



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       a							(			unittest.TestCase				):



		def 	__lowerCamelCase			(     self     :Optional[Any]  ):
						snake_case__	:      Any     		=	tempfile.mkdtemp()

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

						snake_case__	:      Union[str, Any]     		=	InstructBlipProcessor(__lowercase   ,__lowercase   ,__lowercase  )

						processor.save_pretrained(self.tmpdirname  )



		def 	__lowerCamelCase			(     self     :List[Any]   ,**__lowercase     :Union[str, Any]  ):
						return AutoProcessor.from_pretrained(self.tmpdirname   ,**__lowercase  ).tokenizer



		def 	__lowerCamelCase			(     self     :List[Any]   ,**__lowercase     :Optional[int]  ):
						return AutoProcessor.from_pretrained(self.tmpdirname   ,**__lowercase  ).image_processor



		def 	__lowerCamelCase			(     self     :Optional[Any]   ,**__lowercase     :Optional[int]  ):
						return AutoProcessor.from_pretrained(self.tmpdirname   ,**__lowercase  ).qformer_tokenizer



		def 	__lowerCamelCase			(     self     :Optional[int]  ):
						shutil.rmtree(self.tmpdirname  )



		def 	__lowerCamelCase			(     self     :Tuple  ):
						snake_case__	:      Tuple     		=	[np.random.randint(2_5_5   ,size=(3, 3_0, 4_0_0)   ,dtype=np.uinta  )]

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

						return image_inputs



		def 	__lowerCamelCase			(     self     :Tuple  ):
						snake_case__	:      Optional[Any]     		=	InstructBlipProcessor(
						    tokenizer=self.get_tokenizer()   ,image_processor=self.get_image_processor()   ,qformer_tokenizer=self.get_qformer_tokenizer()   ,)
						processor.save_pretrained(self.tmpdirname  )

						snake_case__	:      int     		=	self.get_tokenizer(bos_token='''(BOS)'''   ,eos_token='''(EOS)'''  )
						snake_case__	:      Dict     		=	self.get_image_processor(do_normalize=__lowercase   ,padding_value=1.0  )

						snake_case__	:      Dict     		=	InstructBlipProcessor.from_pretrained(
						    self.tmpdirname   ,bos_token='''(BOS)'''   ,eos_token='''(EOS)'''   ,do_normalize=__lowercase   ,padding_value=1.0  )

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

						self.assertEqual(processor.image_processor.to_json_string()   ,image_processor_add_kwargs.to_json_string()  )
						self.assertIsInstance(processor.image_processor   ,__lowercase  )
						self.assertIsInstance(processor.qformer_tokenizer   ,__lowercase  )



		def 	__lowerCamelCase			(     self     :Dict  ):
						snake_case__	:      List[str]     		=	self.get_image_processor()
						snake_case__	:      Tuple     		=	self.get_tokenizer()
						snake_case__	:      Dict     		=	self.get_qformer_tokenizer()

						snake_case__	:      Any     		=	InstructBlipProcessor(
						    tokenizer=__lowercase   ,image_processor=__lowercase   ,qformer_tokenizer=__lowercase  )

						snake_case__	:      Dict     		=	self.prepare_image_inputs()

						snake_case__	:      int     		=	image_processor(__lowercase   ,return_tensors='''np'''  )
						snake_case__	:      Optional[int]     		=	processor(images=__lowercase   ,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     :Union[str, Any]  ):
						snake_case__	:      Optional[Any]     		=	self.get_image_processor()
						snake_case__	:      Tuple     		=	self.get_tokenizer()
						snake_case__	:      str     		=	self.get_qformer_tokenizer()

						snake_case__	:      Optional[int]     		=	InstructBlipProcessor(
						    tokenizer=__lowercase   ,image_processor=__lowercase   ,qformer_tokenizer=__lowercase  )

						snake_case__	:      List[Any]     		=	'''lower newer'''

						snake_case__	:      Tuple     		=	processor(text=__lowercase  )

						snake_case__	:      Optional[Any]     		=	tokenizer(__lowercase   ,return_token_type_ids=__lowercase  )
						snake_case__	:      str     		=	qformer_tokenizer(__lowercase   ,return_token_type_ids=__lowercase  )

						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 	__lowerCamelCase			(     self     :List[str]  ):
						snake_case__	:      Union[str, Any]     		=	self.get_image_processor()
						snake_case__	:      List[Any]     		=	self.get_tokenizer()
						snake_case__	:      Optional[int]     		=	self.get_qformer_tokenizer()

						snake_case__	:      Tuple     		=	InstructBlipProcessor(
						    tokenizer=__lowercase   ,image_processor=__lowercase   ,qformer_tokenizer=__lowercase  )

						snake_case__	:      str     		=	'''lower newer'''
						snake_case__	:      Tuple     		=	self.prepare_image_inputs()

						snake_case__	:      int     		=	processor(text=__lowercase   ,images=__lowercase  )

						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(__lowercase  ):
										processor()



		def 	__lowerCamelCase			(     self     :Union[str, Any]  ):
						snake_case__	:      List[str]     		=	self.get_image_processor()
						snake_case__	:      List[str]     		=	self.get_tokenizer()
						snake_case__	:      Tuple     		=	self.get_qformer_tokenizer()

						snake_case__	:      Dict     		=	InstructBlipProcessor(
						    tokenizer=__lowercase   ,image_processor=__lowercase   ,qformer_tokenizer=__lowercase  )

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

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

						self.assertListEqual(__lowercase   ,__lowercase  )






		def 	__lowerCamelCase			(     self     :Optional[int]  ):
						snake_case__	:      Optional[Any]     		=	self.get_image_processor()
						snake_case__	:      str     		=	self.get_tokenizer()
						snake_case__	:      int     		=	self.get_qformer_tokenizer()

						snake_case__	:      List[str]     		=	InstructBlipProcessor(
						    tokenizer=__lowercase   ,image_processor=__lowercase   ,qformer_tokenizer=__lowercase  )

						snake_case__	:      int     		=	'''lower newer'''
						snake_case__	:      str     		=	self.prepare_image_inputs()

						snake_case__	:      List[str]     		=	processor(text=__lowercase   ,images=__lowercase  )

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






def 			_lowerCAmelCase       (					__lowerCAmelCase  ,  __lowerCAmelCase      )   ->					int:


				"""simple docstring"""

				return int((input_a, input_a).count(1      ) != 0      )



def 			_lowerCAmelCase       (					)   ->					None:


				"""simple docstring"""

				assert or_gate(0  ,  0      ) == 0
				assert or_gate(0  ,  1      ) == 1
				assert or_gate(1  ,  0      ) == 1
				assert or_gate(1  ,  1      ) == 1


if __name__ == "__main__":
				print(or_gate(0, 1))
				print(or_gate(1, 0))
				print(or_gate(0, 0))
				print(or_gate(1, 1))

