






import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
	from PIL import Image

	from transformers import AutoProcessor, BertTokenizer, BlipImageProcessor, BlipProcessor, PreTrainedTokenizerFast


@require_vision
class 					_snake_case						(			unittest.TestCase ):






	def    lowerCAmelCase_							(		self       )						->    List[Any]:
					snake_case__      :str         =   tempfile.mkdtemp()

					snake_case__      :Dict         =   BlipImageProcessor()
					snake_case__      :Optional[Any]         =   BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertModel"       )

					snake_case__      :Optional[Any]         =   BlipProcessor(UpperCamelCase					,UpperCamelCase       )

					processor.save_pretrained(self.tmpdirname       )






	def    lowerCAmelCase_							(		self					,**UpperCamelCase       )						->    Tuple:
					return AutoProcessor.from_pretrained(self.tmpdirname					,**UpperCamelCase       ).tokenizer






	def    lowerCAmelCase_							(		self					,**UpperCamelCase       )						->    Optional[int]:
					return AutoProcessor.from_pretrained(self.tmpdirname					,**UpperCamelCase       ).image_processor






	def    lowerCAmelCase_							(		self       )						->    List[Any]:
					shutil.rmtree(self.tmpdirname       )






	def    lowerCAmelCase_							(		self       )						->    int:
					snake_case__      :Optional[int]         =   [np.random.randint(255					,size=(3, 30, 400)					,dtype=np.uinta       )]

					snake_case__      :Union[str, Any]         =   [Image.fromarray(np.moveaxis(UpperCamelCase					,0					,-1       )       ) for x in image_inputs]

					return image_inputs






	def    lowerCAmelCase_							(		self       )						->    List[str]:
					snake_case__      :Optional[Any]         =   BlipProcessor(tokenizer=self.get_tokenizer()					,image_processor=self.get_image_processor()       )
					processor.save_pretrained(self.tmpdirname       )

					snake_case__      :str         =   self.get_tokenizer(bos_token="(BOS)"					,eos_token="(EOS)"       )
					snake_case__      :str         =   self.get_image_processor(do_normalize=UpperCamelCase					,padding_value=1.0       )

					snake_case__      :List[Any]         =   BlipProcessor.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					,UpperCamelCase       )

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






	def    lowerCAmelCase_							(		self       )						->    Optional[Any]:
					snake_case__      :Union[str, Any]         =   self.get_image_processor()
					snake_case__      :Optional[int]         =   self.get_tokenizer()

					snake_case__      :List[str]         =   BlipProcessor(tokenizer=UpperCamelCase					,image_processor=UpperCamelCase       )

					snake_case__      :int         =   self.prepare_image_inputs()

					snake_case__      :Any         =   image_processor(UpperCamelCase					,return_tensors="np"       )
					snake_case__      :str         =   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       )						->    str:
					snake_case__      :Union[str, Any]         =   self.get_image_processor()
					snake_case__      :List[str]         =   self.get_tokenizer()

					snake_case__      :str         =   BlipProcessor(tokenizer=UpperCamelCase					,image_processor=UpperCamelCase       )

					snake_case__      :int         =   "lower newer"

					snake_case__      :Dict         =   processor(text=UpperCamelCase       )

					snake_case__      :Dict         =   tokenizer(UpperCamelCase					,return_token_type_ids=UpperCamelCase       )

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






	def    lowerCAmelCase_							(		self       )						->    str:
					snake_case__      :Optional[int]         =   self.get_image_processor()
					snake_case__      :Optional[Any]         =   self.get_tokenizer()

					snake_case__      :str         =   BlipProcessor(tokenizer=UpperCamelCase					,image_processor=UpperCamelCase       )

					snake_case__      :Optional[Any]         =   "lower newer"
					snake_case__      :List[Any]         =   self.prepare_image_inputs()

					snake_case__      :str         =   processor(text=UpperCamelCase					,images=UpperCamelCase       )

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

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






	def    lowerCAmelCase_							(		self       )						->    Tuple:
					snake_case__      :Optional[int]         =   self.get_image_processor()
					snake_case__      :Dict         =   self.get_tokenizer()

					snake_case__      :Optional[int]         =   BlipProcessor(tokenizer=UpperCamelCase					,image_processor=UpperCamelCase       )

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

					snake_case__      :str         =   processor.batch_decode(UpperCamelCase       )
					snake_case__      :Optional[Any]         =   tokenizer.batch_decode(UpperCamelCase       )

					self.assertListEqual(UpperCamelCase					,UpperCamelCase       )






	def    lowerCAmelCase_							(		self       )						->    Dict:
					snake_case__      :Union[str, Any]         =   self.get_image_processor()
					snake_case__      :str         =   self.get_tokenizer()

					snake_case__      :int         =   BlipProcessor(tokenizer=UpperCamelCase					,image_processor=UpperCamelCase       )

					snake_case__      :Optional[Any]         =   "lower newer"
					snake_case__      :List[str]         =   self.prepare_image_inputs()

					snake_case__      :Any         =   processor(text=UpperCamelCase					,images=UpperCamelCase       )

					# For now the processor supports only ['pixel_values', 'input_ids', 'attention_mask']
					self.assertListEqual(list(inputs.keys()       )					,["pixel_values", "input_ids", "attention_mask"]       )







from __future__ import annotations


class 					_snake_case						:






	def __init__(		self					,UpperCamelCase       )						->    None:
					snake_case__      :Union[str, Any]         =   data
					snake_case__      :Node | None         =   None
					snake_case__      :Node | None         =   None





def 					lowercase_ (    __snake_case     :							Node | None      )     -> None:  # In Order traversal of the tree





				'''simple docstring'''


				if tree:
								display(tree.left      )
								print(tree.data      )
								display(tree.right      )





def 					lowercase_ (    __snake_case     :							Node | None      )     -> int:





				'''simple docstring'''


				return 1 + max(depth_of_tree(tree.left      )	,	depth_of_tree(tree.right      )      ) if tree else 0





def 					lowercase_ (    __snake_case     :							Node      )     -> bool:





				'''simple docstring'''


				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 					lowercase_ (    )     -> None:  # Main function for testing.





				'''simple docstring'''


				snake_case__      :Dict         =   Node(1      )
				snake_case__      :int         =   Node(2      )
				snake_case__      :Optional[Any]         =   Node(3      )
				snake_case__      :Tuple         =   Node(4      )
				snake_case__      :str         =   Node(5      )
				snake_case__      :Optional[Any]         =   Node(6      )
				snake_case__      :List[Any]         =   Node(7      )
				snake_case__      :List[str]         =   Node(8      )
				snake_case__      :Tuple         =   Node(9      )

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


if __name__ == "__main__":
	main()