
"""simple docstring"""

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,
					    BertTokenizerFast,
					    BlipImageProcessor,
					    GPTaTokenizer,
					    InstructBlipProcessor,
					    PreTrainedTokenizerFast,
					)






@require_vision
class 	_lowercase       (    unittest.TestCase		):




	def       _UpperCamelCase   (			self )		->							Union[str, Any]:
			lowerCamelCase					:      Dict          =   tempfile.mkdtemp()

			lowerCamelCase					:      int          =   BlipImageProcessor()
			lowerCamelCase					:      Optional[int]          =   GPTaTokenizer.from_pretrained('hf-internal-testing/tiny-random-GPT2Model' )
			lowerCamelCase					:      List[Any]          =   BertTokenizerFast.from_pretrained('hf-internal-testing/tiny-random-bert' )

			lowerCamelCase					:      Tuple          =   InstructBlipProcessor(UpperCAmelCase_		,			UpperCAmelCase_		,			UpperCAmelCase_ )

			processor.save_pretrained(self.tmpdirname )




	def       _UpperCamelCase   (			self		,			**UpperCAmelCase_ )		->							str:
			return AutoProcessor.from_pretrained(self.tmpdirname		,			**UpperCAmelCase_ ).tokenizer




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




	def       _UpperCamelCase   (			self		,			**UpperCAmelCase_ )		->							Any:
			return AutoProcessor.from_pretrained(self.tmpdirname		,			**UpperCAmelCase_ ).qformer_tokenizer




	def       _UpperCamelCase   (			self )		->							Dict:
			shutil.rmtree(self.tmpdirname )




	def       _UpperCamelCase   (			self )		->							List[Any]:
			lowerCamelCase					:      Dict          =   [np.random.randint(255		,			size=(3, 30, 400)		,			dtype=np.uinta )]

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

			return image_inputs




	def       _UpperCamelCase   (			self )		->							List[str]:
			lowerCamelCase					:      str          =   InstructBlipProcessor(
			    tokenizer=self.get_tokenizer()		,			image_processor=self.get_image_processor()		,			qformer_tokenizer=self.get_qformer_tokenizer()		,			)
			processor.save_pretrained(self.tmpdirname )

			lowerCamelCase					:      Optional[Any]          =   self.get_tokenizer(bos_token='(BOS)'		,			eos_token='(EOS)' )
			lowerCamelCase					:      List[str]          =   self.get_image_processor(do_normalize=UpperCAmelCase_		,			padding_value=1.0 )

			lowerCamelCase					:      Tuple          =   InstructBlipProcessor.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_ )
			self.assertIsInstance(processor.qformer_tokenizer		,			UpperCAmelCase_ )




	def       _UpperCamelCase   (			self )		->							Union[str, Any]:
			lowerCamelCase					:      List[Any]          =   self.get_image_processor()
			lowerCamelCase					:      Dict          =   self.get_tokenizer()
			lowerCamelCase					:      Optional[int]          =   self.get_qformer_tokenizer()

			lowerCamelCase					:      int          =   InstructBlipProcessor(
			    tokenizer=UpperCAmelCase_		,			image_processor=UpperCAmelCase_		,			qformer_tokenizer=UpperCAmelCase_ )

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

			lowerCamelCase					:      Optional[Any]          =   image_processor(UpperCAmelCase_		,			return_tensors='np' )
			lowerCamelCase					:      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       _UpperCamelCase   (			self )		->							int:
			lowerCamelCase					:      Any          =   self.get_image_processor()
			lowerCamelCase					:      Dict          =   self.get_tokenizer()
			lowerCamelCase					:      str          =   self.get_qformer_tokenizer()

			lowerCamelCase					:      Optional[Any]          =   InstructBlipProcessor(
			    tokenizer=UpperCAmelCase_		,			image_processor=UpperCAmelCase_		,			qformer_tokenizer=UpperCAmelCase_ )

			lowerCamelCase					:      List[Any]          =   'lower newer'

			lowerCamelCase					:      Optional[int]          =   processor(text=UpperCAmelCase_ )

			lowerCamelCase					:      str          =   tokenizer(UpperCAmelCase_		,			return_token_type_ids=UpperCAmelCase_ )
			lowerCamelCase					:      Dict          =   qformer_tokenizer(UpperCAmelCase_		,			return_token_type_ids=UpperCAmelCase_ )

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

			for key in encoded_tokens_qformer.keys():
					self.assertListEqual(encoded_tokens_qformer[key]		,			encoded_processor['qformer_' + key] )




	def       _UpperCamelCase   (			self )		->							int:
			lowerCamelCase					:      Tuple          =   self.get_image_processor()
			lowerCamelCase					:      Optional[int]          =   self.get_tokenizer()
			lowerCamelCase					:      int          =   self.get_qformer_tokenizer()

			lowerCamelCase					:      List[str]          =   InstructBlipProcessor(
			    tokenizer=UpperCAmelCase_		,			image_processor=UpperCAmelCase_		,			qformer_tokenizer=UpperCAmelCase_ )

			lowerCamelCase					:      Union[str, Any]          =   'lower newer'
			lowerCamelCase					:      List[Any]          =   self.prepare_image_inputs()

			lowerCamelCase					:      str          =   processor(text=UpperCAmelCase_		,			images=UpperCAmelCase_ )

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

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




	def       _UpperCamelCase   (			self )		->							Any:
			lowerCamelCase					:      Any          =   self.get_image_processor()
			lowerCamelCase					:      Tuple          =   self.get_tokenizer()
			lowerCamelCase					:      Optional[Any]          =   self.get_qformer_tokenizer()

			lowerCamelCase					:      List[str]          =   InstructBlipProcessor(
			    tokenizer=UpperCAmelCase_		,			image_processor=UpperCAmelCase_		,			qformer_tokenizer=UpperCAmelCase_ )

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

			lowerCamelCase					:      Union[str, Any]          =   processor.batch_decode(UpperCAmelCase_ )
			lowerCamelCase					:      Dict          =   tokenizer.batch_decode(UpperCAmelCase_ )

			self.assertListEqual(UpperCAmelCase_		,			UpperCAmelCase_ )




	def       _UpperCamelCase   (			self )		->							List[str]:
			lowerCamelCase					:      int          =   self.get_image_processor()
			lowerCamelCase					:      Any          =   self.get_tokenizer()
			lowerCamelCase					:      Optional[int]          =   self.get_qformer_tokenizer()

			lowerCamelCase					:      Union[str, Any]          =   InstructBlipProcessor(
			    tokenizer=UpperCAmelCase_		,			image_processor=UpperCAmelCase_		,			qformer_tokenizer=UpperCAmelCase_ )

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

			lowerCamelCase					:      List[Any]          =   processor(text=UpperCAmelCase_		,			images=UpperCAmelCase_ )

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








"""simple docstring"""

def 		UpperCAmelCase (		a_      ):





		'''simple docstring'''


		lowerCamelCase					:      List[Any]          =   1
		for i in range(1,						num + 1      ):
				fact *= i
		return fact
def 		UpperCAmelCase (		a_      ):





		'''simple docstring'''


		lowerCamelCase					:      Optional[Any]          =   0
		while number > 0:
				lowerCamelCase					:      str          =   number % 10
				sum_of_digits += last_digit
				lowerCamelCase					:      Tuple          =   number // 10  # Removing the last_digit from the given number
		return sum_of_digits
def 		UpperCAmelCase (		a_ = 100      ):





		'''simple docstring'''


		lowerCamelCase					:      Optional[Any]          =   factorial(a_      )
		lowerCamelCase					:      int          =   split_and_add(a_      )
		return result


if __name__ == "__main__":
					print(solution(int(input('Enter the Number: ').strip())))






