
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     ):
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Union[str, Any]       	=      tempfile.mkdtemp()

           lowercase							:     Tuple       	=      BlipImageProcessor()
           lowercase							:     str       	=      GPTaTokenizer.from_pretrained("""hf-internal-testing/tiny-random-GPT2Model"""      )
           lowercase							:     Dict       	=      BertTokenizerFast.from_pretrained("""hf-internal-testing/tiny-random-bert"""      )

           lowercase							:     Tuple       	=      InstructBlipProcessor(snake_case		,snake_case		,snake_case      )

           processor.save_pretrained(self.tmpdirname      )
    def       _SCREAMING_SNAKE_CASE       (  self		,**snake_case      ):



           '''simple docstring'''







           return AutoProcessor.from_pretrained(self.tmpdirname		,**snake_case      ).tokenizer
    def       _SCREAMING_SNAKE_CASE       (  self		,**snake_case      ):



           '''simple docstring'''







           return AutoProcessor.from_pretrained(self.tmpdirname		,**snake_case      ).image_processor
    def       _SCREAMING_SNAKE_CASE       (  self		,**snake_case      ):



           '''simple docstring'''







           return AutoProcessor.from_pretrained(self.tmpdirname		,**snake_case      ).qformer_tokenizer
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







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



           '''simple docstring'''







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

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

           return image_inputs
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Union[str, Any]       	=      InstructBlipProcessor(
               tokenizer=self.get_tokenizer()		,image_processor=self.get_image_processor()		,qformer_tokenizer=self.get_qformer_tokenizer()		,)
           processor.save_pretrained(self.tmpdirname      )

           lowercase							:     Optional[Any]       	=      self.get_tokenizer(bos_token="""(BOS)"""		,eos_token="""(EOS)"""      )
           lowercase							:     Union[str, Any]       	=      self.get_image_processor(do_normalize=snake_case		,padding_value=1.0      )

           lowercase							:     Dict       	=      InstructBlipProcessor.from_pretrained(
               self.tmpdirname		,bos_token="""(BOS)"""		,eos_token="""(EOS)"""		,do_normalize=snake_case		,padding_value=1.0      )

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

           self.assertEqual(processor.image_processor.to_json_string()		,image_processor_add_kwargs.to_json_string()      )
           self.assertIsInstance(processor.image_processor		,snake_case      )
           self.assertIsInstance(processor.qformer_tokenizer		,snake_case      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







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

           lowercase							:     Optional[Any]       	=      InstructBlipProcessor(
               tokenizer=snake_case		,image_processor=snake_case		,qformer_tokenizer=snake_case      )

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

           lowercase							:     Optional[int]       	=      image_processor(snake_case		,return_tensors="""np"""      )
           lowercase							:     Union[str, Any]       	=      processor(images=snake_case		,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       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







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

           lowercase							:     Dict       	=      InstructBlipProcessor(
               tokenizer=snake_case		,image_processor=snake_case		,qformer_tokenizer=snake_case      )

           lowercase							:     Optional[int]       	=      """lower newer"""

           lowercase							:     Any       	=      processor(text=snake_case      )

           lowercase							:     Any       	=      tokenizer(snake_case		,return_token_type_ids=snake_case      )
           lowercase							:     List[str]       	=      qformer_tokenizer(snake_case		,return_token_type_ids=snake_case      )

           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       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







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

           lowercase							:     List[Any]       	=      InstructBlipProcessor(
               tokenizer=snake_case		,image_processor=snake_case		,qformer_tokenizer=snake_case      )

           lowercase							:     Any       	=      """lower newer"""
           lowercase							:     Tuple       	=      self.prepare_image_inputs()

           lowercase							:     Any       	=      processor(text=snake_case		,images=snake_case      )

           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(snake_case      ):
                  processor()
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







           lowercase							:     Any       	=      self.get_image_processor()
           lowercase							:     str       	=      self.get_tokenizer()
           lowercase							:     str       	=      self.get_qformer_tokenizer()

           lowercase							:     Tuple       	=      InstructBlipProcessor(
               tokenizer=snake_case		,image_processor=snake_case		,qformer_tokenizer=snake_case      )

           lowercase							:     Tuple       	=      [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

           lowercase							:     Optional[Any]       	=      processor.batch_decode(snake_case      )
           lowercase							:     Any       	=      tokenizer.batch_decode(snake_case      )

           self.assertListEqual(snake_case		,snake_case      )
    def       _SCREAMING_SNAKE_CASE       (  self      ):



           '''simple docstring'''







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

           lowercase							:     Tuple       	=      InstructBlipProcessor(
               tokenizer=snake_case		,image_processor=snake_case		,qformer_tokenizer=snake_case      )

           lowercase							:     int       	=      """lower newer"""
           lowercase							:     Any       	=      self.prepare_image_inputs()

           lowercase							:     Dict       	=      processor(text=snake_case		,images=snake_case      )

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


def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    List[str]:
       if index == r:
              for j in range(SCREAMING_SNAKE_CASE__				):
                     print(data[j]					,	end=""" """				)
              print(""" """				)
              return
       #  When no more elements are there to put in data[]
       if i >= n:
              return
       # current is included, put next at next location
       lowercase							:     Tuple       	=      arr[i]
       combination_util(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	index + 1					,	SCREAMING_SNAKE_CASE__					,	i + 1				)
       # current is excluded, replace it with
       # next (Note that i+1 is passed, but
       # index is not changed)
       combination_util(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	i + 1				)
       # The main function that prints all combinations
       # of size r in arr[] of size n. This function
       # mainly uses combinationUtil()







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    List[str]:
       # A temporary array to store all combination one by one
       lowercase							:     Optional[int]       	=      [0] * r
       # Print all combination using temporary array 'data[]'
       combination_util(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	0					,	SCREAMING_SNAKE_CASE__					,	0				)


if __name__ == "__main__":
  # Driver code to check the function above
  lowercase  :					int						    =							[10, 20, 30, 40, 50]
  print_combination(arr, len(arr), 3)
  # This code is contributed by Ambuj sahu
