code: 
  
  
  
  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 		_snake_case      (			unittest.TestCase				):
  
  
  
  
  
   """simple docstring"""
  
  
  
   def lowercase_		(						self					)	->							Optional[Any]:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _A           =    tempfile.mkdtemp()
  
     _A           =    CLIPImageProcessor()
     _A           =    BertTokenizer.from_pretrained(
         '''hf-internal-testing/tiny-random-BertModel'''	,    model_input_names=['''input_ids''', '''attention_mask''']					)
  
     _A           =    GitProcessor(a	,    a					)
  
     processor.save_pretrained(self.tmpdirname					)
   def lowercase_		(						self	,    **a					)	->							List[Any]:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     return AutoProcessor.from_pretrained(self.tmpdirname	,    **a					).tokenizer
   def lowercase_		(						self	,    **a					)	->							List[Any]:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     return AutoProcessor.from_pretrained(self.tmpdirname	,    **a					).image_processor
   def lowercase_		(						self					)	->							Dict:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     shutil.rmtree(self.tmpdirname					)
   def lowercase_		(						self					)	->							Any:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _A           =    [np.random.randint(2_5_5	,    size=(3, 3_0, 4_0_0)	,    dtype=np.uinta					)]
  
     _A           =    [Image.fromarray(np.moveaxis(a	,    0	,    -1					)					) for x in image_inputs]
  
     return image_inputs
   def lowercase_		(						self					)	->							int:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _A           =    GitProcessor(tokenizer=self.get_tokenizer()	,    image_processor=self.get_image_processor()					)
     processor.save_pretrained(self.tmpdirname					)
  
     _A           =    self.get_tokenizer(bos_token='''(BOS)'''	,    eos_token='''(EOS)'''					)
     _A           =    self.get_image_processor(do_normalize=a	,    padding_value=1.0					)
  
     _A           =    GitProcessor.from_pretrained(
         self.tmpdirname	,    bos_token='''(BOS)'''	,    eos_token='''(EOS)'''	,    do_normalize=a	,    padding_value=1.0					)
  
     self.assertEqual(processor.tokenizer.get_vocab()	,    tokenizer_add_kwargs.get_vocab()					)
     self.assertIsInstance(processor.tokenizer	,    a					)
  
     self.assertEqual(processor.image_processor.to_json_string()	,    image_processor_add_kwargs.to_json_string()					)
     self.assertIsInstance(processor.image_processor	,    a					)
   def lowercase_		(						self					)	->							List[str]:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _A           =    self.get_image_processor()
     _A           =    self.get_tokenizer()
  
     _A           =    GitProcessor(tokenizer=a	,    image_processor=a					)
  
     _A           =    self.prepare_image_inputs()
  
     _A           =    image_processor(a	,    return_tensors='''np'''					)
     _A           =    processor(images=a	,    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					)	->							int:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _A           =    self.get_image_processor()
     _A           =    self.get_tokenizer()
  
     _A           =    GitProcessor(tokenizer=a	,    image_processor=a					)
  
     _A           =    '''lower newer'''
  
     _A           =    processor(text=a					)
  
     _A           =    tokenizer(a	,    return_token_type_ids=a					)
  
     for key in encoded_tok.keys():
       self.assertListEqual(encoded_tok[key]	,    encoded_processor[key]					)
   def lowercase_		(						self					)	->							List[str]:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _A           =    self.get_image_processor()
     _A           =    self.get_tokenizer()
  
     _A           =    GitProcessor(tokenizer=a	,    image_processor=a					)
  
     _A           =    '''lower newer'''
     _A           =    self.prepare_image_inputs()
  
     _A           =    processor(text=a	,    images=a					)
  
     self.assertListEqual(list(inputs.keys()					)	,    ['''input_ids''', '''attention_mask''', '''pixel_values''']					)
  
     # test if it raises when no input is passed
     with pytest.raises(a					):
       processor()
   def lowercase_		(						self					)	->							Union[str, Any]:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _A           =    self.get_image_processor()
     _A           =    self.get_tokenizer()
  
     _A           =    GitProcessor(tokenizer=a	,    image_processor=a					)
  
     _A           =    [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]
  
     _A           =    processor.batch_decode(a					)
     _A           =    tokenizer.batch_decode(a					)
  
     self.assertListEqual(a	,    a					)
  
  
  
   def lowercase_		(						self					)	->							Any:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _A           =    self.get_image_processor()
     _A           =    self.get_tokenizer()
  
     _A           =    GitProcessor(tokenizer=a	,    image_processor=a					)
  
     _A           =    '''lower newer'''
     _A           =    self.prepare_image_inputs()
  
     _A           =    processor(text=a	,    images=a					)
  
     # For now the processor supports only ['input_ids', 'attention_mask', 'pixel_values']
     self.assertListEqual(list(inputs.keys()					)	,    ['''input_ids''', '''attention_mask''', '''pixel_values''']					)
style_context: 
  
  
  
  import platform
  from argparse import ArgumentParser
  
  import huggingface_hub
  import pandas
  import pyarrow
  
  from datasets import __version__ as version
  from datasets.commands import BaseDatasetsCLICommand
  
  
  
  
  def     UpperCAmelCase__ (							__snake_case							)   -> Optional[Any]:
    return EnvironmentCommand()
  
  
  
  class 		_snake_case      (			lowerCamelCase				):
  
  
  
  
  
   """simple docstring"""
  
  
  
   @staticmethod
   def lowercase_		(						a					)	->							Dict:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _A           =    parser.add_parser('''env'''	,    help='''Print relevant system environment info.'''					)
     download_parser.set_defaults(func=a					)
   def lowercase_		(						self					)	->							Optional[int]:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     _A           =    {
         '''`datasets` version''': version,
         '''Platform''': platform.platform(),
         '''Python version''': platform.python_version(),
         '''Huggingface_hub version''': huggingface_hub.__version__,
         '''PyArrow version''': pyarrow.__version__,
         '''Pandas version''': pandas.__version__,
     }
  
     print('''\nCopy-and-paste the text below in your GitHub issue.\n'''					)
     print(self.format_dict(a					)					)
  
     return info
  
  
  
   @staticmethod
   def lowercase_		(						a					)	->							Optional[int]:
  
  
  
  
     """simple docstring"""
  
  
  
  
  
  
  
     return "\n".join([f'''- {prop}: {val}''' for prop, val in d.items()]					) + "\n"