





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, BlipaProcessor, BlipImageProcessor, GPTaTokenizer, PreTrainedTokenizerFast



@require_vision
class     _UpperCAmelCase   (   unittest.TestCase   ):

  """simple docstring"""


  def     lowercase		(    self			:		List[Any]					)							->						str:
     __lowerCAmelCase							     =     tempfile.mkdtemp()

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

     __lowerCAmelCase							     =     BlipaProcessor(lowerCAmelCase_ ,  lowerCAmelCase_					)

     processor.save_pretrained(self.tmpdirname					)






  def     lowercase		(    self			:		Union[str, Any] ,  **lowerCAmelCase_			:		Optional[Any]					)							->						List[Any]:
     return AutoProcessor.from_pretrained(self.tmpdirname ,  **lowerCAmelCase_					).tokenizer






  def     lowercase		(    self			:		Optional[int] ,  **lowerCAmelCase_			:		List[str]					)							->						str:
     return AutoProcessor.from_pretrained(self.tmpdirname ,  **lowerCAmelCase_					).image_processor






  def     lowercase		(    self			:		Union[str, Any]					)							->						str:
     shutil.rmtree(self.tmpdirname					)






  def     lowercase		(    self			:		Any					)							->						Optional[int]:
     __lowerCAmelCase							     =     [np.random.randint(2_5_5 ,  size=(3, 3_0, 4_0_0) ,  dtype=np.uinta					)]

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

     return image_inputs






  def     lowercase		(    self			:		Any					)							->						int:
     __lowerCAmelCase							     =     BlipaProcessor(tokenizer=self.get_tokenizer() ,  image_processor=self.get_image_processor()					)
     processor.save_pretrained(self.tmpdirname					)

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

     __lowerCAmelCase							     =     BlipaProcessor.from_pretrained(
         self.tmpdirname ,  bos_token='(BOS)' ,  eos_token='(EOS)' ,  do_normalize=lowerCAmelCase_ ,  padding_value=1.0					)

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

     self.assertEqual(processor.image_processor.to_json_string() ,  image_processor_add_kwargs.to_json_string()					)
     self.assertIsInstance(processor.image_processor ,  lowerCAmelCase_					)






  def     lowercase		(    self			:		Optional[int]					)							->						Optional[int]:
     __lowerCAmelCase							     =     self.get_image_processor()
     __lowerCAmelCase							     =     self.get_tokenizer()

     __lowerCAmelCase							     =     BlipaProcessor(tokenizer=lowerCAmelCase_ ,  image_processor=lowerCAmelCase_					)

     __lowerCAmelCase							     =     self.prepare_image_inputs()

     __lowerCAmelCase							     =     image_processor(lowerCAmelCase_ ,  return_tensors='np'					)
     __lowerCAmelCase							     =     processor(images=lowerCAmelCase_ ,  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     lowercase		(    self			:		Any					)							->						Union[str, Any]:
     __lowerCAmelCase							     =     self.get_image_processor()
     __lowerCAmelCase							     =     self.get_tokenizer()

     __lowerCAmelCase							     =     BlipaProcessor(tokenizer=lowerCAmelCase_ ,  image_processor=lowerCAmelCase_					)

     __lowerCAmelCase							     =     'lower newer'

     __lowerCAmelCase							     =     processor(text=lowerCAmelCase_					)

     __lowerCAmelCase							     =     tokenizer(lowerCAmelCase_ ,  return_token_type_ids=lowerCAmelCase_					)

     for key in encoded_tok.keys():
        self.assertListEqual(encoded_tok[key] ,  encoded_processor[key]					)






  def     lowercase		(    self			:		int					)							->						List[Any]:
     __lowerCAmelCase							     =     self.get_image_processor()
     __lowerCAmelCase							     =     self.get_tokenizer()

     __lowerCAmelCase							     =     BlipaProcessor(tokenizer=lowerCAmelCase_ ,  image_processor=lowerCAmelCase_					)

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

     __lowerCAmelCase							     =     processor(text=lowerCAmelCase_ ,  images=lowerCAmelCase_					)

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

     # test if it raises when no input is passed
     with pytest.raises(lowerCAmelCase_					):
        processor()






  def     lowercase		(    self			:		int					)							->						Optional[Any]:
     __lowerCAmelCase							     =     self.get_image_processor()
     __lowerCAmelCase							     =     self.get_tokenizer()

     __lowerCAmelCase							     =     BlipaProcessor(tokenizer=lowerCAmelCase_ ,  image_processor=lowerCAmelCase_					)

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

     __lowerCAmelCase							     =     processor.batch_decode(lowerCAmelCase_					)
     __lowerCAmelCase							     =     tokenizer.batch_decode(lowerCAmelCase_					)

     self.assertListEqual(lowerCAmelCase_ ,  lowerCAmelCase_					)






  def     lowercase		(    self			:		List[Any]					)							->						List[str]:
     __lowerCAmelCase							     =     self.get_image_processor()
     __lowerCAmelCase							     =     self.get_tokenizer()

     __lowerCAmelCase							     =     BlipaProcessor(tokenizer=lowerCAmelCase_ ,  image_processor=lowerCAmelCase_					)

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

     __lowerCAmelCase							     =     processor(text=lowerCAmelCase_ ,  images=lowerCAmelCase_					)

     # For now the processor supports only ['pixel_values', 'input_ids', 'attention_mask']
     self.assertListEqual(list(inputs.keys()					) ,  ['pixel_values', 'input_ids', 'attention_mask']					)








from collections.abc import Sequence

def   a_   (			lowerCAmelCase_				:      Sequence[float],     lowerCAmelCase_				:      bool = False     ):
   if not arr:
      return 0

   __lowerCAmelCase							     =     0 if allow_empty_subarrays else float('-inf'     )
   __lowerCAmelCase							     =     0.0
   for num in arr:
      __lowerCAmelCase							     =     max(0 if allow_empty_subarrays else num,     curr_sum + num     )
      __lowerCAmelCase							     =     max(lowerCAmelCase_,     lowerCAmelCase_     )

   return max_sum


if __name__ == "__main__":
     from doctest import testmod

     testmod()

     _snake_case  :   Optional[Any]						   =  [-2, 1, -3, 4, -1, 2, 1, -5, 4]
     print(F"""{max_subarray_sum(nums) = }""")

