

class       __UpperCAmelCase  :



   def __init__(							self							:  Union[str, Any],	__A							:  Optional[int]		):
     UpperCAmelCase :							Union[str, Any]								=				data
     UpperCAmelCase :							BinaryTreeNode | None								=				None
     UpperCAmelCase :							BinaryTreeNode | None								=				None






def     a__  (	UpperCAmelCase							:    BinaryTreeNode | None       ,				UpperCAmelCase							:    int    )						->		Dict:
  if node is None:
    UpperCAmelCase :							List[Any]								=				BinaryTreeNode(UpperCamelCase__    )
    return node

  # binary search tree is not empty,
  # so we will insert it into the tree
  # if new_value is less than value of data in node,
  #  add it to left subtree and proceed recursively
  if new_value < node.data:
    UpperCAmelCase :							Dict								=				insert(node.left_child       ,				UpperCamelCase__    )
  else:
    # if new_value is greater than value of data in node,
    #  add it to right subtree and proceed recursively
    UpperCAmelCase :							int								=				insert(node.right_child       ,				UpperCamelCase__    )
  return node

def     a__  (	UpperCAmelCase							:    None | BinaryTreeNode    )						->		List[str]:  # if node is None,return
  if node:
    UpperCAmelCase :							Dict								=				inorder(node.left_child    )
    UpperCAmelCase :							str								=				[*inorder_array, node.data]
    UpperCAmelCase :							List[Any]								=				inorder_array + inorder(node.right_child    )
  else:
    UpperCAmelCase :							Union[str, Any]								=				[]
  return inorder_array

def     a__  (	)						->		Dict:
  UpperCAmelCase :							List[Any]								=				insert(UpperCamelCase__       ,				15    )
  insert(UpperCamelCase__       ,				10    )
  insert(UpperCamelCase__       ,				25    )
  insert(UpperCamelCase__       ,				6    )
  insert(UpperCamelCase__       ,				14    )
  insert(UpperCamelCase__       ,				20    )
  insert(UpperCamelCase__       ,				60    )
  return root

def     a__  (	)						->		Union[str, Any]:
  # main function
  UpperCAmelCase :							Dict								=				make_tree()
  print('''Printing values of binary search tree in Inorder Traversal.'''    )
  inorder(UpperCamelCase__    )


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    main()








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       __UpperCAmelCase  ( unittest.TestCase		):



   def  __magic_name__					(							self							:  Dict		):
     UpperCAmelCase :							Tuple								=				'''<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(''' '''		)
     UpperCAmelCase :							List[str]								=				dict(zip(__A,	range(len(__A		)		)		)		)

     UpperCAmelCase :							int								=				{
         '''pad_token''': '''<pad>''',
         '''unk_token''': '''<unk>''',
         '''bos_token''': '''<s>''',
         '''eos_token''': '''</s>''',
     }
     UpperCAmelCase :							str								=				{
         '''feature_size''': 1,
         '''padding_value''': 0.0,
         '''sampling_rate''': 1_6_0_0_0,
         '''return_attention_mask''': False,
         '''do_normalize''': True,
     }

     UpperCAmelCase :							List[Any]								=				tempfile.mkdtemp()
     UpperCAmelCase :							str								=				os.path.join(self.tmpdirname,	VOCAB_FILES_NAMES['''vocab_file''']		)
     UpperCAmelCase :							Tuple								=				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  __magic_name__					(							self							:  List[Any],	**__A							:  List[Any]		):
     UpperCAmelCase :							str								=				self.add_kwargs_tokens_map.copy()
     kwargs.update(__A		)
     return WavaVecaCTCTokenizer.from_pretrained(self.tmpdirname,	**__A		)



   def  __magic_name__					(							self							:  List[Any],	**__A							:  Union[str, Any]		):
     return WavaVecaFeatureExtractor.from_pretrained(self.tmpdirname,	**__A		)



   def  __magic_name__					(							self							:  Any		):
     shutil.rmtree(self.tmpdirname		)



   def  __magic_name__					(							self							:  str		):
     UpperCAmelCase :							Any								=				self.get_tokenizer()
     UpperCAmelCase :							Optional[int]								=				self.get_feature_extractor()

     UpperCAmelCase :							Tuple								=				WavaVecaProcessor(tokenizer=__A,	feature_extractor=__A		)

     processor.save_pretrained(self.tmpdirname		)
     UpperCAmelCase :							Union[str, Any]								=				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  __magic_name__					(							self							:  Optional[int]		):
     UpperCAmelCase :							int								=				WavaVecaProcessor(tokenizer=self.get_tokenizer(),	feature_extractor=self.get_feature_extractor()		)
     processor.save_pretrained(self.tmpdirname		)

     UpperCAmelCase :							Dict								=				self.get_tokenizer(bos_token='''(BOS)''',	eos_token='''(EOS)'''		)
     UpperCAmelCase :							int								=				self.get_feature_extractor(do_normalize=__A,	padding_value=1.0		)

     UpperCAmelCase :							int								=				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  __magic_name__					(							self							:  Union[str, Any]		):
     UpperCAmelCase :							Optional[Any]								=				self.get_feature_extractor()
     UpperCAmelCase :							Optional[int]								=				self.get_tokenizer()

     UpperCAmelCase :							Any								=				WavaVecaProcessor(tokenizer=__A,	feature_extractor=__A		)

     UpperCAmelCase :							Tuple								=				floats_list((3, 1_0_0_0)		)

     UpperCAmelCase :							Any								=				feature_extractor(__A,	return_tensors='''np'''		)
     UpperCAmelCase :							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  __magic_name__					(							self							:  Union[str, Any]		):
     UpperCAmelCase :							Optional[Any]								=				self.get_feature_extractor()
     UpperCAmelCase :							Union[str, Any]								=				self.get_tokenizer()

     UpperCAmelCase :							List[Any]								=				WavaVecaProcessor(tokenizer=__A,	feature_extractor=__A		)

     UpperCAmelCase :							List[str]								=				'''This is a test string'''

     UpperCAmelCase :							Tuple								=				processor(text=__A		)

     UpperCAmelCase :							Tuple								=				tokenizer(__A		)

     for key in encoded_tok.keys():
       self.assertListEqual(encoded_tok[key],	encoded_processor[key]		)



   def  __magic_name__					(							self							:  Optional[int]		):
     UpperCAmelCase :							Tuple								=				self.get_feature_extractor()
     UpperCAmelCase :							int								=				self.get_tokenizer()

     UpperCAmelCase :							List[str]								=				WavaVecaProcessor(tokenizer=__A,	feature_extractor=__A		)

     UpperCAmelCase :							Any								=				[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

     UpperCAmelCase :							str								=				processor.batch_decode(__A		)
     UpperCAmelCase :							List[str]								=				tokenizer.batch_decode(__A		)

     self.assertListEqual(__A,	__A		)





   def  __magic_name__					(							self							:  int		):
     UpperCAmelCase :							Optional[int]								=				self.get_feature_extractor()
     UpperCAmelCase :							List[str]								=				self.get_tokenizer()

     UpperCAmelCase :							Any								=				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''',	)





