


'''simple docstring'''







from collections.abc import Iterable
from typing import Any


class  lowerCAmelCase_						:





  """simple docstring"""



  def __init__(					self     :							List[str]				,							SCREAMING_SNAKE_CASE__     :							int | None = None						):





       '''simple docstring'''

       __a       =   value
       __a       =   None  # Added in order to delete a node easier
       __a       =   None
       __a       =   None


  def __repr__(					self     :							int						):





       '''simple docstring'''

       from pprint import pformat

       if self.left is None and self.right is None:
            return str(self.value						)
       return pformat({f'''{self.value}''': (self.left, self.right)}				,							indent=1						)


class  lowerCAmelCase_						:





  """simple docstring"""



  def __init__(					self     :							Any				,							SCREAMING_SNAKE_CASE__     :							Node | None = None						):





       '''simple docstring'''

       __a       =   root

  def __str__(					self     :							Union[str, Any]						):





       '''simple docstring'''

       return str(self.root						)

  def __a						(					self     :							List[str]				,							SCREAMING_SNAKE_CASE__     :							Node				,							SCREAMING_SNAKE_CASE__     :							Node | None						):





       '''simple docstring'''

       if new_children is not None:  # reset its kids
            __a       =   node.parent
       if node.parent is not None:  # reset its parent
            if self.is_right(SCREAMING_SNAKE_CASE__						):  # If it is the right children
                 __a       =   new_children
            else:
                 __a       =   new_children
       else:
            __a       =   new_children

  def __a						(					self     :							Dict				,							SCREAMING_SNAKE_CASE__     :							Node						):





       '''simple docstring'''

       if node.parent and node.parent.right:
            return node == node.parent.right
       return False

  def __a						(					self     :							Any						):





       '''simple docstring'''

       return self.root is None

  def __a						(					self     :							int				,							SCREAMING_SNAKE_CASE__     :							Union[str, Any]						):





       '''simple docstring'''

       __a       =   Node(SCREAMING_SNAKE_CASE__						)  # create a new Node
       if self.empty():  # if Tree is empty
            __a       =   new_node  # set its root
       else:  # Tree is not empty
            __a       =   self.root  # from root
            if parent_node is None:
                 return
            while True:  # While we don't get to a leaf
                 if value < parent_node.value:  # We go left
                      if parent_node.left is None:
                           __a       =   new_node  # We insert the new node in a leaf
                           break
                      else:
                           __a       =   parent_node.left
                 else:
                      if parent_node.right is None:
                           __a       =   new_node
                           break
                      else:
                           __a       =   parent_node.right
            __a       =   parent_node

  def __a						(					self     :							Optional[int]				,							*SCREAMING_SNAKE_CASE__     :							Union[str, Any]						):





       '''simple docstring'''

       for value in values:
            self.__insert(SCREAMING_SNAKE_CASE__						)

  def __a						(					self     :							List[Any]				,							SCREAMING_SNAKE_CASE__     :							Union[str, Any]						):





       '''simple docstring'''

       if self.empty():
            raise IndexError("""Warning: Tree is empty! please use another."""						)
       else:
            __a       =   self.root
            # use lazy evaluation here to avoid NoneType Attribute error
            while node is not None and node.value is not value:
                 __a       =   node.left if value < node.value else node.right
            return node

  def __a						(					self     :							List[Any]				,							SCREAMING_SNAKE_CASE__     :							Node | None = None						):





       '''simple docstring'''

       if node is None:
            if self.root is None:
                 return None
            __a       =   self.root

       if not self.empty():
            while node.right is not None:
                 __a       =   node.right
       return node

  def __a						(					self     :							Dict				,							SCREAMING_SNAKE_CASE__     :							Node | None = None						):





       '''simple docstring'''

       if node is None:
            __a       =   self.root
       if self.root is None:
            return None
       if not self.empty():
            __a       =   self.root
            while node.left is not None:
                 __a       =   node.left
       return node

  def __a						(					self     :							Optional[int]				,							SCREAMING_SNAKE_CASE__     :							int						):





       '''simple docstring'''

       __a       =   self.search(SCREAMING_SNAKE_CASE__						)  # Look for the node with that label
       if node is not None:
            if node.left is None and node.right is None:  # If it has no children
                 self.__reassign_nodes(SCREAMING_SNAKE_CASE__				,							SCREAMING_SNAKE_CASE__						)
            elif node.left is None:  # Has only right children
                 self.__reassign_nodes(SCREAMING_SNAKE_CASE__				,							node.right						)
            elif node.right is None:  # Has only left children
                 self.__reassign_nodes(SCREAMING_SNAKE_CASE__				,							node.left						)
            else:
                 __a       =   self.get_max(
                     node.left						)  # Gets the max value of the left branch
                 self.remove(tmp_node.value						)  # type: ignore
                 __a       =   (
                     tmp_node.value  # type: ignore
                 )  # Assigns the value to the node to delete and keep tree structure

  def __a						(					self     :							Dict				,							SCREAMING_SNAKE_CASE__     :							Node | None						):





       '''simple docstring'''

       if node is not None:
            yield node  # Preorder Traversal
            yield from self.preorder_traverse(node.left						)
            yield from self.preorder_traverse(node.right						)

  def __a						(					self     :							Optional[Any]				,							SCREAMING_SNAKE_CASE__     :							Union[str, Any]=None						):





       '''simple docstring'''

       if traversal_function is None:
            return self.preorder_traverse(self.root						)
       else:
            return traversal_function(self.root						)

  def __a						(					self     :							Optional[Any]				,							SCREAMING_SNAKE_CASE__     :							list				,							SCREAMING_SNAKE_CASE__     :							Node | None						):





       '''simple docstring'''

       if node:
            self.inorder(SCREAMING_SNAKE_CASE__				,							node.left						)
            arr.append(node.value						)
            self.inorder(SCREAMING_SNAKE_CASE__				,							node.right						)


  def __a						(					self     :							Any				,							SCREAMING_SNAKE_CASE__     :							int				,							SCREAMING_SNAKE_CASE__     :							Node						):





       '''simple docstring'''

       __a       =   []
       self.inorder(SCREAMING_SNAKE_CASE__				,							SCREAMING_SNAKE_CASE__						)  # append all values to list using inorder traversal
       return arr[k - 1]




def        __lowercase						(      __SCREAMING_SNAKE_CASE		)				->					list[Node]:
     """simple docstring"""




     __a       =   []
     if curr_node is not None:
          __a       =   postorder(curr_node.left		) + postorder(curr_node.right		) + [curr_node]
     return node_list




def        __lowercase						(      )				->					None:
     """simple docstring"""




     __a       =   (8, 3, 6, 1, 10, 14, 13, 4, 7)
     __a       =   BinarySearchTree()
     for i in testlist:
          t.insert(__SCREAMING_SNAKE_CASE		)

     # Prints all the elements of the list in order traversal
     print(__SCREAMING_SNAKE_CASE		)

     if t.search(6		) is not None:
          print("""The value 6 exists"""		)
     else:
          print("""The value 6 doesn't exist"""		)

     if t.search(-1		) is not None:
          print("""The value -1 exists"""		)
     else:
          print("""The value -1 doesn't exist"""		)

     if not t.empty():
          print("""Max Value: """				,  t.get_max().value		)  # type: ignore
          print("""Min Value: """				,  t.get_min().value		)  # type: ignore

     for i in testlist:
          t.remove(__SCREAMING_SNAKE_CASE		)
          print(__SCREAMING_SNAKE_CASE		)


if __name__ == "__main__":
 import doctest

 doctest.testmod(verbose=True)










'''simple docstring'''







import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class  lowerCAmelCase_						(       snake_case__		,    unittest.TestCase      ):





  """simple docstring"""



  a_       :Union[str, Any]												=LEDTokenizer
  a_       :List[Any]												=LEDTokenizerFast
  a_       :Union[str, Any]												=True

  def __a						(					self     :							Dict						):





       '''simple docstring'''

       super().setUp()
       __a       =   [
           """l""",
           """o""",
           """w""",
           """e""",
           """r""",
           """s""",
           """t""",
           """i""",
           """d""",
           """n""",
           """\u0120""",
           """\u0120l""",
           """\u0120n""",
           """\u0120lo""",
           """\u0120low""",
           """er""",
           """\u0120lowest""",
           """\u0120newer""",
           """\u0120wider""",
           """<unk>""",
       ]
       __a       =   dict(zip(SCREAMING_SNAKE_CASE__				,							range(len(SCREAMING_SNAKE_CASE__						)						)						)						)
       __a       =   ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
       __a       =   {"""unk_token""": """<unk>"""}

       __a       =   os.path.join(self.tmpdirname				,							VOCAB_FILES_NAMES["""vocab_file"""]						)
       __a       =   os.path.join(self.tmpdirname				,							VOCAB_FILES_NAMES["""merges_file"""]						)
       with open(self.vocab_file				,							"""w"""				,							encoding="""utf-8"""						) as fp:
            fp.write(json.dumps(SCREAMING_SNAKE_CASE__						) + """\n"""						)
       with open(self.merges_file				,							"""w"""				,							encoding="""utf-8"""						) as fp:
            fp.write("""\n""".join(SCREAMING_SNAKE_CASE__						)						)

  def __a						(					self     :							Optional[Any]				,							**SCREAMING_SNAKE_CASE__     :							Optional[Any]						):





       '''simple docstring'''

       kwargs.update(self.special_tokens_map						)
       return self.tokenizer_class.from_pretrained(self.tmpdirname				,							**SCREAMING_SNAKE_CASE__						)

  def __a						(					self     :							int				,							**SCREAMING_SNAKE_CASE__     :							Optional[int]						):





       '''simple docstring'''

       kwargs.update(self.special_tokens_map						)
       return self.rust_tokenizer_class.from_pretrained(self.tmpdirname				,							**SCREAMING_SNAKE_CASE__						)

  def __a						(					self     :							str				,							SCREAMING_SNAKE_CASE__     :							int						):





       '''simple docstring'''

       return "lower newer", "lower newer"

  @cached_property
  def __a						(					self     :							Dict						):





       '''simple docstring'''

       return LEDTokenizer.from_pretrained("""allenai/led-base-16384"""						)

  @cached_property
  def __a						(					self     :							Union[str, Any]						):





       '''simple docstring'''

       return LEDTokenizerFast.from_pretrained("""allenai/led-base-16384"""						)

  @require_torch
  def __a						(					self     :							Tuple						):





       '''simple docstring'''

       __a       =   ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
       __a       =   [0, 2_5_0, 2_5_1, 1_7_8_1_8, 1_3, 3_9_1_8_6, 1_9_3_8, 4, 2]

       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            __a       =   tokenizer(SCREAMING_SNAKE_CASE__				,							max_length=len(SCREAMING_SNAKE_CASE__						)				,							padding=SCREAMING_SNAKE_CASE__				,							return_tensors="""pt"""						)
            self.assertIsInstance(SCREAMING_SNAKE_CASE__				,							SCREAMING_SNAKE_CASE__						)

            self.assertEqual((2, 9)				,							batch.input_ids.shape						)
            self.assertEqual((2, 9)				,							batch.attention_mask.shape						)
            __a       =   batch.input_ids.tolist()[0]
            self.assertListEqual(SCREAMING_SNAKE_CASE__				,							SCREAMING_SNAKE_CASE__						)

  @require_torch
  def __a						(					self     :							Dict						):





       '''simple docstring'''

       __a       =   ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            __a       =   tokenizer(SCREAMING_SNAKE_CASE__				,							padding=SCREAMING_SNAKE_CASE__				,							return_tensors="""pt"""						)
            self.assertIn("""input_ids"""				,							SCREAMING_SNAKE_CASE__						)
            self.assertIn("""attention_mask"""				,							SCREAMING_SNAKE_CASE__						)
            self.assertNotIn("""labels"""				,							SCREAMING_SNAKE_CASE__						)
            self.assertNotIn("""decoder_attention_mask"""				,							SCREAMING_SNAKE_CASE__						)

  @require_torch
  def __a						(					self     :							Union[str, Any]						):





       '''simple docstring'''

       __a       =   [
           """Summary of the text.""",
           """Another summary.""",
       ]
       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            __a       =   tokenizer(text_target=SCREAMING_SNAKE_CASE__				,							max_length=3_2				,							padding="""max_length"""				,							return_tensors="""pt"""						)
            self.assertEqual(3_2				,							targets["""input_ids"""].shape[1]						)

  @require_torch
  def __a						(					self     :							Any						):





       '''simple docstring'''

       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            __a       =   tokenizer(
                ["""I am a small frog""" * 1_0_2_4, """I am a small frog"""]				,							padding=SCREAMING_SNAKE_CASE__				,							truncation=SCREAMING_SNAKE_CASE__				,							return_tensors="""pt"""						)
            self.assertIsInstance(SCREAMING_SNAKE_CASE__				,							SCREAMING_SNAKE_CASE__						)
            self.assertEqual(batch.input_ids.shape				,							(2, 5_1_2_2)						)

  @require_torch
  def __a						(					self     :							Tuple						):





       '''simple docstring'''

       __a       =   ["""A long paragraph for summarization."""]
       __a       =   [
           """Summary of the text.""",
       ]
       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            __a       =   tokenizer(SCREAMING_SNAKE_CASE__				,							return_tensors="""pt"""						)
            __a       =   tokenizer(text_target=SCREAMING_SNAKE_CASE__				,							return_tensors="""pt"""						)
            __a       =   inputs["""input_ids"""]
            __a       =   targets["""input_ids"""]
            self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()						)
            self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()						)
            self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()						)
            self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()						)

  @require_torch
  def __a						(					self     :							Dict						):





       '''simple docstring'''

       for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            __a       =   ["""Summary of the text.""", """Another summary."""]
            __a       =   [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

            __a       =   tokenizer(SCREAMING_SNAKE_CASE__				,							padding=SCREAMING_SNAKE_CASE__						)
            __a       =   [[0] * len(SCREAMING_SNAKE_CASE__						) for x in encoded_output["""input_ids"""]]
            __a       =   tokenizer.pad(SCREAMING_SNAKE_CASE__						)
            self.assertSequenceEqual(outputs["""global_attention_mask"""]				,							SCREAMING_SNAKE_CASE__						)

  def __a						(					self     :							List[Any]						):





       '''simple docstring'''

       pass


  def __a						(					self     :							Any						):





       '''simple docstring'''

       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
            with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''						):
                 __a       =   self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE__				,							**SCREAMING_SNAKE_CASE__						)
                 __a       =   self.tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE__				,							**SCREAMING_SNAKE_CASE__						)
                 __a       =   """A, <mask> AllenNLP sentence."""
                 __a       =   tokenizer_r.encode_plus(SCREAMING_SNAKE_CASE__				,							add_special_tokens=SCREAMING_SNAKE_CASE__				,							return_token_type_ids=SCREAMING_SNAKE_CASE__						)
                 __a       =   tokenizer_p.encode_plus(SCREAMING_SNAKE_CASE__				,							add_special_tokens=SCREAMING_SNAKE_CASE__				,							return_token_type_ids=SCREAMING_SNAKE_CASE__						)
                 self.assertEqual(sum(tokens_r["""token_type_ids"""]						)				,							sum(tokens_p["""token_type_ids"""]						)						)
                 self.assertEqual(
                     sum(tokens_r["""attention_mask"""]						) / len(tokens_r["""attention_mask"""]						)				,							sum(tokens_p["""attention_mask"""]						) / len(tokens_p["""attention_mask"""]						)				,							)

                 __a       =   tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]						)
                 __a       =   tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]						)
                 self.assertSequenceEqual(tokens_p["""input_ids"""]				,							[0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]						)
                 self.assertSequenceEqual(tokens_r["""input_ids"""]				,							[0, 2_5_0, 6, 5_0_2_6_4, 3_8_2_3, 4_8_7, 2_1_9_9_2, 3_6_4_5, 4, 2]						)

                 self.assertSequenceEqual(
                     SCREAMING_SNAKE_CASE__				,							["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]						)
                 self.assertSequenceEqual(
                     SCREAMING_SNAKE_CASE__				,							["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]						)






