
"""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, BlipImageProcessor, BlipProcessor, PreTrainedTokenizerFast
@require_vision
class      _UpperCAmelCase							(		unittest.TestCase							):




  def     a_      (							self							)						->					List[Any]:
      UpperCAmelCase									=					tempfile.mkdtemp()

      UpperCAmelCase									=					BlipImageProcessor()
      UpperCAmelCase									=					BertTokenizer.from_pretrained('hf-internal-testing/tiny-random-BertModel'							)

      UpperCAmelCase									=					BlipProcessor(UpperCamelCase__   ,       UpperCamelCase__							)

      processor.save_pretrained(self.tmpdirname							)




  def     a_      (							self   ,       **lowercase_							)						->					Tuple:
      return AutoProcessor.from_pretrained(self.tmpdirname   ,       **UpperCamelCase__							).tokenizer




  def     a_      (							self   ,       **lowercase_							)						->					str:
      return AutoProcessor.from_pretrained(self.tmpdirname   ,       **UpperCamelCase__							).image_processor




  def     a_      (							self							)						->					Any:
      shutil.rmtree(self.tmpdirname							)




  def     a_      (							self							)						->					Tuple:
      UpperCAmelCase									=					[np.random.randint(2_5_5   ,       size=(3, 3_0, 4_0_0)   ,       dtype=np.uinta							)]

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

      return image_inputs




  def     a_      (							self							)						->					List[str]:
      UpperCAmelCase									=					BlipProcessor(tokenizer=self.get_tokenizer()   ,       image_processor=self.get_image_processor()							)
      processor.save_pretrained(self.tmpdirname							)

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

      UpperCAmelCase									=					BlipProcessor.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__							)




  def     a_      (							self							)						->					Dict:
      UpperCAmelCase									=					self.get_image_processor()
      UpperCAmelCase									=					self.get_tokenizer()

      UpperCAmelCase									=					BlipProcessor(tokenizer=UpperCamelCase__   ,       image_processor=UpperCamelCase__							)

      UpperCAmelCase									=					self.prepare_image_inputs()

      UpperCAmelCase									=					image_processor(UpperCamelCase__   ,       return_tensors='np'							)
      UpperCAmelCase									=					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     a_      (							self							)						->					List[Any]:
      UpperCAmelCase									=					self.get_image_processor()
      UpperCAmelCase									=					self.get_tokenizer()

      UpperCAmelCase									=					BlipProcessor(tokenizer=UpperCamelCase__   ,       image_processor=UpperCamelCase__							)

      UpperCAmelCase									=					'lower newer'

      UpperCAmelCase									=					processor(text=UpperCamelCase__							)

      UpperCAmelCase									=					tokenizer(UpperCamelCase__   ,       return_token_type_ids=UpperCamelCase__							)

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




  def     a_      (							self							)						->					str:
      UpperCAmelCase									=					self.get_image_processor()
      UpperCAmelCase									=					self.get_tokenizer()

      UpperCAmelCase									=					BlipProcessor(tokenizer=UpperCamelCase__   ,       image_processor=UpperCamelCase__							)

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

      UpperCAmelCase									=					processor(text=UpperCamelCase__   ,       images=UpperCamelCase__							)

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

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




  def     a_      (							self							)						->					Dict:
      UpperCAmelCase									=					self.get_image_processor()
      UpperCAmelCase									=					self.get_tokenizer()

      UpperCAmelCase									=					BlipProcessor(tokenizer=UpperCamelCase__   ,       image_processor=UpperCamelCase__							)

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

      UpperCAmelCase									=					processor.batch_decode(UpperCamelCase__							)
      UpperCAmelCase									=					tokenizer.batch_decode(UpperCamelCase__							)

      self.assertListEqual(UpperCamelCase__   ,       UpperCamelCase__							)




  def     a_      (							self							)						->					int:
      UpperCAmelCase									=					self.get_image_processor()
      UpperCAmelCase									=					self.get_tokenizer()

      UpperCAmelCase									=					BlipProcessor(tokenizer=UpperCamelCase__   ,       image_processor=UpperCamelCase__							)

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

      UpperCAmelCase									=					processor(text=UpperCamelCase__   ,       images=UpperCamelCase__							)

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





"""simple docstring"""

import os
from collections.abc import Iterator




def     lowercase__						(					lowerCAmelCase				:					str = "." ) ->      Iterator[str]:






    """simple docstring"""




    for dir_path, dir_names, filenames in os.walk(lowerCAmelCase ):
        UpperCAmelCase									=					[d for d in dir_names if d != 'scripts' and d[0] not in '._']
        for filename in filenames:
            if filename == "__init__.py":
                continue
            if os.path.splitext(lowerCAmelCase )[1] in (".py", ".ipynb"):
                yield os.path.join(lowerCAmelCase ,				lowerCAmelCase ).lstrip('./' )




def     lowercase__						(					lowerCAmelCase				:					Union[str, Any] ) ->      Any:






    """simple docstring"""




    return F"{i * '  '}*" if i else "\n##"




def     lowercase__						(					lowerCAmelCase				:					str ,				lowerCAmelCase				:					str ) ->      str:






    """simple docstring"""




    UpperCAmelCase									=					old_path.split(os.sep )
    for i, new_part in enumerate(new_path.split(os.sep ) ):
        if (i + 1 > len(lowerCAmelCase ) or old_parts[i] != new_part) and new_part:
            print(F"{md_prefix(lowerCAmelCase )} {new_part.replace('_' ,				' ' ).title()}" )
    return new_path




def     lowercase__						(					lowerCAmelCase				:					str = "." ) ->      None:






    """simple docstring"""




    UpperCAmelCase									=					''
    for filepath in sorted(good_file_paths(lowerCAmelCase ) ):
        UpperCAmelCase			,							UpperCAmelCase									=					os.path.split(lowerCAmelCase )
        if filepath != old_path:
            UpperCAmelCase									=					print_path(lowerCAmelCase ,				lowerCAmelCase )
        UpperCAmelCase									=					(filepath.count(os.sep ) + 1) if filepath else 0
        UpperCAmelCase									=					F"{filepath}/{filename}".replace(' ' ,				'%20' )
        UpperCAmelCase									=					os.path.splitext(filename.replace('_' ,				' ' ).title() )[0]
        print(F"{md_prefix(lowerCAmelCase )} [{filename}]({url})" )


if __name__ == "__main__":
   print_directory_md('''.''')



