



"""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 							lowerCamelCase_(   unittest.TestCase    ):





     '''simple docstring'''



     def 			snake_case__      (    self   ):
         _lowerCamelCase        =				tempfile.mkdtemp()

         _lowerCamelCase        =				BlipImageProcessor()
         _lowerCamelCase        =				GPTaTokenizer.from_pretrained('''hf-internal-testing/tiny-random-GPT2Model'''   )
         _lowerCamelCase        =				BertTokenizerFast.from_pretrained('''hf-internal-testing/tiny-random-bert'''   )

         _lowerCamelCase        =				InstructBlipProcessor(UpperCamelCase__				,       UpperCamelCase__				,       UpperCamelCase__   )

         processor.save_pretrained(self.tmpdirname   )

     def 			snake_case__      (    self				,       **lowerCamelCase__   ):
         return AutoProcessor.from_pretrained(self.tmpdirname				,       **UpperCamelCase__   ).tokenizer

     def 			snake_case__      (    self				,       **lowerCamelCase__   ):
         return AutoProcessor.from_pretrained(self.tmpdirname				,       **UpperCamelCase__   ).image_processor

     def 			snake_case__      (    self				,       **lowerCamelCase__   ):
         return AutoProcessor.from_pretrained(self.tmpdirname				,       **UpperCamelCase__   ).qformer_tokenizer

     def 			snake_case__      (    self   ):
         shutil.rmtree(self.tmpdirname   )

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

         _lowerCamelCase        =				[Image.fromarray(np.moveaxis(UpperCamelCase__				,       0				,       -1   )   ) for x in image_inputs]

         return image_inputs

     def 			snake_case__      (    self   ):
         _lowerCamelCase        =				InstructBlipProcessor(
             tokenizer=self.get_tokenizer()				,       image_processor=self.get_image_processor()				,       qformer_tokenizer=self.get_qformer_tokenizer()				,       )
         processor.save_pretrained(self.tmpdirname   )

         _lowerCamelCase        =				self.get_tokenizer(bos_token='''(BOS)'''				,       eos_token='''(EOS)'''   )
         _lowerCamelCase        =				self.get_image_processor(do_normalize=UpperCamelCase__				,       padding_value=1.0   )

         _lowerCamelCase        =				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 			snake_case__      (    self   ):
         _lowerCamelCase        =				self.get_image_processor()
         _lowerCamelCase        =				self.get_tokenizer()
         _lowerCamelCase        =				self.get_qformer_tokenizer()

         _lowerCamelCase        =				InstructBlipProcessor(
             tokenizer=UpperCamelCase__				,       image_processor=UpperCamelCase__				,       qformer_tokenizer=UpperCamelCase__   )

         _lowerCamelCase        =				self.prepare_image_inputs()

         _lowerCamelCase        =				image_processor(UpperCamelCase__				,       return_tensors='''np'''   )
         _lowerCamelCase        =				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 			snake_case__      (    self   ):
         _lowerCamelCase        =				self.get_image_processor()
         _lowerCamelCase        =				self.get_tokenizer()
         _lowerCamelCase        =				self.get_qformer_tokenizer()

         _lowerCamelCase        =				InstructBlipProcessor(
             tokenizer=UpperCamelCase__				,       image_processor=UpperCamelCase__				,       qformer_tokenizer=UpperCamelCase__   )

         _lowerCamelCase        =				'''lower newer'''

         _lowerCamelCase        =				processor(text=UpperCamelCase__   )

         _lowerCamelCase        =				tokenizer(UpperCamelCase__				,       return_token_type_ids=UpperCamelCase__   )
         _lowerCamelCase        =				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 			snake_case__      (    self   ):
         _lowerCamelCase        =				self.get_image_processor()
         _lowerCamelCase        =				self.get_tokenizer()
         _lowerCamelCase        =				self.get_qformer_tokenizer()

         _lowerCamelCase        =				InstructBlipProcessor(
             tokenizer=UpperCamelCase__				,       image_processor=UpperCamelCase__				,       qformer_tokenizer=UpperCamelCase__   )

         _lowerCamelCase        =				'''lower newer'''
         _lowerCamelCase        =				self.prepare_image_inputs()

         _lowerCamelCase        =				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 			snake_case__      (    self   ):
         _lowerCamelCase        =				self.get_image_processor()
         _lowerCamelCase        =				self.get_tokenizer()
         _lowerCamelCase        =				self.get_qformer_tokenizer()

         _lowerCamelCase        =				InstructBlipProcessor(
             tokenizer=UpperCamelCase__				,       image_processor=UpperCamelCase__				,       qformer_tokenizer=UpperCamelCase__   )

         _lowerCamelCase        =				[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         _lowerCamelCase        =				processor.batch_decode(UpperCamelCase__   )
         _lowerCamelCase        =				tokenizer.batch_decode(UpperCamelCase__   )

         self.assertListEqual(UpperCamelCase__				,       UpperCamelCase__   )





     def 			snake_case__      (    self   ):
         _lowerCamelCase        =				self.get_image_processor()
         _lowerCamelCase        =				self.get_tokenizer()
         _lowerCamelCase        =				self.get_qformer_tokenizer()

         _lowerCamelCase        =				InstructBlipProcessor(
             tokenizer=UpperCamelCase__				,       image_processor=UpperCamelCase__				,       qformer_tokenizer=UpperCamelCase__   )

         _lowerCamelCase        =				'''lower newer'''
         _lowerCamelCase        =				self.prepare_image_inputs()

         _lowerCamelCase        =				processor(text=UpperCamelCase__				,       images=UpperCamelCase__   )

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





"""simple docstring"""
import numpy as np



def        lowerCAmelCase_(   lowercase_     :							np.array							)	->       np.array:
				return 1 / (1 + np.exp(-vector							))



def        lowerCAmelCase_(   lowercase_     :							np.array							)	->       np.array:
				return vector * sigmoid(1.7_0_2 * vector							)


if __name__ == "__main__":
			import doctest

			doctest.testmod()
