



"""simple docstring"""

class 						lowerCAmelCase__	:


	'''simple docstring'''







	def __init__(			self							:					Optional[int]    ,					_SCREAMING_SNAKE_CASE							:					Dict						)	->  None:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       int 							=    data
					SCREAMING_SNAKE_CASE	:       BinaryTreeNode | None 							=    None
					SCREAMING_SNAKE_CASE	:       BinaryTreeNode | None 							=    None




def    __snake_case       (  __A			:	BinaryTreeNode | None       ,		__A			:	int    )    ->					Optional[Any]:






				'''simple docstring'''
				if node is None:
								SCREAMING_SNAKE_CASE	:       Optional[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:
								SCREAMING_SNAKE_CASE	:       str 							=    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
								SCREAMING_SNAKE_CASE	:       Tuple 							=    insert(node.right_child       ,		UpperCamelCase__    )
				return node
def    __snake_case       (  __A			:	None | BinaryTreeNode    )    ->					str:  # if node is None,return






				'''simple docstring'''
				if node:
								SCREAMING_SNAKE_CASE	:       Any 							=    inorder(node.left_child    )
								SCREAMING_SNAKE_CASE	:       int 							=    [*inorder_array, node.data]
								SCREAMING_SNAKE_CASE	:       Optional[int] 							=    inorder_array + inorder(node.right_child    )
				else:
								SCREAMING_SNAKE_CASE	:       List[str] 							=    []
				return inorder_array
def    __snake_case       (  )    ->					Dict:






				'''simple docstring'''
				SCREAMING_SNAKE_CASE	:       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    __snake_case       (  )    ->					Optional[Any]:






				'''simple docstring'''
				# main function
				SCREAMING_SNAKE_CASE	:       Dict 							=    make_tree()
				print('Printing values of binary search tree in Inorder Traversal.'    )
				inorder(UpperCamelCase__    )


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							main()






"""simple docstring"""

import json
import os
import random
import shutil
import tempfile
import unittest

import numpy as np
import pytest

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


if is_vision_available():
							from PIL import Image

							from transformers import FlavaImageProcessor, FlavaProcessor
							from transformers.models.flava.image_processing_flava import (
							    FLAVA_CODEBOOK_MEAN,
							    FLAVA_CODEBOOK_STD,
							    FLAVA_IMAGE_MEAN,
							    FLAVA_IMAGE_STD,
							)
@require_vision
class 						lowerCAmelCase__	(  unittest.TestCase   ):


	'''simple docstring'''







	def  _lowerCAmelCase    (			self							:					int						)	->  Union[str, Any]:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       Any 							=    tempfile.mkdtemp()

					# fmt: off
					SCREAMING_SNAKE_CASE	:       Optional[Any] 							=    ['[UNK]', '[CLS]', '[SEP]', '[PAD]', '[MASK]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing', ',', 'low', 'lowest']
					# fmt: on
					SCREAMING_SNAKE_CASE	:       Union[str, Any] 							=    os.path.join(self.tmpdirname    ,					VOCAB_FILES_NAMES['vocab_file']						)

					with open(self.vocab_file    ,					'w'    ,					encoding='utf-8'						) as fp:
									fp.write(''.join([x + '\n' for x in vocab_tokens]						)						)

					SCREAMING_SNAKE_CASE	:       Optional[Any] 							=    {
					    'image_mean': FLAVA_IMAGE_MEAN,
					    'image_std': FLAVA_IMAGE_STD,
					    'do_normalize': True,
					    'do_resize': True,
					    'size': 224,
					    'do_center_crop': True,
					    'crop_size': 224,
					    'input_size_patches': 14,
					    'total_mask_patches': 75,
					    'mask_group_max_patches': None,
					    'mask_group_min_patches': 16,
					    'mask_group_min_aspect_ratio': 0.3,
					    'mask_group_max_aspect_ratio': None,
					    'codebook_do_resize': True,
					    'codebook_size': 112,
					    'codebook_do_center_crop': True,
					    'codebook_crop_size': 112,
					    'codebook_do_map_pixels': True,
					    'codebook_do_normalize': True,
					    'codebook_image_mean': FLAVA_CODEBOOK_MEAN,
					    'codebook_image_std': FLAVA_CODEBOOK_STD,
					}

					SCREAMING_SNAKE_CASE	:       List[Any] 							=    os.path.join(self.tmpdirname    ,					_SCREAMING_SNAKE_CASE						)
					with open(self.image_processor_file    ,					'w'    ,					encoding='utf-8'						) as fp:
									json.dump(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE						)





	def  _lowerCAmelCase    (			self							:					Any    ,					**_SCREAMING_SNAKE_CASE							:					str						)	->  str:





					"""simple docstring"""


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





	def  _lowerCAmelCase    (			self							:					int    ,					**_SCREAMING_SNAKE_CASE							:					Any						)	->  Union[str, Any]:





					"""simple docstring"""


					return BertTokenizerFast.from_pretrained(self.tmpdirname    ,					**_SCREAMING_SNAKE_CASE						)





	def  _lowerCAmelCase    (			self							:					Union[str, Any]    ,					**_SCREAMING_SNAKE_CASE							:					Dict						)	->  str:





					"""simple docstring"""


					return FlavaImageProcessor.from_pretrained(self.tmpdirname    ,					**_SCREAMING_SNAKE_CASE						)





	def  _lowerCAmelCase    (			self							:					Dict						)	->  str:





					"""simple docstring"""


					shutil.rmtree(self.tmpdirname						)





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





					"""simple docstring"""


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

					SCREAMING_SNAKE_CASE	:       str 							=    [Image.fromarray(np.moveaxis(_SCREAMING_SNAKE_CASE    ,					0    ,					-1						)						) for x in image_inputs]

					return image_inputs





	def  _lowerCAmelCase    (			self							:					Tuple						)	->  Tuple:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       int 							=    self.get_tokenizer()
					SCREAMING_SNAKE_CASE	:       List[Any] 							=    self.get_rust_tokenizer()
					SCREAMING_SNAKE_CASE	:       str 							=    self.get_image_processor()

					SCREAMING_SNAKE_CASE	:       int 							=    FlavaProcessor(tokenizer=_SCREAMING_SNAKE_CASE    ,					image_processor=_SCREAMING_SNAKE_CASE						)
					processor_slow.save_pretrained(self.tmpdirname						)
					SCREAMING_SNAKE_CASE	:       Union[str, Any] 							=    FlavaProcessor.from_pretrained(self.tmpdirname    ,					use_fast=_SCREAMING_SNAKE_CASE						)

					SCREAMING_SNAKE_CASE	:       str 							=    FlavaProcessor(tokenizer=_SCREAMING_SNAKE_CASE    ,					image_processor=_SCREAMING_SNAKE_CASE						)
					processor_fast.save_pretrained(self.tmpdirname						)
					SCREAMING_SNAKE_CASE	:       Optional[Any] 							=    FlavaProcessor.from_pretrained(self.tmpdirname						)

					self.assertEqual(processor_slow.tokenizer.get_vocab()    ,					tokenizer_slow.get_vocab()						)
					self.assertEqual(processor_fast.tokenizer.get_vocab()    ,					tokenizer_fast.get_vocab()						)
					self.assertEqual(tokenizer_slow.get_vocab()    ,					tokenizer_fast.get_vocab()						)
					self.assertIsInstance(processor_slow.tokenizer    ,					_SCREAMING_SNAKE_CASE						)
					self.assertIsInstance(processor_fast.tokenizer    ,					_SCREAMING_SNAKE_CASE						)

					self.assertEqual(processor_slow.image_processor.to_json_string()    ,					image_processor.to_json_string()						)
					self.assertEqual(processor_fast.image_processor.to_json_string()    ,					image_processor.to_json_string()						)
					self.assertIsInstance(processor_slow.image_processor    ,					_SCREAMING_SNAKE_CASE						)
					self.assertIsInstance(processor_fast.image_processor    ,					_SCREAMING_SNAKE_CASE						)





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





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       Tuple 							=    FlavaProcessor(tokenizer=self.get_tokenizer()    ,					image_processor=self.get_image_processor()						)
					processor.save_pretrained(self.tmpdirname						)

					SCREAMING_SNAKE_CASE	:       Dict 							=    self.get_tokenizer(bos_token='(BOS)'    ,					eos_token='(EOS)'						)
					SCREAMING_SNAKE_CASE	:       Union[str, Any] 							=    self.get_image_processor(do_normalize=_SCREAMING_SNAKE_CASE    ,					padding_value=1.0						)

					SCREAMING_SNAKE_CASE	:       List[str] 							=    FlavaProcessor.from_pretrained(
					    self.tmpdirname    ,					bos_token='(BOS)'    ,					eos_token='(EOS)'    ,					do_normalize=_SCREAMING_SNAKE_CASE    ,					padding_value=1.0						)

					self.assertEqual(processor.tokenizer.get_vocab()    ,					tokenizer_add_kwargs.get_vocab()						)
					self.assertIsInstance(processor.tokenizer    ,					_SCREAMING_SNAKE_CASE						)

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





	def  _lowerCAmelCase    (			self							:					List[Any]						)	->  Tuple:





					"""simple docstring"""


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

					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    FlavaProcessor(tokenizer=_SCREAMING_SNAKE_CASE    ,					image_processor=_SCREAMING_SNAKE_CASE						)

					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    self.prepare_image_inputs()

					SCREAMING_SNAKE_CASE	:       Any 							=    image_processor(_SCREAMING_SNAKE_CASE    ,					return_tensors='np'						)
					SCREAMING_SNAKE_CASE	:       str 							=    processor(images=_SCREAMING_SNAKE_CASE    ,					return_tensors='np'						)

					for key in input_feat_extract.keys():
									self.assertAlmostEqual(input_feat_extract[key].sum()    ,					input_processor[key].sum()    ,					delta=1E-2						)

					# With rest of the args
					random.seed(1_234						)
					SCREAMING_SNAKE_CASE	:       str 							=    image_processor(
					    _SCREAMING_SNAKE_CASE    ,					return_image_mask=_SCREAMING_SNAKE_CASE    ,					return_codebook_pixels=_SCREAMING_SNAKE_CASE    ,					return_tensors='np'						)
					random.seed(1_234						)
					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    processor(
					    images=_SCREAMING_SNAKE_CASE    ,					return_image_mask=_SCREAMING_SNAKE_CASE    ,					return_codebook_pixels=_SCREAMING_SNAKE_CASE    ,					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							:					Any						)	->  Optional[int]:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       Dict 							=    self.get_image_processor()
					SCREAMING_SNAKE_CASE	:       Optional[Any] 							=    self.get_tokenizer()

					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    FlavaProcessor(tokenizer=_SCREAMING_SNAKE_CASE    ,					image_processor=_SCREAMING_SNAKE_CASE						)

					SCREAMING_SNAKE_CASE	:       List[Any] 							=    'lower newer'

					SCREAMING_SNAKE_CASE	:       List[str] 							=    processor(text=_SCREAMING_SNAKE_CASE						)

					SCREAMING_SNAKE_CASE	:       List[str] 							=    tokenizer(_SCREAMING_SNAKE_CASE						)

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





	def  _lowerCAmelCase    (			self							:					Tuple						)	->  int:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    self.get_image_processor()
					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    self.get_tokenizer()

					SCREAMING_SNAKE_CASE	:       str 							=    FlavaProcessor(tokenizer=_SCREAMING_SNAKE_CASE    ,					image_processor=_SCREAMING_SNAKE_CASE						)

					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    'lower newer'
					SCREAMING_SNAKE_CASE	:       List[str] 							=    self.prepare_image_inputs()

					SCREAMING_SNAKE_CASE	:       List[str] 							=    processor(text=_SCREAMING_SNAKE_CASE    ,					images=_SCREAMING_SNAKE_CASE						)

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

					# add extra args
					SCREAMING_SNAKE_CASE	:       Any 							=    processor(text=_SCREAMING_SNAKE_CASE    ,					images=_SCREAMING_SNAKE_CASE    ,					return_codebook_pixels=_SCREAMING_SNAKE_CASE    ,					return_image_mask=_SCREAMING_SNAKE_CASE						)

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

					# test if it raises when no input is passed
					with pytest.raises(_SCREAMING_SNAKE_CASE						):
									processor()





	def  _lowerCAmelCase    (			self							:					Optional[Any]						)	->  Union[str, Any]:





					"""simple docstring"""


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

					SCREAMING_SNAKE_CASE	:       Union[str, Any] 							=    FlavaProcessor(tokenizer=_SCREAMING_SNAKE_CASE    ,					image_processor=_SCREAMING_SNAKE_CASE						)

					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

					SCREAMING_SNAKE_CASE	:       Optional[Any] 							=    processor.batch_decode(_SCREAMING_SNAKE_CASE						)
					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    tokenizer.batch_decode(_SCREAMING_SNAKE_CASE						)

					self.assertListEqual(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE						)







	def  _lowerCAmelCase    (			self							:					int						)	->  Any:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       Union[str, Any] 							=    self.get_image_processor()
					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    self.get_tokenizer()

					SCREAMING_SNAKE_CASE	:       int 							=    FlavaProcessor(tokenizer=_SCREAMING_SNAKE_CASE    ,					image_processor=_SCREAMING_SNAKE_CASE						)

					SCREAMING_SNAKE_CASE	:       Any 							=    'lower newer'
					SCREAMING_SNAKE_CASE	:       List[Any] 							=    self.prepare_image_inputs()

					SCREAMING_SNAKE_CASE	:       Dict 							=    processor(text=_SCREAMING_SNAKE_CASE    ,					images=_SCREAMING_SNAKE_CASE						)

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





