_A		, **_A						)
							return cls.from_tokenizer(_A		, **_A						)






						def UpperCAmelCase_					(   self   :   List[str]		, _A   :   List[str]						)				->     str:







							"""simple docstring"""


							if self.do_lower_case:
								snake_case_		:      Optional[int]           =						case_fold_utfa(_A						)
							snake_case_		:      Tuple           =						self.tf_tokenizer.tokenize(_A						)
							return tokens.merge_dims(1		, -1						)






						def UpperCAmelCase_					(   self   :   Optional[int]		, _A   :   Optional[int]		, _A   :   Optional[Any]=None		, _A   :   Optional[Any]=None		, _A   :   List[str]=None		, _A   :   List[Any]=None		, _A   :   Any=None		, _A   :   Optional[int]=None		, _A   :   int=None		, )				->     Optional[int]:







							"""simple docstring"""


							if padding is None:
								snake_case_		:      Union[str, Any]           =						self.padding
							if padding not in ("longest", "max_length"):
								raise ValueError('Padding must be either \'longest\' or \'max_length\'!'						)
							if max_length is not None and text_pair is not None:
								# Because we have to instantiate a Trimmer to do it properly
								raise ValueError('max_length cannot be overridden at call time when truncating paired texts!'						)
							if max_length is None:
								snake_case_		:      Optional[Any]           =						self.max_length
							if truncation is None:
								snake_case_		:      str           =						self.truncation
							if pad_to_multiple_of is None:
								snake_case_		:      Tuple           =						self.pad_to_multiple_of
							if return_token_type_ids is None:
								snake_case_		:      List[Any]           =						self.return_token_type_ids
							if return_attention_mask is None:
								snake_case_		:      Dict           =						self.return_attention_mask
							if not isinstance(_A		, tf.Tensor						):
								snake_case_		:      Optional[Any]           =						tf.convert_to_tensor(_A						)
							if text_pair is not None and not isinstance(_A		, tf.Tensor						):
								snake_case_		:      List[Any]           =						tf.convert_to_tensor(_A						)
							if text_pair is not None:
								if text.shape.rank > 1:
									raise ValueError('text argument should not be multidimensional when a text pair is supplied!'						)
								if text_pair.shape.rank > 1:
									raise ValueError('text_pair should not be multidimensional!'						)
							if text.shape.rank == 2:
								snake_case_    ,snake_case_		:      Dict           =						text[:, 0], text[:, 1]
							snake_case_		:      str           =						self.unpaired_tokenize(_A						)
							if text_pair is None:  # Unpaired text
								if truncation:
									snake_case_		:      List[str]           =						text[:, : max_length - 2]  # Allow room for special tokens
								snake_case_    ,snake_case_		:      Dict           =						combine_segments(
								    (text,)		, start_of_sequence_id=self.cls_token_id		, end_of_segment_id=self.sep_token_id						)
							else:  # Paired text
								snake_case_		:      Tuple           =						self.unpaired_tokenize(_A						)
								if truncation:
									snake_case_    ,snake_case_		:      List[Any]           =						self.paired_trimmer.trim([text, text_pair]						)
								snake_case_    ,snake_case_		:      Optional[Any]           =						combine_segments(
								    (text, text_pair)		, start_of_sequence_id=self.cls_token_id		, end_of_segment_id=self.sep_token_id						)
							if padding == "longest":
								snake_case_		:      List[Any]           =						input_ids.bounding_shape(axis=1						)
								if pad_to_multiple_of is not None:
									# No ceiling division in tensorflow, so we negate floordiv instead
									snake_case_		:      Any           =						pad_to_multiple_of * (-tf.math.floordiv(-pad_length		, _A						))
							else:
								snake_case_		:      Optional[Any]           =						max_length

							snake_case_    ,snake_case_		:      Tuple           =						pad_model_inputs(_A		, max_seq_length=_A		, pad_value=self.pad_token_id						)
							snake_case_		:      str           =						{'input_ids': input_ids}
							if return_attention_mask:
								snake_case_		:      Any           =						attention_mask
							if return_token_type_ids:
								snake_case_    ,snake_case_		:      Dict           =						pad_model_inputs(
								    _A		, max_seq_length=_A		, pad_value=self.pad_token_id						)
								snake_case_		:      Union[str, Any]           =						token_type_ids
							return output






						def UpperCAmelCase_					(   self   :   Any						)				->     Any:







							"""simple docstring"""


							return {
							    "vocab_list": self.vocab_list,
							    "do_lower_case": self.do_lower_case,
							    "cls_token_id": self.cls_token_id,
							    "sep_token_id": self.sep_token_id,
							    "pad_token_id": self.pad_token_id,
							}



"""simple docstring"""





class A_      :




  '''simple docstring'''







  def __init__(						self							,  lowercase_    ):

     """simple docstring"""
     UpperCAmelCase_   :   str     	=       data
     UpperCAmelCase_   :   str     	=       None
     UpperCAmelCase_   :   List[Any]     	=       None







  def __str__(						self    ):

     """simple docstring"""
     return F"""{self.data}"""




class A_      :




  '''simple docstring'''







  def __init__(						self    ):

     """simple docstring"""
     UpperCAmelCase_   :   Tuple     	=       None
     UpperCAmelCase_   :   List[str]     	=       None







  def __iter__(						self    ):

     """simple docstring"""
     UpperCAmelCase_   :   Optional[int]     	=       self.head
     while node:
        yield node.data
        UpperCAmelCase_   :   Optional[Any]     	=       node.next







  def __str__(						self    ):

     """simple docstring"""
     return "->".join([str(lowercase_    ) for item in self]    )







  def __len__(						self    ):

     """simple docstring"""
     return sum(1 for _ in self    )







  def 			UpperCamelCase__   (						self							,  lowercase_    ):

     """simple docstring"""
     self.insert_at_nth(0							,  lowercase_    )







  def 			UpperCamelCase__   (						self							,  lowercase_    ):

     """simple docstring"""
     self.insert_at_nth(len(self    )							,  lowercase_    )







  def 			UpperCamelCase__   (						self							,  lowercase_							,  lowercase_    ):

     """simple docstring"""
     UpperCAmelCase_   :   int     	=       len(self    )

     if not 0 <= index <= length:
        raise IndexError("list index out of range"    )
     UpperCAmelCase_   :   Tuple     	=       Node(lowercase_    )
     if self.head is None:
        UpperCAmelCase_   :   List[str]     	=       new_node
     elif index == 0:
        UpperCAmelCase_   :   int     	=       new_node
        UpperCAmelCase_   :   Optional[Any]     	=       self.head
        UpperCAmelCase_   :   Optional[int]     	=       new_node
     elif index == length:
        UpperCAmelCase_   :   Union[str, Any]     	=       new_node
        UpperCAmelCase_   :   Optional[Any]     	=       self.tail
        UpperCAmelCase_   :   Tuple     	=       new_node
     else:
        UpperCAmelCase_   :   Dict     	=       self.head
        for _ in range(0							,  lowercase_    ):
           UpperCAmelCase_   :   str     	=       temp.next
        UpperCAmelCase_   :   int     	=       new_node
        UpperCAmelCase_   :   Tuple     	=       temp.previous
        UpperCAmelCase_   :   Union[str, Any]     	=       temp
        UpperCAmelCase_   :   int     	=       new_node







  def 			UpperCamelCase__   (						self    ):

     """simple docstring"""
     return self.delete_at_nth(0    )







  def 			UpperCamelCase__   (						self    ):

     """simple docstring"""
     return self.delete_at_nth(len(self    ) - 1    )







  def 			UpperCamelCase__   (						self							,  lowercase_    ):

     """simple docstring"""
     UpperCAmelCase_   :   int     	=       len(self    )

     if not 0 <= index <= length - 1:
        raise IndexError("list index out of range"    )
     UpperCAmelCase_   :   Optional[int]     	=       self.head  # default first node
     if length == 1:
        UpperCAmelCase_   :   Union[str, Any]     	=       None
     elif index == 0:
        UpperCAmelCase_   :   List[Any]     	=       self.head.next
        UpperCAmelCase_   :   str     	=       None
     elif index == length - 1:
        UpperCAmelCase_   :   str     	=       self.tail
        UpperCAmelCase_   :   Optional[Any]     	=       self.tail.previous
        UpperCAmelCase_   :   Any     	=       None
     else:
        UpperCAmelCase_   :   List[Any]     	=       self.head
        for _ in range(0							,  lowercase_    ):
           UpperCAmelCase_   :   str     	=       temp.next
        UpperCAmelCase_   :   Dict     	=       temp
        UpperCAmelCase_   :   Optional[Any]     	=       temp.previous
        UpperCAmelCase_   :   int     	=       temp.next
     return delete_node.data







  def 			UpperCamelCase__   (						self							,  lowercase_    ):

     """simple docstring"""
     UpperCAmelCase_   :   Tuple     	=       self.head

     while current.data != data:  # Find the position to delete
        if current.next:
           UpperCAmelCase_   :   List[str]     	=       current.next
        else:  # We have reached the end an no value matches
           raise ValueError("No data matching given value"    )

     if current == self.head:
        self.delete_head()

     elif current == self.tail:
        self.delete_tail()

     else:  # Before: 1 <--> 2(current) <--> 3
        UpperCAmelCase_   :   str     	=       current.next  # 1 --> 3
        UpperCAmelCase_   :   Optional[Any]     	=       current.previous  # 1 <--> 3
     return data







  def 			UpperCamelCase__   (						self    ):

     """simple docstring"""
     return len(self    ) == 0







def       __a	(						):
   UpperCAmelCase_   :   Dict     	=       DoublyLinkedList()
   assert linked_list.is_empty() is True
   assert str(__lowerCamelCase    ) == ""

   try:
      linked_list.delete_head()
      raise AssertionError  # This should not happen.
   except IndexError:
      assert True  # This should happen.

   try:
      linked_list.delete_tail()
      raise AssertionError  # This should not happen.
   except IndexError:
      assert True  # This should happen.

   for i in range(10    ):
      assert len(__lowerCamelCase    ) == i
      linked_list.insert_at_nth(__lowerCamelCase,						i + 1    )
   assert str(__lowerCamelCase    ) == "->".join(str(__lowerCamelCase    ) for i in range(1,						11    )    )

   linked_list.insert_at_head(0    )
   linked_list.insert_at_tail(11    )
   assert str(__lowerCamelCase    ) == "->".join(str(__lowerCamelCase    ) for i in range(0,						12    )    )

   assert linked_list.delete_head() == 0
   assert linked_list.delete_at_nth(9    ) == 10
   assert linked_list.delete_tail() == 11
   assert len(__lowerCamelCase    ) == 9
   assert str(__lowerCamelCase    ) == "->".join(str(__lowerCamelCase    ) for i in range(1,						10    )    )


if __name__ == "__main__":
    from doctest import testmod

    testmod()


