"""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     UpperCAmelCase						(unittest.TestCase  ):



    """simple docstring"""

    def _snake_case			(   self							):
       lowercase__:   int					=      tempfile.mkdtemp()

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

       lowercase__:   List[Any]					=      InstructBlipProcessor(_UpperCAmelCase    ,			_UpperCAmelCase    ,			_UpperCAmelCase							)

       processor.save_pretrained(self.tmpdirname							)






    def _snake_case			(   self    ,			**_UpperCAmelCase							):
       return AutoProcessor.from_pretrained(self.tmpdirname    ,			**_UpperCAmelCase							).tokenizer






    def _snake_case			(   self    ,			**_UpperCAmelCase							):
       return AutoProcessor.from_pretrained(self.tmpdirname    ,			**_UpperCAmelCase							).image_processor






    def _snake_case			(   self    ,			**_UpperCAmelCase							):
       return AutoProcessor.from_pretrained(self.tmpdirname    ,			**_UpperCAmelCase							).qformer_tokenizer






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






    def _snake_case			(   self							):
       lowercase__:   Optional[Any]					=      [np.random.randint(255    ,			size=(3, 30, 400)    ,			dtype=np.uinta							)]

       lowercase__:   Tuple					=      [Image.fromarray(np.moveaxis(_UpperCAmelCase    ,			0    ,			-1							)							) for x in image_inputs]

       return image_inputs






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

       lowercase__:   Tuple					=      self.get_tokenizer(bos_token='''(BOS)'''    ,			eos_token='''(EOS)'''							)
       lowercase__:   Tuple					=      self.get_image_processor(do_normalize=_UpperCAmelCase    ,			padding_value=1.0							)

       lowercase__:   int					=      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							):
       lowercase__:   List[str]					=      self.get_image_processor()
       lowercase__:   str					=      self.get_tokenizer()
       lowercase__:   Optional[int]					=      self.get_qformer_tokenizer()

       lowercase__:   Optional[int]					=      InstructBlipProcessor(
           tokenizer=_UpperCAmelCase    ,			image_processor=_UpperCAmelCase    ,			qformer_tokenizer=_UpperCAmelCase							)

       lowercase__:   Union[str, Any]					=      self.prepare_image_inputs()

       lowercase__:   Any					=      image_processor(_UpperCAmelCase    ,			return_tensors='''np'''							)
       lowercase__:   Tuple					=      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							):
       lowercase__:   Optional[int]					=      self.get_image_processor()
       lowercase__:   Tuple					=      self.get_tokenizer()
       lowercase__:   Optional[Any]					=      self.get_qformer_tokenizer()

       lowercase__:   Union[str, Any]					=      InstructBlipProcessor(
           tokenizer=_UpperCAmelCase    ,			image_processor=_UpperCAmelCase    ,			qformer_tokenizer=_UpperCAmelCase							)

       lowercase__:   Optional[Any]					=      '''lower newer'''

       lowercase__:   List[str]					=      processor(text=_UpperCAmelCase							)

       lowercase__:   Optional[int]					=      tokenizer(_UpperCAmelCase    ,			return_token_type_ids=_UpperCAmelCase							)
       lowercase__:   Optional[Any]					=      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							):
       lowercase__:   Tuple					=      self.get_image_processor()
       lowercase__:   Tuple					=      self.get_tokenizer()
       lowercase__:   str					=      self.get_qformer_tokenizer()

       lowercase__:   Optional[int]					=      InstructBlipProcessor(
           tokenizer=_UpperCAmelCase    ,			image_processor=_UpperCAmelCase    ,			qformer_tokenizer=_UpperCAmelCase							)

       lowercase__:   Dict					=      '''lower newer'''
       lowercase__:   int					=      self.prepare_image_inputs()

       lowercase__:   Dict					=      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							):
       lowercase__:   str					=      self.get_image_processor()
       lowercase__:   Tuple					=      self.get_tokenizer()
       lowercase__:   Tuple					=      self.get_qformer_tokenizer()

       lowercase__:   Optional[Any]					=      InstructBlipProcessor(
           tokenizer=_UpperCAmelCase    ,			image_processor=_UpperCAmelCase    ,			qformer_tokenizer=_UpperCAmelCase							)

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

       lowercase__:   Tuple					=      processor.batch_decode(_UpperCAmelCase							)
       lowercase__:   Dict					=      tokenizer.batch_decode(_UpperCAmelCase							)

       self.assertListEqual(_UpperCAmelCase    ,			_UpperCAmelCase							)






    def _snake_case			(   self							):
       lowercase__:   Dict					=      self.get_image_processor()
       lowercase__:   Union[str, Any]					=      self.get_tokenizer()
       lowercase__:   Union[str, Any]					=      self.get_qformer_tokenizer()

       lowercase__:   Union[str, Any]					=      InstructBlipProcessor(
           tokenizer=_UpperCAmelCase    ,			image_processor=_UpperCAmelCase    ,			qformer_tokenizer=_UpperCAmelCase							)

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

       lowercase__:   Optional[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 SCREAMING_SNAKE_CASE__			(   __UpperCAmelCase       ,    __UpperCAmelCase )  ->  List[str]:
   lowercase__:   Optional[Any]					=      0
   lowercase__:   List[Any]					=      len(__UpperCAmelCase ) - 1

   while left <= right:
      # avoid divided by 0 during interpolation
      if sorted_collection[left] == sorted_collection[right]:
         if sorted_collection[left] == item:
            return left
         else:
            return None

      lowercase__:   Tuple					=      left + ((item - sorted_collection[left]) * (right - left)) // (
          sorted_collection[right] - sorted_collection[left]
      )

      # out of range check
      if point < 0 or point >= len(__UpperCAmelCase ):
         return None

      lowercase__:   Optional[int]					=      sorted_collection[point]
      if current_item == item:
         return point
      else:
         if point < left:
            lowercase__:   List[Any]					=      left
            lowercase__:   int					=      point
         elif point > right:
            lowercase__:   Dict					=      right
            lowercase__:   List[str]					=      point
         else:
            if item < current_item:
               lowercase__:   int					=      point - 1
            else:
               lowercase__:   int					=      point + 1
   return None



def SCREAMING_SNAKE_CASE__			(   __UpperCAmelCase       ,    __UpperCAmelCase       ,    __UpperCAmelCase       ,    __UpperCAmelCase )  ->  List[str]:

   # avoid divided by 0 during interpolation
   if sorted_collection[left] == sorted_collection[right]:
      if sorted_collection[left] == item:
         return left
      else:
         return None

   lowercase__:   Optional[int]					=      left + ((item - sorted_collection[left]) * (right - left)) // (
       sorted_collection[right] - sorted_collection[left]
   )

   # out of range check
   if point < 0 or point >= len(__UpperCAmelCase ):
      return None

   if sorted_collection[point] == item:
      return point
   elif point < left:
      return interpolation_search_by_recursion(__UpperCAmelCase       ,    __UpperCAmelCase       ,    __UpperCAmelCase       ,    __UpperCAmelCase )
   elif point > right:
      return interpolation_search_by_recursion(__UpperCAmelCase       ,    __UpperCAmelCase       ,    __UpperCAmelCase       ,    __UpperCAmelCase )
   else:
      if sorted_collection[point] > item:
         return interpolation_search_by_recursion(
             __UpperCAmelCase       ,    __UpperCAmelCase       ,    __UpperCAmelCase       ,    point - 1 )
      else:
         return interpolation_search_by_recursion(
             __UpperCAmelCase       ,    __UpperCAmelCase       ,    point + 1       ,    __UpperCAmelCase )



def SCREAMING_SNAKE_CASE__			(   __UpperCAmelCase )  ->  List[Any]:
   if collection != sorted(__UpperCAmelCase ):
      raise ValueError('''Collection must be ascending sorted''' )
   return True


if __name__ == "__main__":
       import sys
       __A			   = 0
       if debug == 1:
              __A			   = [1_0, 3_0, 4_0, 4_5, 5_0, 6_6, 7_7, 9_3]
              try:
                     __assert_sorted(collection)
              except ValueError:
                     sys.exit("Sequence must be ascending sorted to apply interpolation search")
              __A			   = 6_7

       __A			   = interpolation_search(collection, target)
       if result is not None:
              print(f'''{target} found at positions: {result}''')
       else:
              print("Not found")
