'''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    lowerCamelCase__  (   unittest.TestCase     ):



   def  _UpperCamelCase		(    self     )				->     List[Any]:
        """simple docstring"""





        _UpperCamelCase  :Any       =tempfile.mkdtemp()

        _UpperCamelCase  :Union[str, Any]       =CLIPImageProcessor()
        _UpperCamelCase  :Dict       =BertTokenizer.from_pretrained(
            """hf-internal-testing/tiny-random-BertModel"""					,      model_input_names=["""input_ids""", """attention_mask"""]     )

        _UpperCamelCase  :Union[str, Any]       =GitProcessor(lowerCAmelCase__					,      lowerCAmelCase__     )

        processor.save_pretrained(self.tmpdirname     )



   def  _UpperCamelCase		(    self					,      **lowerCAmelCase__     )				->     Dict:
        """simple docstring"""





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



   def  _UpperCamelCase		(    self					,      **lowerCAmelCase__     )				->     Any:
        """simple docstring"""





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



   def  _UpperCamelCase		(    self     )				->     Optional[Any]:
        """simple docstring"""





        shutil.rmtree(self.tmpdirname     )



   def  _UpperCamelCase		(    self     )				->     Union[str, Any]:
        """simple docstring"""





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

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

        return image_inputs



   def  _UpperCamelCase		(    self     )				->     Optional[Any]:
        """simple docstring"""





        _UpperCamelCase  :Optional[Any]       =GitProcessor(tokenizer=self.get_tokenizer()					,      image_processor=self.get_image_processor()     )
        processor.save_pretrained(self.tmpdirname     )

        _UpperCamelCase  :Optional[Any]       =self.get_tokenizer(bos_token="""(BOS)"""					,      eos_token="""(EOS)"""     )
        _UpperCamelCase  :Dict       =self.get_image_processor(do_normalize=lowerCAmelCase__					,      padding_value=1.0     )

        _UpperCamelCase  :int       =GitProcessor.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  _UpperCamelCase		(    self     )				->     Optional[Any]:
        """simple docstring"""





        _UpperCamelCase  :Tuple       =self.get_image_processor()
        _UpperCamelCase  :Optional[int]       =self.get_tokenizer()

        _UpperCamelCase  :Optional[int]       =GitProcessor(tokenizer=lowerCAmelCase__					,      image_processor=lowerCAmelCase__     )

        _UpperCamelCase  :Optional[Any]       =self.prepare_image_inputs()

        _UpperCamelCase  :Tuple       =image_processor(lowerCAmelCase__					,      return_tensors="""np"""     )
        _UpperCamelCase  :Tuple       =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  _UpperCamelCase		(    self     )				->     int:
        """simple docstring"""





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

        _UpperCamelCase  :Any       =GitProcessor(tokenizer=lowerCAmelCase__					,      image_processor=lowerCAmelCase__     )

        _UpperCamelCase  :Union[str, Any]       ="""lower newer"""

        _UpperCamelCase  :List[str]       =processor(text=lowerCAmelCase__     )

        _UpperCamelCase  :List[Any]       =tokenizer(lowerCAmelCase__					,      return_token_type_ids=lowerCAmelCase__     )

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



   def  _UpperCamelCase		(    self     )				->     Tuple:
        """simple docstring"""





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

        _UpperCamelCase  :Optional[Any]       =GitProcessor(tokenizer=lowerCAmelCase__					,      image_processor=lowerCAmelCase__     )

        _UpperCamelCase  :Dict       ="""lower newer"""
        _UpperCamelCase  :Optional[Any]       =self.prepare_image_inputs()

        _UpperCamelCase  :Any       =processor(text=lowerCAmelCase__					,      images=lowerCAmelCase__     )

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

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



   def  _UpperCamelCase		(    self     )				->     Any:
        """simple docstring"""





        _UpperCamelCase  :List[Any]       =self.get_image_processor()
        _UpperCamelCase  :Tuple       =self.get_tokenizer()

        _UpperCamelCase  :Optional[int]       =GitProcessor(tokenizer=lowerCAmelCase__					,      image_processor=lowerCAmelCase__     )

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

        _UpperCamelCase  :int       =processor.batch_decode(lowerCAmelCase__     )
        _UpperCamelCase  :Dict       =tokenizer.batch_decode(lowerCAmelCase__     )

        self.assertListEqual(lowerCAmelCase__					,      lowerCAmelCase__     )




   def  _UpperCamelCase		(    self     )				->     List[Any]:
        """simple docstring"""





        _UpperCamelCase  :Dict       =self.get_image_processor()
        _UpperCamelCase  :Optional[Any]       =self.get_tokenizer()

        _UpperCamelCase  :Any       =GitProcessor(tokenizer=lowerCAmelCase__					,      image_processor=lowerCAmelCase__     )

        _UpperCamelCase  :List[Any]       ="""lower newer"""
        _UpperCamelCase  :Dict       =self.prepare_image_inputs()

        _UpperCamelCase  :str       =processor(text=lowerCAmelCase__					,      images=lowerCAmelCase__     )

        # 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'''




class      UpperCamelCase_					:





	def __init__(    self       )     ->     None:
								UpperCAmelCase	:						int					=						[0, 1]






	def 					_lowercase(    self						,						A       )     ->     list:
								if (difference := index - (len(self.sequence       ) - 2)) >= 1:
															for _ in range(A       ):
																						self.sequence.append(self.sequence[-1] + self.sequence[-2]       )
								return self.sequence[:index]




def  __lowerCamelCase    (   ) ->     None:
							print(
							    """Fibonacci Series Using Dynamic Programming\n"""      ,							"""Enter the index of the Fibonacci number you want to calculate """      ,							"""in the prompt below. (To exit enter exit or Ctrl-C)\n"""      ,							sep=""""""      ,							)
							UpperCAmelCase	:						Tuple					=						Fibonacci()

							while True:
														UpperCAmelCase	:						str					=						input(""">> """						)
														if prompt in {"exit", "quit"}:
																					break

														try:
																					UpperCAmelCase	:						int					=						int(_lowercase						)
														except ValueError:
																					print("""Enter a number or 'exit'"""						)
																					continue

														print(fibonacci.get(_lowercase						)						)


if __name__ == "__main__":
							main()

