


'''simple docstring'''



class       a							:


     """simple docstring"""






     def __init__(							self	:						Optional[Any]				,					snake_case	:						str     )		->				Tuple:
          __UpperCAmelCase      :					List[Any]    				=     val
          # Number of nodes in left subtree
          __UpperCAmelCase      :					Optional[int]    				=     0
          __UpperCAmelCase      :					Any    				=     None
          __UpperCAmelCase      :					Any    				=     None
          __UpperCAmelCase      :					Tuple    				=     None






     def 					lowerCamelCase__					(							self	:						Dict				,					snake_case	:						str     )		->				int:
          assert self.left_tree_size == other.left_tree_size, "Unequal Sizes of Blocks"

          if self.val < other.val:
               __UpperCAmelCase      :					Optional[int]    				=     self.right
               __UpperCAmelCase      :					Dict    				=     None
               if self.right:
                    __UpperCAmelCase      :					Optional[Any]    				=     other
               __UpperCAmelCase      :					int    				=     other
               __UpperCAmelCase      :					List[str]    				=     self.left_tree_size * 2 + 1
               return self
          else:
               __UpperCAmelCase      :					List[str]    				=     other.right
               __UpperCAmelCase      :					Tuple    				=     None
               if other.right:
                    __UpperCAmelCase      :					Dict    				=     self
               __UpperCAmelCase      :					int    				=     self
               __UpperCAmelCase      :					List[Any]    				=     other.left_tree_size * 2 + 1
               return other



class       a							:


     """simple docstring"""






     def __init__(							self	:						Any				,					snake_case	:						int=None				,					snake_case	:						str=None				,					snake_case	:						Dict=0     )		->				List[Any]:
          __UpperCAmelCase      :					str    				=     heap_size
          __UpperCAmelCase      :					List[Any]    				=     bottom_root
          __UpperCAmelCase      :					str    				=     min_node

     def 					lowerCamelCase__					(							self	:						Any				,					snake_case	:						Any     )		->				Tuple:


          if other.size == 0:
               return None
          if self.size == 0:
               __UpperCAmelCase      :					Any    				=     other.size
               __UpperCAmelCase      :					Optional[Any]    				=     other.bottom_root
               __UpperCAmelCase      :					Optional[Any]    				=     other.min_node
               return None
          # Update size
          __UpperCAmelCase      :					Optional[Any]    				=     self.size + other.size

          # Update min.node
          if self.min_node.val > other.min_node.val:
               __UpperCAmelCase      :					Optional[int]    				=     other.min_node
          # Merge

          # Order roots by left_subtree_size
          __UpperCAmelCase      :					Optional[int]    				=     []
          __UpperCAmelCase				,  __UpperCAmelCase      :					Dict    				=     self.bottom_root, other.bottom_root
          while i or j:
               if i and ((not j) or i.left_tree_size < j.left_tree_size):
                    combined_roots_list.append((i, True)     )
                    __UpperCAmelCase      :					Dict    				=     i.parent
               else:
                    combined_roots_list.append((j, False)     )
                    __UpperCAmelCase      :					Optional[int]    				=     j.parent
        # Insert links between them
          for i in range(len(_snake_case     ) - 1     ):
               if combined_roots_list[i][1] != combined_roots_list[i + 1][1]:
                    __UpperCAmelCase      :					List[str]    				=     combined_roots_list[i + 1][0]
                    __UpperCAmelCase      :					Union[str, Any]    				=     combined_roots_list[i][0]
        # Consecutively merge roots with same left_tree_size
          __UpperCAmelCase      :					str    				=     combined_roots_list[0][0]
          while i.parent:
               if (
                   (i.left_tree_size == i.parent.left_tree_size) and (not i.parent.parent)
               ) or (
                   i.left_tree_size == i.parent.left_tree_size
                   and i.left_tree_size != i.parent.parent.left_tree_size
               ):
                    # Neighbouring Nodes
                    __UpperCAmelCase      :					Tuple    				=     i.left
                    __UpperCAmelCase      :					List[Any]    				=     i.parent.parent

                    # Merging trees
                    __UpperCAmelCase      :					Tuple    				=     i.merge_trees(i.parent     )

                    # Updating links
                    __UpperCAmelCase      :					Any    				=     previous_node
                    __UpperCAmelCase      :					List[str]    				=     next_node
                    if previous_node:
                         __UpperCAmelCase      :					List[Any]    				=     i
                    if next_node:
                         __UpperCAmelCase      :					Optional[int]    				=     i
               else:
                    __UpperCAmelCase      :					Any    				=     i.parent
        # Updating self.bottom_root
          while i.left:
               __UpperCAmelCase      :					Any    				=     i.left
          __UpperCAmelCase      :					int    				=     i

          # Update other
          __UpperCAmelCase      :					Dict    				=     self.size
          __UpperCAmelCase      :					Tuple    				=     self.bottom_root
          __UpperCAmelCase      :					Dict    				=     self.min_node

          # Return the merged heap
          return self

     def 					lowerCamelCase__					(							self	:						List[Any]				,					snake_case	:						int     )		->				Dict:


          if self.size == 0:
               __UpperCAmelCase      :					Dict    				=     Node(_snake_case     )
               __UpperCAmelCase      :					Union[str, Any]    				=     1
               __UpperCAmelCase      :					Tuple    				=     self.bottom_root
          else:
               # Create new node
               __UpperCAmelCase      :					List[str]    				=     Node(_snake_case     )

               # Update size
               self.size += 1

               # update min_node
               if val < self.min_node.val:
                    __UpperCAmelCase      :					List[Any]    				=     new_node
               # Put new_node as a bottom_root in heap
               __UpperCAmelCase      :					Optional[int]    				=     new_node
               __UpperCAmelCase      :					str    				=     self.bottom_root
               __UpperCAmelCase      :					Optional[int]    				=     new_node

               # Consecutively merge roots with same left_tree_size
               while (
                   self.bottom_root.parent
                   and self.bottom_root.left_tree_size
                   == self.bottom_root.parent.left_tree_size
               ):
                    # Next node
                    __UpperCAmelCase      :					str    				=     self.bottom_root.parent.parent

                    # Merge
                    __UpperCAmelCase      :					Tuple    				=     self.bottom_root.merge_trees(self.bottom_root.parent     )

                    # Update Links
                    __UpperCAmelCase      :					Optional[Any]    				=     next_node
                    __UpperCAmelCase      :					Tuple    				=     None
                    if next_node:
                         __UpperCAmelCase      :					int    				=     self.bottom_root

     def 					lowerCamelCase__					(							self	:						Tuple     )		->				Tuple:
          return self.min_node.val

     def 					lowerCamelCase__					(							self	:						List[Any]     )		->				Tuple:
          return self.size == 0

     def 					lowerCamelCase__					(							self	:						Tuple     )		->				List[str]:
          __UpperCAmelCase      :					str    				=     self.min_node.val

          # Last element in heap corner case
          if self.size == 1:
               # Update size
               __UpperCAmelCase      :					Any    				=     0

               # Update bottom root
               __UpperCAmelCase      :					Optional[Any]    				=     None

               # Update min_node
               __UpperCAmelCase      :					List[Any]    				=     None

               return min_value
          # No right subtree corner case
          # The structure of the tree implies that this should be the bottom root
          # and there is at least one other root
          if self.min_node.right is None:
               # Update size
               self.size -= 1

               # Update bottom root
               __UpperCAmelCase      :					Dict    				=     self.bottom_root.parent
               __UpperCAmelCase      :					Tuple    				=     None

               # Update min_node
               __UpperCAmelCase      :					Optional[int]    				=     self.bottom_root
               __UpperCAmelCase      :					Optional[int]    				=     self.bottom_root.parent
               while i:
                    if i.val < self.min_node.val:
                         __UpperCAmelCase      :					int    				=     i
                    __UpperCAmelCase      :					Dict    				=     i.parent
               return min_value
          # General case
          # Find the BinomialHeap of the right subtree of min_node
          __UpperCAmelCase      :					Optional[int]    				=     self.min_node.right
          __UpperCAmelCase      :					Any    				=     None
          __UpperCAmelCase      :					Optional[Any]    				=     bottom_of_new
          __UpperCAmelCase      :					Tuple    				=     1

          # Size, min_node and bottom_root
          while bottom_of_new.left:
               __UpperCAmelCase      :					Optional[int]    				=     size_of_new * 2 + 1
               __UpperCAmelCase      :					Any    				=     bottom_of_new.left
               if bottom_of_new.val < min_of_new.val:
                    __UpperCAmelCase      :					Optional[Any]    				=     bottom_of_new
        # Corner case of single root on top left path
          if (not self.min_node.left) and (not self.min_node.parent):
               __UpperCAmelCase      :					Tuple    				=     size_of_new
               __UpperCAmelCase      :					List[Any]    				=     bottom_of_new
               __UpperCAmelCase      :					Tuple    				=     min_of_new
               # print("Single root, multiple nodes case")
               return min_value
          # Remaining cases
          # Construct heap of right subtree
          __UpperCAmelCase      :					List[str]    				=     BinomialHeap(
              bottom_root=_snake_case				,					min_node=_snake_case				,					heap_size=_snake_case     )

          # Update size
          __UpperCAmelCase      :					Optional[Any]    				=     self.size - 1 - size_of_new

          # Neighbour nodes
          __UpperCAmelCase      :					Dict    				=     self.min_node.left
          __UpperCAmelCase      :					str    				=     self.min_node.parent

          # Initialize new bottom_root and min_node
          __UpperCAmelCase      :					Optional[Any]    				=     previous_node or next_node
          __UpperCAmelCase      :					int    				=     next_node

          # Update links of previous_node and search below for new min_node and
          # bottom_root
          if previous_node:
               __UpperCAmelCase      :					int    				=     next_node

               # Update bottom_root and search for min_node below
               __UpperCAmelCase      :					str    				=     previous_node
               __UpperCAmelCase      :					Optional[int]    				=     previous_node
               while self.bottom_root.left:
                    __UpperCAmelCase      :					Tuple    				=     self.bottom_root.left
                    if self.bottom_root.val < self.min_node.val:
                         __UpperCAmelCase      :					Any    				=     self.bottom_root
          if next_node:
               __UpperCAmelCase      :					Any    				=     previous_node

               # Search for new min_node above min_node
               __UpperCAmelCase      :					Dict    				=     next_node
               while i:
                    if i.val < self.min_node.val:
                         __UpperCAmelCase      :					Tuple    				=     i
                    __UpperCAmelCase      :					Tuple    				=     i.parent
        # Merge heaps
          self.merge_heaps(_snake_case     )

          return min_value

     def 					lowerCamelCase__					(							self	:						str     )		->				Dict:
          __UpperCAmelCase      :					Dict    				=     self.bottom_root
          while top_root.parent:
               __UpperCAmelCase      :					Any    				=     top_root.parent
          # preorder
          __UpperCAmelCase      :					Any    				=     []
          self.__traversal(_snake_case				,					_snake_case     )
          return heap_pre_order

     def 					lowerCamelCase__					(							self	:						List[Any]				,					snake_case	:						List[str]				,					snake_case	:						Optional[Any]				,					snake_case	:						List[Any]=0     )		->				Optional[Any]:


          if curr_node:
               preorder.append((curr_node.val, level)     )
               self.__traversal(curr_node.left				,					_snake_case				,					level + 1     )
               self.__traversal(curr_node.right				,					_snake_case				,					level + 1     )
          else:
               preorder.append(('''#''', level)     )






     def __str__(							self	:						Tuple     )		->				int:


          if self.is_empty():
               return ""
          __UpperCAmelCase      :					Dict    				=     self.pre_order()

          return "\n".join(('''-''' * level + str(_snake_case     )) for value, level in preorder_heap     )


# Unit Tests
if __name__ == "__main__":
      import doctest

      doctest.testmod()





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 __snake_case     (     tf.keras.layers.Layer						):







   def __init__( self						:		Optional[int]   ,		_snake_case						:		List   ,		_snake_case						:		bool   ,		_snake_case						:		int = None   ,		_snake_case						:		int = None   ,		_snake_case						:		int = None   ,		_snake_case						:		str = "longest"   ,		_snake_case						:		bool = True   ,		_snake_case						:		int = 512   ,		_snake_case						:		int = None   ,		_snake_case						:		bool = True   ,		_snake_case						:		bool = True   ,		_snake_case						:		bool = True   ,		**_snake_case						:		Any   ,		):

        """simple docstring"""


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

        UpperCAmelCase_		=				vocab_list
        UpperCAmelCase_		=				do_lower_case
        UpperCAmelCase_		=				cls_token_id or vocab_list.index('''[CLS]''')
        UpperCAmelCase_		=				sep_token_id or vocab_list.index('''[SEP]''')
        UpperCAmelCase_		=				pad_token_id or vocab_list.index('''[PAD]''')
        UpperCAmelCase_		=				ShrinkLongestTrimmer(max_length - 3   ,		axis=1)  # Allow room for special tokens
        UpperCAmelCase_		=				max_length
        UpperCAmelCase_		=				padding
        UpperCAmelCase_		=				truncation
        UpperCAmelCase_		=				pad_to_multiple_of
        UpperCAmelCase_		=				return_token_type_ids
        UpperCAmelCase_		=				return_attention_mask







   @classmethod
   def lowerCamelCase		( cls						:		Optional[Any]   ,		_snake_case						:		"PreTrainedTokenizerBase"   ,		**_snake_case						:		str):  # noqa: F821

        """simple docstring"""


        UpperCAmelCase_		=				kwargs.pop('''do_lower_case'''   ,		_snake_case)
        UpperCAmelCase_		=				tokenizer.do_lower_case if do_lower_case is None else do_lower_case
        UpperCAmelCase_		=				kwargs.pop('''cls_token_id'''   ,		_snake_case)
        UpperCAmelCase_		=				tokenizer.cls_token_id if cls_token_id is None else cls_token_id
        UpperCAmelCase_		=				kwargs.pop('''sep_token_id'''   ,		_snake_case)
        UpperCAmelCase_		=				tokenizer.sep_token_id if sep_token_id is None else sep_token_id
        UpperCAmelCase_		=				kwargs.pop('''pad_token_id'''   ,		_snake_case)
        UpperCAmelCase_		=				tokenizer.pad_token_id if pad_token_id is None else pad_token_id

        UpperCAmelCase_		=				tokenizer.get_vocab()
        UpperCAmelCase_		=				sorted([(wordpiece, idx) for wordpiece, idx in vocab.items()]   ,		key=lambda _snake_case: x[1])
        UpperCAmelCase_		=				[entry[0] for entry in vocab]
        return cls(
            vocab_list=_snake_case   ,		do_lower_case=_snake_case   ,		cls_token_id=_snake_case   ,		sep_token_id=_snake_case   ,		pad_token_id=_snake_case   ,		**_snake_case   ,		)







   @classmethod
   def lowerCamelCase		( cls						:		List[str]   ,		_snake_case						:		Union[str, os.PathLike]   ,		*_snake_case						:		Union[str, Any]   ,		**_snake_case						:		Union[str, Any]):

        """simple docstring"""


        try:
             UpperCAmelCase_		=				BertTokenizer.from_pretrained(_snake_case   ,		*_snake_case   ,		**_snake_case)
        except:  # noqa: E722
             from .tokenization_bert_fast import BertTokenizerFast

             UpperCAmelCase_		=				BertTokenizerFast.from_pretrained(_snake_case   ,		*_snake_case   ,		**_snake_case)
        return cls.from_tokenizer(_snake_case   ,		**_snake_case)







   def lowerCamelCase		( self						:		int   ,		_snake_case						:		str):

        """simple docstring"""


        if self.do_lower_case:
             UpperCAmelCase_		=				case_fold_utfa(_snake_case)
        UpperCAmelCase_		=				self.tf_tokenizer.tokenize(_snake_case)
        return tokens.merge_dims(1   ,		-1)







   def lowerCamelCase		( self						:		int   ,		_snake_case						:		str   ,		_snake_case						:		str=None   ,		_snake_case						:		Union[str, Any]=None   ,		_snake_case						:		str=None   ,		_snake_case						:		int=None   ,		_snake_case						:		Optional[int]=None   ,		_snake_case						:		Optional[Any]=None   ,		_snake_case						:		List[str]=None   ,		):

        """simple docstring"""


        if padding is None:
             UpperCAmelCase_		=				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:
             UpperCAmelCase_		=				self.max_length
        if truncation is None:
             UpperCAmelCase_		=				self.truncation
        if pad_to_multiple_of is None:
             UpperCAmelCase_		=				self.pad_to_multiple_of
        if return_token_type_ids is None:
             UpperCAmelCase_		=				self.return_token_type_ids
        if return_attention_mask is None:
             UpperCAmelCase_		=				self.return_attention_mask
        if not isinstance(_snake_case   ,		tf.Tensor):
             UpperCAmelCase_		=				tf.convert_to_tensor(_snake_case)
        if text_pair is not None and not isinstance(_snake_case   ,		tf.Tensor):
             UpperCAmelCase_		=				tf.convert_to_tensor(_snake_case)
        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:
             UpperCAmelCase_	,			UpperCAmelCase_		=				text[:, 0], text[:, 1]
        UpperCAmelCase_		=				self.unpaired_tokenize(_snake_case)
        if text_pair is None:  # Unpaired text
             if truncation:
                  UpperCAmelCase_		=				text[:, : max_length - 2]  # Allow room for special tokens
             UpperCAmelCase_	,			UpperCAmelCase_		=				combine_segments(
                 (text,)   ,		start_of_sequence_id=self.cls_token_id   ,		end_of_segment_id=self.sep_token_id)
        else:  # Paired text
             UpperCAmelCase_		=				self.unpaired_tokenize(_snake_case)
             if truncation:
                  UpperCAmelCase_	,			UpperCAmelCase_		=				self.paired_trimmer.trim([text, text_pair])
             UpperCAmelCase_	,			UpperCAmelCase_		=				combine_segments(
                 (text, text_pair)   ,		start_of_sequence_id=self.cls_token_id   ,		end_of_segment_id=self.sep_token_id)
        if padding == "longest":
             UpperCAmelCase_		=				input_ids.bounding_shape(axis=1)
             if pad_to_multiple_of is not None:
                  # No ceiling division in tensorflow, so we negate floordiv instead
                  UpperCAmelCase_		=				pad_to_multiple_of * (-tf.math.floordiv(-pad_length   ,		_snake_case))
        else:
             UpperCAmelCase_		=				max_length

        UpperCAmelCase_	,			UpperCAmelCase_		=				pad_model_inputs(_snake_case   ,		max_seq_length=_snake_case   ,		pad_value=self.pad_token_id)
        UpperCAmelCase_		=				{'''input_ids''': input_ids}
        if return_attention_mask:
             UpperCAmelCase_		=				attention_mask
        if return_token_type_ids:
             UpperCAmelCase_	,			UpperCAmelCase_		=				pad_model_inputs(
                 _snake_case   ,		max_seq_length=_snake_case   ,		pad_value=self.pad_token_id)
             UpperCAmelCase_		=				token_type_ids
        return output







   def lowerCamelCase		( self						:		Optional[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,
        }






