
"""simple docstring"""







import json
import os
import unittest

from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import (
    VOCAB_FILES_NAMES,
    GPTNeoXJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class 				UpperCAmelCase_	(UpperCAmelCase_  , unittest.TestCase						):
 """simple docstring"""




 UpperCamelCase_						:     Tuple				   =    GPTNeoXJapaneseTokenizer
 UpperCamelCase_						:     Optional[Any]				   =    False
 UpperCamelCase_						:     Dict				   =    {"""do_clean_text""": False, """add_prefix_space""": False}




 def   a      ( self       : str )->					Optional[Any]:



      """simple docstring"""

      super().setUp()

      UpperCAmelCase_						:    Dict    					=  [
          """こん""",
          """こんに""",
          """にちは""",
          """ばんは""",
          """世界,㔺界""",
          """、""",
          """。""",
          """<BR>""",
          """<SP>""",
          """<TAB>""",
          """<URL>""",
          """<EMAIL>""",
          """<TEL>""",
          """<DATE>""",
          """<PRICE>""",
          """<BLOCK>""",
          """<KIGOU>""",
          """<U2000U2BFF>""",
          """<|emoji1|>""",
          """<unk>""",
          """<|startoftext|>""",
          """<|endoftext|>""",
      ]
      UpperCAmelCase_						:    Tuple    					=  {"""emoji""": {"""\ud83d\ude00""": """<|emoji1|>"""}, """emoji_inv""": {"""<|emoji1|>""": """\ud83d\ude00"""}}  # 😀
      UpperCAmelCase_						:    int    					=  {"""unk_token""": """<unk>"""}

      UpperCAmelCase_						:    List[Any]    					=  os.path.join(self.tmpdirname     ,   VOCAB_FILES_NAMES["""vocab_file"""] )
      UpperCAmelCase_						:    List[str]    					=  os.path.join(self.tmpdirname     ,   VOCAB_FILES_NAMES["""emoji_file"""] )
      with open(self.vocab_file     ,   """w"""     ,   encoding="""utf-8""" ) as vocab_writer:
           vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens] ) )
      with open(self.emoji_file     ,   """w""" ) as emoji_writer:
           emoji_writer.write(json.dumps(a_ ) )




 def   a      ( self       : Optional[int]     ,   **a_       : Union[str, Any] )->					Tuple:



      """simple docstring"""

      kwargs.update(self.special_tokens_map )
      return GPTNeoXJapaneseTokenizer.from_pretrained(self.tmpdirname     ,   **a_ )




 def   a      ( self       : Tuple     ,   a_       : int )->					Dict:



      """simple docstring"""

      UpperCAmelCase_						:    List[str]    					=  """こんにちは、世界。 \nこんばんは、㔺界。😀"""
      UpperCAmelCase_						:    int    					=  """こんにちは、世界。 \nこんばんは、世界。😀"""
      return input_text, output_text




 def   a      ( self       : List[str]     ,   a_       : Optional[int] )->					List[Any]:



      """simple docstring"""

      UpperCAmelCase_					,UpperCAmelCase_						:    str    					=  self.get_input_output_texts(a_ )
      UpperCAmelCase_						:    int    					=  tokenizer.encode(a_     ,   add_special_tokens=a_ )
      UpperCAmelCase_						:    List[str]    					=  tokenizer.decode(a_     ,   clean_up_tokenization_spaces=a_ )
      return text, ids




 def   a      ( self       : Optional[Any] )->					Optional[int]:



      """simple docstring"""

      pass  # TODO add if relevant




 def   a      ( self       : Union[str, Any] )->					Tuple:



      """simple docstring"""

      pass  # TODO add if relevant




 def   a      ( self       : Optional[Any] )->					Optional[Any]:



      """simple docstring"""

      pass  # TODO add if relevant




 def   a      ( self       : Optional[Any] )->					int:



      """simple docstring"""

      UpperCAmelCase_						:    Union[str, Any]    					=  self.get_tokenizer()

      # Testing tokenization
      UpperCAmelCase_						:    str    					=  """こんにちは、世界。　こんばんは、㔺界。"""
      UpperCAmelCase_						:    str    					=  ["""こん""", """にちは""", """、""", """世界""", """。""", """<SP>""", """こん""", """ばんは""", """、""", """㔺界""", """。"""]
      UpperCAmelCase_						:    Optional[Any]    					=  tokenizer.tokenize(a_ )
      self.assertListEqual(a_     ,   a_ )

      # Testing conversion to ids without special tokens
      UpperCAmelCase_						:    Optional[Any]    					=  [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
      UpperCAmelCase_						:    Optional[int]    					=  tokenizer.convert_tokens_to_ids(a_ )
      self.assertListEqual(a_     ,   a_ )

      # Testing conversion to ids with special tokens
      UpperCAmelCase_						:    int    					=  tokens + [tokenizer.unk_token]
      UpperCAmelCase_						:    List[str]    					=  [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
      UpperCAmelCase_						:    Optional[Any]    					=  tokenizer.convert_tokens_to_ids(a_ )
      self.assertListEqual(a_     ,   a_ )




 @slow
 def   a      ( self       : Any )->					Optional[int]:



      """simple docstring"""

      UpperCAmelCase_						:    Union[str, Any]    					=  self.tokenizer_class.from_pretrained("""abeja/gpt-neox-japanese-2.7b""" )

      UpperCAmelCase_						:    Any    					=  tokenizer.encode("""ありがとう。"""     ,   add_special_tokens=a_ )
      UpperCAmelCase_						:    int    					=  tokenizer.encode("""どういたしまして。"""     ,   add_special_tokens=a_ )

      UpperCAmelCase_						:    Any    					=  tokenizer.build_inputs_with_special_tokens(a_ )
      UpperCAmelCase_						:    Tuple    					=  tokenizer.build_inputs_with_special_tokens(a_     ,   a_ )

      assert encoded_sentence == ids_a
      assert encoded_pair == ids_a + ids_a




 def   a      ( self       : int )->					Dict:



      """simple docstring"""

      pass






 def   a      ( self       : Optional[Any] )->					List[str]:



      """simple docstring"""

      pass



"""simple docstring"""







from __future__ import annotations



class 		UpperCAmelCase_	:
 """simple docstring"""




 def __init__( self       : Any     ,   a_       : int = 0 )->					None:



      """simple docstring"""

      UpperCAmelCase_						:    Tuple    					=  value
      UpperCAmelCase_						:    Node | None    					=  None
      UpperCAmelCase_						:    Node | None    					=  None




def 			A_			(					lowercase						, lowercase      )     ->							Node | None:


     """simple docstring"""







     if treea is None:
          return treea
     if treea is None:
          return treea

     UpperCAmelCase_						:    int    					=  treea.value + treea.value
     UpperCAmelCase_						:    List[str]    					=  merge_two_binary_trees(treea.left						, treea.left      )
     UpperCAmelCase_						:    List[str]    					=  merge_two_binary_trees(treea.right						, treea.right      )
     return treea




def 			A_			(					lowercase      )     ->							None:


     """simple docstring"""







     if root:
          print(root.value      )
          print_preorder(root.left      )
          print_preorder(root.right      )


if __name__ == "__main__":
       lowercase_						    =					Node(1)
       lowercase_						    =					Node(2)
       lowercase_						    =					Node(3)
       lowercase_						    =					Node(4)

       lowercase_						    =					Node(2)
       lowercase_						    =					Node(4)
       lowercase_						    =					Node(6)
       lowercase_						    =					Node(9)
       lowercase_						    =					Node(5)

       print("Tree1 is: ")
       print_preorder(treea)
       print("Tree2 is: ")
       print_preorder(treea)
       lowercase_						    =					merge_two_binary_trees(treea, treea)
       print("Merged Tree is: ")
       print_preorder(merged_tree)

