


'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
		from PIL import Image

		from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor
@require_tokenizers
@require_vision
class    lowercase	(							unittest.TestCase					):

		"""simple docstring"""

		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Optional[Any]												= tempfile.mkdtemp()

							# fmt: off
							UpperCamelCase__   :List[str]												= ['''[UNK]''', '''[CLS]''', '''[SEP]''', '''[PAD]''', '''[MASK]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''', ''',''', '''low''', '''lowest''']
							# fmt: on
							UpperCamelCase__   :Dict												= os.path.join(self.tmpdirname    ,   VOCAB_FILES_NAMES['''vocab_file''']							)
							with open(self.vocab_file    ,   '''w'''    ,   encoding='''utf-8'''							) as vocab_writer:
												vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]							)							)

							UpperCamelCase__   :int												= {
							    '''do_resize''': True,
							    '''size''': {'''height''': 18, '''width''': 18},
							    '''do_normalize''': True,
							    '''image_mean''': [0.5, 0.5, 0.5],
							    '''image_std''': [0.5, 0.5, 0.5],
							}
							UpperCamelCase__   :Union[str, Any]												= os.path.join(self.tmpdirname    ,   UpperCamelCase_							)
							with open(self.image_processor_file    ,   '''w'''    ,   encoding='''utf-8'''							) as fp:
												json.dump(UpperCamelCase_    ,   UpperCamelCase_							)




		def     lowerCAmelCase__				(		self    ,   **UpperCamelCase_							):

							'''simple docstring'''


							return BertTokenizer.from_pretrained(self.tmpdirname    ,   **UpperCamelCase_							)




		def     lowerCAmelCase__				(		self    ,   **UpperCamelCase_							):

							'''simple docstring'''


							return ViTImageProcessor.from_pretrained(self.tmpdirname    ,   **UpperCamelCase_							)




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							shutil.rmtree(self.tmpdirname							)




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Tuple												= [np.random.randint(255    ,   size=(3, 30, 400)    ,   dtype=np.uinta							)]

							UpperCamelCase__   :List[Any]												= [Image.fromarray(np.moveaxis(UpperCamelCase_    ,   0    ,   -1							)							) for x in image_inputs]

							return image_inputs




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Any												= self.get_tokenizer()
							UpperCamelCase__   :Dict												= self.get_image_processor()

							UpperCamelCase__   :str												= VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase_    ,   image_processor=UpperCamelCase_							)

							processor.save_pretrained(self.tmpdirname							)
							UpperCamelCase__   :Union[str, Any]												= VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname							)

							self.assertEqual(processor.tokenizer.get_vocab()    ,   tokenizer.get_vocab()							)
							self.assertIsInstance(processor.tokenizer    ,   (BertTokenizer, BertTokenizerFast)							)

							self.assertEqual(processor.image_processor.to_json_string()    ,   image_processor.to_json_string()							)
							self.assertIsInstance(processor.image_processor    ,   UpperCamelCase_							)




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Any												= VisionTextDualEncoderProcessor(
							    tokenizer=self.get_tokenizer()    ,   image_processor=self.get_image_processor()							)
							processor.save_pretrained(self.tmpdirname							)

							UpperCamelCase__   :Tuple												= self.get_tokenizer(bos_token='''(BOS)'''    ,   eos_token='''(EOS)'''							)
							UpperCamelCase__   :Union[str, Any]												= self.get_image_processor(do_normalize=UpperCamelCase_    ,   padding_value=1.0							)

							UpperCamelCase__   :Any												= VisionTextDualEncoderProcessor.from_pretrained(
							    self.tmpdirname    ,   bos_token='''(BOS)'''    ,   eos_token='''(EOS)'''    ,   do_normalize=UpperCamelCase_    ,   padding_value=1.0							)

							self.assertEqual(processor.tokenizer.get_vocab()    ,   tokenizer_add_kwargs.get_vocab()							)
							self.assertIsInstance(processor.tokenizer    ,   (BertTokenizer, BertTokenizerFast)							)

							self.assertEqual(processor.image_processor.to_json_string()    ,   image_processor_add_kwargs.to_json_string()							)
							self.assertIsInstance(processor.image_processor    ,   UpperCamelCase_							)




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Tuple												= self.get_image_processor()
							UpperCamelCase__   :List[Any]												= self.get_tokenizer()

							UpperCamelCase__   :Dict												= VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase_    ,   image_processor=UpperCamelCase_							)

							UpperCamelCase__   :Optional[Any]												= self.prepare_image_inputs()

							UpperCamelCase__   :List[str]												= image_processor(UpperCamelCase_    ,   return_tensors='''np'''							)
							UpperCamelCase__   :Optional[int]												= processor(images=UpperCamelCase_    ,   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     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :List[str]												= self.get_image_processor()
							UpperCamelCase__   :List[str]												= self.get_tokenizer()

							UpperCamelCase__   :List[Any]												= VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase_    ,   image_processor=UpperCamelCase_							)

							UpperCamelCase__   :Any												= '''lower newer'''

							UpperCamelCase__   :Optional[Any]												= processor(text=UpperCamelCase_							)

							UpperCamelCase__   :Tuple												= tokenizer(UpperCamelCase_							)

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




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :str												= self.get_image_processor()
							UpperCamelCase__   :str												= self.get_tokenizer()

							UpperCamelCase__   :Tuple												= VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase_    ,   image_processor=UpperCamelCase_							)

							UpperCamelCase__   :List[Any]												= '''lower newer'''
							UpperCamelCase__   :Optional[int]												= self.prepare_image_inputs()

							UpperCamelCase__   :Optional[int]												= processor(text=UpperCamelCase_    ,   images=UpperCamelCase_							)

							self.assertListEqual(list(inputs.keys()							)    ,   ['''input_ids''', '''token_type_ids''', '''attention_mask''', '''pixel_values''']							)

							# test if it raises when no input is passed
							with self.assertRaises(UpperCamelCase_							):
												processor()




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Tuple												= self.get_image_processor()
							UpperCamelCase__   :List[str]												= self.get_tokenizer()

							UpperCamelCase__   :Tuple												= VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase_    ,   image_processor=UpperCamelCase_							)

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

							UpperCamelCase__   :List[str]												= processor.batch_decode(UpperCamelCase_							)
							UpperCamelCase__   :Any												= tokenizer.batch_decode(UpperCamelCase_							)

							self.assertListEqual(UpperCamelCase_    ,   UpperCamelCase_							)




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Optional[int]												= self.get_image_processor()
							UpperCamelCase__   :List[Any]												= self.get_tokenizer()

							UpperCamelCase__   :int												= VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase_    ,   image_processor=UpperCamelCase_							)

							UpperCamelCase__   :List[str]												= '''lower newer'''
							UpperCamelCase__   :Tuple												= self.prepare_image_inputs()

							UpperCamelCase__   :Dict												= processor(text=UpperCamelCase_    ,   images=UpperCamelCase_							)

							self.assertListEqual(list(inputs.keys()							)    ,   processor.model_input_names							)




"""simple docstring"""
from __future__ import annotations



class       SCREAMING_SNAKE_CASE__  :

   def __init__(   self      ,     _SCREAMING_SNAKE_CASE						)  ->      None:





    '''simple docstring'''




    UpperCAmelCase	:					Any	=	data
    UpperCAmelCase	:					Node | None	=	None
    UpperCAmelCase	:					Node | None	=	None

def       _snake_case						(						UpperCamelCase						:		Node | None						):  # In Order traversal of the tree
 if tree:
  display(tree.left						)
  print(tree.data						)
  display(tree.right						)

def       _snake_case						(						UpperCamelCase						:		Node | None						):
 return 1 + max(depth_of_tree(tree.left						)			,		depth_of_tree(tree.right						)						) if tree else 0

def       _snake_case						(						UpperCamelCase						:		Node						):
 if not tree:
  return True
 if tree.left and tree.right:
  return is_full_binary_tree(tree.left						) and is_full_binary_tree(tree.right						)
 else:
  return not tree.left and not tree.right

def       _snake_case						(						):  # Main function for testing.
 UpperCAmelCase	:					int	=	Node(1						)
 UpperCAmelCase	:					Tuple	=	Node(2						)
 UpperCAmelCase	:					Any	=	Node(3						)
 UpperCAmelCase	:					Optional[int]	=	Node(4						)
 UpperCAmelCase	:					Any	=	Node(5						)
 UpperCAmelCase	:					Optional[int]	=	Node(6						)
 UpperCAmelCase	:					int	=	Node(7						)
 UpperCAmelCase	:					str	=	Node(8						)
 UpperCAmelCase	:					str	=	Node(9						)

 print(is_full_binary_tree(UpperCamelCase						)						)
 print(depth_of_tree(UpperCamelCase						)						)
 print("""Tree is: """						)
 display(UpperCamelCase						)


if __name__ == "__main__":
      main()
