





"""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 							snake_case							(			unittest.TestCase ):

      '''simple docstring'''



      def       A_					(							self       :      List[Any] ):


        '''simple docstring'''




        __UpperCAmelCase    :						Optional[Any]       =						tempfile.mkdtemp()

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

        __UpperCAmelCase    :						Optional[int]       =						InstructBlipProcessor(__lowercase						,				__lowercase						,				__lowercase )

        processor.save_pretrained(self.tmpdirname )

      def       A_					(							self       :      Dict						,				**__lowercase       :      List[Any] ):


        '''simple docstring'''




        return AutoProcessor.from_pretrained(self.tmpdirname						,				**__lowercase ).tokenizer

      def       A_					(							self       :      Tuple						,				**__lowercase       :      Optional[int] ):


        '''simple docstring'''




        return AutoProcessor.from_pretrained(self.tmpdirname						,				**__lowercase ).image_processor

      def       A_					(							self       :      Tuple						,				**__lowercase       :      int ):


        '''simple docstring'''




        return AutoProcessor.from_pretrained(self.tmpdirname						,				**__lowercase ).qformer_tokenizer

      def       A_					(							self       :      str ):


        '''simple docstring'''




        shutil.rmtree(self.tmpdirname )

      def       A_					(							self       :      List[str] ):


        '''simple docstring'''




        __UpperCAmelCase    :						List[Any]       =						[np.random.randint(255						,				size=(3, 30, 400)						,				dtype=np.uinta )]

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

        return image_inputs

      def       A_					(							self       :      Tuple ):


        '''simple docstring'''




        __UpperCAmelCase    :						int       =						InstructBlipProcessor(
            tokenizer=self.get_tokenizer()						,				image_processor=self.get_image_processor()						,				qformer_tokenizer=self.get_qformer_tokenizer()						,				)
        processor.save_pretrained(self.tmpdirname )

        __UpperCAmelCase    :						Dict       =						self.get_tokenizer(bos_token='''(BOS)'''						,				eos_token='''(EOS)''' )
        __UpperCAmelCase    :						List[Any]       =						self.get_image_processor(do_normalize=__lowercase						,				padding_value=1.0 )

        __UpperCAmelCase    :						int       =						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       A_					(							self       :      Optional[Any] ):


        '''simple docstring'''




        __UpperCAmelCase    :						Union[str, Any]       =						self.get_image_processor()
        __UpperCAmelCase    :						List[Any]       =						self.get_tokenizer()
        __UpperCAmelCase    :						Any       =						self.get_qformer_tokenizer()

        __UpperCAmelCase    :						List[Any]       =						InstructBlipProcessor(
            tokenizer=__lowercase						,				image_processor=__lowercase						,				qformer_tokenizer=__lowercase )

        __UpperCAmelCase    :						List[str]       =						self.prepare_image_inputs()

        __UpperCAmelCase    :						Any       =						image_processor(__lowercase						,				return_tensors='''np''' )
        __UpperCAmelCase    :						Optional[Any]       =						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       A_					(							self       :      List[Any] ):


        '''simple docstring'''




        __UpperCAmelCase    :						Optional[int]       =						self.get_image_processor()
        __UpperCAmelCase    :						int       =						self.get_tokenizer()
        __UpperCAmelCase    :						Dict       =						self.get_qformer_tokenizer()

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

        __UpperCAmelCase    :						Tuple       =						'''lower newer'''

        __UpperCAmelCase    :						Optional[Any]       =						processor(text=__lowercase )

        __UpperCAmelCase    :						int       =						tokenizer(__lowercase						,				return_token_type_ids=__lowercase )
        __UpperCAmelCase    :						int       =						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       A_					(							self       :      List[Any] ):


        '''simple docstring'''




        __UpperCAmelCase    :						int       =						self.get_image_processor()
        __UpperCAmelCase    :						List[Any]       =						self.get_tokenizer()
        __UpperCAmelCase    :						Optional[Any]       =						self.get_qformer_tokenizer()

        __UpperCAmelCase    :						Union[str, Any]       =						InstructBlipProcessor(
            tokenizer=__lowercase						,				image_processor=__lowercase						,				qformer_tokenizer=__lowercase )

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

        __UpperCAmelCase    :						Union[str, Any]       =						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       A_					(							self       :      List[Any] ):


        '''simple docstring'''




        __UpperCAmelCase    :						int       =						self.get_image_processor()
        __UpperCAmelCase    :						Any       =						self.get_tokenizer()
        __UpperCAmelCase    :						Any       =						self.get_qformer_tokenizer()

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

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

        __UpperCAmelCase    :						List[str]       =						processor.batch_decode(__lowercase )
        __UpperCAmelCase    :						Optional[int]       =						tokenizer.batch_decode(__lowercase )

        self.assertListEqual(__lowercase						,				__lowercase )







      def       A_					(							self       :      str ):


        '''simple docstring'''




        __UpperCAmelCase    :						int       =						self.get_image_processor()
        __UpperCAmelCase    :						Any       =						self.get_tokenizer()
        __UpperCAmelCase    :						Optional[int]       =						self.get_qformer_tokenizer()

        __UpperCAmelCase    :						List[Any]       =						InstructBlipProcessor(
            tokenizer=__lowercase						,				image_processor=__lowercase						,				qformer_tokenizer=__lowercase )

        __UpperCAmelCase    :						Dict       =						'''lower newer'''
        __UpperCAmelCase    :						Any       =						self.prepare_image_inputs()

        __UpperCAmelCase    :						List[Any]       =						processor(text=__lowercase						,				images=__lowercase )

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






"""simple docstring"""





def       lowerCamelCase_       (   UpperCAmelCase_ = 10_00  )						->int:





  """simple docstring"""


  return sum(2 * a * ((a - 1) // 2) for a in range(3  ,			n + 1  )  )


if __name__ == "__main__":
  print(solution())