

'''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, BertTokenizer, CLIPImageProcessor, GitProcessor, PreTrainedTokenizerFast
@require_vision
class      SCREAMING_SNAKE_CASE__      (    unittest.TestCase				):




    def   __lowerCamelCase				( self      ):






          """simple docstring"""






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

          SCREAMING_SNAKE_CASE_				:      Optional[int]					=	CLIPImageProcessor()
          SCREAMING_SNAKE_CASE_				:      str					=	BertTokenizer.from_pretrained(
              "hf-internal-testing/tiny-random-BertModel"    ,					model_input_names=["input_ids", "attention_mask"]      )

          SCREAMING_SNAKE_CASE_				:      Any					=	GitProcessor(lowercase__    ,					lowercase__      )

          processor.save_pretrained(self.tmpdirname      )




    def   __lowerCamelCase				( self    ,					**lowercase__      ):






          """simple docstring"""






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




    def   __lowerCamelCase				( self    ,					**lowercase__      ):






          """simple docstring"""






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




    def   __lowerCamelCase				( self      ):






          """simple docstring"""






          shutil.rmtree(self.tmpdirname      )




    def   __lowerCamelCase				( self      ):






          """simple docstring"""






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

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

          return image_inputs




    def   __lowerCamelCase				( self      ):






          """simple docstring"""






          SCREAMING_SNAKE_CASE_				:      str					=	GitProcessor(tokenizer=self.get_tokenizer()    ,					image_processor=self.get_image_processor()      )
          processor.save_pretrained(self.tmpdirname      )

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

          SCREAMING_SNAKE_CASE_				:      str					=	GitProcessor.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__      )




    def   __lowerCamelCase				( self      ):






          """simple docstring"""






          SCREAMING_SNAKE_CASE_				:      List[str]					=	self.get_image_processor()
          SCREAMING_SNAKE_CASE_				:      Dict					=	self.get_tokenizer()

          SCREAMING_SNAKE_CASE_				:      Dict					=	GitProcessor(tokenizer=lowercase__    ,					image_processor=lowercase__      )

          SCREAMING_SNAKE_CASE_				:      List[Any]					=	self.prepare_image_inputs()

          SCREAMING_SNAKE_CASE_				:      Tuple					=	image_processor(lowercase__    ,					return_tensors="np"      )
          SCREAMING_SNAKE_CASE_				:      Optional[int]					=	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   __lowerCamelCase				( self      ):






          """simple docstring"""






          SCREAMING_SNAKE_CASE_				:      int					=	self.get_image_processor()
          SCREAMING_SNAKE_CASE_				:      int					=	self.get_tokenizer()

          SCREAMING_SNAKE_CASE_				:      List[Any]					=	GitProcessor(tokenizer=lowercase__    ,					image_processor=lowercase__      )

          SCREAMING_SNAKE_CASE_				:      List[Any]					=	"lower newer"

          SCREAMING_SNAKE_CASE_				:      Union[str, Any]					=	processor(text=lowercase__      )

          SCREAMING_SNAKE_CASE_				:      str					=	tokenizer(lowercase__    ,					return_token_type_ids=lowercase__      )

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




    def   __lowerCamelCase				( self      ):






          """simple docstring"""






          SCREAMING_SNAKE_CASE_				:      Tuple					=	self.get_image_processor()
          SCREAMING_SNAKE_CASE_				:      Any					=	self.get_tokenizer()

          SCREAMING_SNAKE_CASE_				:      int					=	GitProcessor(tokenizer=lowercase__    ,					image_processor=lowercase__      )

          SCREAMING_SNAKE_CASE_				:      Any					=	"lower newer"
          SCREAMING_SNAKE_CASE_				:      Any					=	self.prepare_image_inputs()

          SCREAMING_SNAKE_CASE_				:      int					=	processor(text=lowercase__    ,					images=lowercase__      )

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

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




    def   __lowerCamelCase				( self      ):






          """simple docstring"""






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

          SCREAMING_SNAKE_CASE_				:      Union[str, Any]					=	GitProcessor(tokenizer=lowercase__    ,					image_processor=lowercase__      )

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

          SCREAMING_SNAKE_CASE_				:      int					=	processor.batch_decode(lowercase__      )
          SCREAMING_SNAKE_CASE_				:      Dict					=	tokenizer.batch_decode(lowercase__      )

          self.assertListEqual(lowercase__    ,					lowercase__      )







    def   __lowerCamelCase				( self      ):






          """simple docstring"""






          SCREAMING_SNAKE_CASE_				:      List[str]					=	self.get_image_processor()
          SCREAMING_SNAKE_CASE_				:      List[str]					=	self.get_tokenizer()

          SCREAMING_SNAKE_CASE_				:      int					=	GitProcessor(tokenizer=lowercase__    ,					image_processor=lowercase__      )

          SCREAMING_SNAKE_CASE_				:      List[Any]					=	"lower newer"
          SCREAMING_SNAKE_CASE_				:      int					=	self.prepare_image_inputs()

          SCREAMING_SNAKE_CASE_				:      List[str]					=	processor(text=lowercase__    ,					images=lowercase__      )

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




'''simple docstring'''






def  __lowerCamelCase      (				SCREAMING_SNAKE_CASE_					:     Optional[int]  ,  SCREAMING_SNAKE_CASE_					:     Tuple   )							->       List[str]:
      """simple docstring"""

      SCREAMING_SNAKE_CASE_				:      List[str]					=	(boundary[1] - boundary[0]) / steps
      SCREAMING_SNAKE_CASE_				:      Optional[Any]					=	boundary[0]
      SCREAMING_SNAKE_CASE_				:      int					=	boundary[1]
      SCREAMING_SNAKE_CASE_				:      List[Any]					=	make_points(SCREAMING_SNAKE_CASE_  ,  SCREAMING_SNAKE_CASE_  ,  SCREAMING_SNAKE_CASE_   )
      SCREAMING_SNAKE_CASE_				:      Dict					=	0.0
      y += (h / 3.0) * f(SCREAMING_SNAKE_CASE_   )
      SCREAMING_SNAKE_CASE_				:      Tuple					=	2
      for i in x_i:
            y += (h / 3) * (4 - 2 * (cnt % 2)) * f(SCREAMING_SNAKE_CASE_   )
            cnt += 1
      y += (h / 3.0) * f(SCREAMING_SNAKE_CASE_   )
      return y


def  __lowerCamelCase      (				SCREAMING_SNAKE_CASE_					:     Optional[Any]  ,  SCREAMING_SNAKE_CASE_					:     List[Any]  ,  SCREAMING_SNAKE_CASE_					:     Optional[Any]   )							->       List[Any]:
      """simple docstring"""

      SCREAMING_SNAKE_CASE_				:      List[Any]					=	a + h
      while x < (b - h):
            yield x
            SCREAMING_SNAKE_CASE_				:      List[Any]					=	x + h


def  __lowerCamelCase      (				SCREAMING_SNAKE_CASE_					:     str   )							->       List[Any]:  # enter your function here
      """simple docstring"""

      SCREAMING_SNAKE_CASE_				:      List[str]					=	(x - 0) * (x - 0)
      return y


def  __lowerCamelCase      (				)							->       int:
      """simple docstring"""

      SCREAMING_SNAKE_CASE_				:      List[Any]					=	0.0  # Lower bound of integration
      SCREAMING_SNAKE_CASE_				:      Optional[Any]					=	1.0  # Upper bound of integration
      SCREAMING_SNAKE_CASE_				:      str					=	10.0  # define number of steps or resolution
      SCREAMING_SNAKE_CASE_				:      List[Any]					=	[a, b]  # define boundary of integration
      SCREAMING_SNAKE_CASE_				:      List[str]					=	method_a(SCREAMING_SNAKE_CASE_  ,  SCREAMING_SNAKE_CASE_   )
      print(F"y = {y}"   )


if __name__ == "__main__":
      main()

