code: 
  
  import json
  import os
  import shutil
  import tempfile
  import unittest
  
  from transformers.models.wavaveca import WavaVecaCTCTokenizer, WavaVecaFeatureExtractor, WavaVecaProcessor
  from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
  from transformers.utils import FEATURE_EXTRACTOR_NAME
  
  from .test_feature_extraction_wavaveca import floats_list
  
  
  class    SCREAMING_SNAKE_CASE__      (unittest.TestCase  ):
  
  
  
  
  
      def    snake_case_       (   self):
           lowercase__					:     Union[str, Any]   = '<pad> <s> </s> <unk> | E T A O N I H S R D L U M W C F G Y P B V K \' X J Q Z'.split(' ')
           lowercase__					:     Dict   = dict(zip(a		,     range(len(a))))
  
           lowercase__					:     str   = {
               'pad_token': '<pad>',
               'unk_token': '<unk>',
               'bos_token': '<s>',
               'eos_token': '</s>',
           }
           lowercase__					:     Dict   = {
               'feature_size': 1,
               'padding_value': 0.0,
               'sampling_rate': 1_6000,
               'return_attention_mask': False,
               'do_normalize': True,
           }
  
           lowercase__					:     Any   = tempfile.mkdtemp()
           lowercase__					:     Tuple   = os.path.join(self.tmpdirname		,     VOCAB_FILES_NAMES['vocab_file'])
           lowercase__					:     Any   = os.path.join(self.tmpdirname		,     a)
           with open(self.vocab_file		,     'w'		,     encoding='utf-8') as fp:
                fp.write(json.dumps(a) + '\n')
  
           with open(self.feature_extraction_file		,     'w'		,     encoding='utf-8') as fp:
                fp.write(json.dumps(a) + '\n')
  
  
  
  
  
      def    snake_case_       (   self		,     **a):
           lowercase__					:     Any   = self.add_kwargs_tokens_map.copy()
           kwargs.update(a)
           return WavaVecaCTCTokenizer.from_pretrained(self.tmpdirname		,     **a)
  
  
  
  
  
      def    snake_case_       (   self		,     **a):
           return WavaVecaFeatureExtractor.from_pretrained(self.tmpdirname		,     **a)
  
  
  
  
  
      def    snake_case_       (   self):
           shutil.rmtree(self.tmpdirname)
  
  
  
  
  
      def    snake_case_       (   self):
           lowercase__					:     Dict   = self.get_tokenizer()
           lowercase__					:     Optional[int]   = self.get_feature_extractor()
  
           lowercase__					:     List[str]   = WavaVecaProcessor(tokenizer=a		,     feature_extractor=a)
  
           processor.save_pretrained(self.tmpdirname)
           lowercase__					:     Optional[int]   = WavaVecaProcessor.from_pretrained(self.tmpdirname)
  
           self.assertEqual(processor.tokenizer.get_vocab()		,     tokenizer.get_vocab())
           self.assertIsInstance(processor.tokenizer		,     a)
  
           self.assertEqual(processor.feature_extractor.to_json_string()		,     feature_extractor.to_json_string())
           self.assertIsInstance(processor.feature_extractor		,     a)
  
  
  
  
  
      def    snake_case_       (   self):
           lowercase__					:     Optional[Any]   = WavaVecaProcessor(tokenizer=self.get_tokenizer()		,     feature_extractor=self.get_feature_extractor())
           processor.save_pretrained(self.tmpdirname)
  
           lowercase__					:     Any   = self.get_tokenizer(bos_token='(BOS)'		,     eos_token='(EOS)')
           lowercase__					:     str   = self.get_feature_extractor(do_normalize=a		,     padding_value=1.0)
  
           lowercase__					:     Union[str, Any]   = WavaVecaProcessor.from_pretrained(
               self.tmpdirname		,     bos_token='(BOS)'		,     eos_token='(EOS)'		,     do_normalize=a		,     padding_value=1.0)
  
           self.assertEqual(processor.tokenizer.get_vocab()		,     tokenizer_add_kwargs.get_vocab())
           self.assertIsInstance(processor.tokenizer		,     a)
  
           self.assertEqual(processor.feature_extractor.to_json_string()		,     feature_extractor_add_kwargs.to_json_string())
           self.assertIsInstance(processor.feature_extractor		,     a)
  
  
  
  
  
      def    snake_case_       (   self):
           lowercase__					:     int   = self.get_feature_extractor()
           lowercase__					:     Tuple   = self.get_tokenizer()
  
           lowercase__					:     Tuple   = WavaVecaProcessor(tokenizer=a		,     feature_extractor=a)
  
           lowercase__					:     Union[str, Any]   = floats_list((3, 1000))
  
           lowercase__					:     Optional[Any]   = feature_extractor(a		,     return_tensors='np')
           lowercase__					:     Optional[int]   = processor(a		,     return_tensors='np')
  
           for key in input_feat_extract.keys():
                self.assertAlmostEqual(input_feat_extract[key].sum()		,     input_processor[key].sum()		,     delta=1e-2)
  
  
  
  
  
      def    snake_case_       (   self):
           lowercase__					:     Union[str, Any]   = self.get_feature_extractor()
           lowercase__					:     str   = self.get_tokenizer()
  
           lowercase__					:     Optional[int]   = WavaVecaProcessor(tokenizer=a		,     feature_extractor=a)
  
           lowercase__					:     int   = 'This is a test string'
  
           lowercase__					:     List[Any]   = processor(text=a)
  
           lowercase__					:     Tuple   = tokenizer(a)
  
           for key in encoded_tok.keys():
                self.assertListEqual(encoded_tok[key]		,     encoded_processor[key])
  
  
  
  
  
      def    snake_case_       (   self):
           lowercase__					:     Any   = self.get_feature_extractor()
           lowercase__					:     int   = self.get_tokenizer()
  
           lowercase__					:     int   = WavaVecaProcessor(tokenizer=a		,     feature_extractor=a)
  
           lowercase__					:     List[Any]   = [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]
  
           lowercase__					:     Optional[Any]   = processor.batch_decode(a)
           lowercase__					:     List[str]   = tokenizer.batch_decode(a)
  
           self.assertListEqual(a		,     a)
  
  
  
  
  
      def    snake_case_       (   self):
           lowercase__					:     Optional[Any]   = self.get_feature_extractor()
           lowercase__					:     Optional[int]   = self.get_tokenizer()
  
           lowercase__					:     int   = WavaVecaProcessor(tokenizer=a		,     feature_extractor=a)
  
           self.assertListEqual(
               processor.model_input_names		,     feature_extractor.model_input_names		,     msg='`processor` and `feature_extractor` model input names do not match'		,     )
  
  
style_context: 
  
  from __future__ import annotations
  
  
  class    SCREAMING_SNAKE_CASE__      :
  
  
  
  
  
      def __init__(   self		,     a = 0):
           lowercase__					:     int   = value
           lowercase__					:     Node | None   = None
           lowercase__					:     Node | None   = None
  
  
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Node | None			,  SCREAMING_SNAKE_CASE_	:					Node | None    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       if treea is None:
            return treea
       if treea is None:
            return treea
  
       lowercase__					:     Optional[Any]   = treea.value + treea.value
       lowercase__					:     Union[str, Any]   = merge_two_binary_trees(treea.left			,  treea.left    )
       lowercase__					:     Optional[Any]   = merge_two_binary_trees(treea.right			,  treea.right    )
       return treea
  
  def 			snake_case__    (					SCREAMING_SNAKE_CASE_	:					Node | None    ):
  
  
  
       '''simple docstring'''
  
  
  
  
  
       if root:
            print(root.value    )
            print_preorder(root.left    )
            print_preorder(root.right    )
  
  
  if __name__ == "__main__":
         snake_case_    						=				Node(1)
         snake_case_    						=				Node(2)
         snake_case_    						=				Node(3)
         snake_case_    						=				Node(4)
  
         snake_case_    						=				Node(2)
         snake_case_    						=				Node(4)
         snake_case_    						=				Node(6)
         snake_case_    						=				Node(9)
         snake_case_    						=				Node(5)
  
         print('''Tree1 is: ''')
         print_preorder(treea)
         print('''Tree2 is: ''')
         print_preorder(treea)
         snake_case_    						=				merge_two_binary_trees(treea, treea)
         print('''Merged Tree is: ''')
         print_preorder(merged_tree)
  
  