code: 
  """simple docstring"""
  
  
  
  
  
  import os
  import unittest
  
  import pytest
  from parameterized import parameterized
  
  from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
  
  
  # skipping in unittest tests
  
  _a	 =							[(1,)]
  
  
  
  
  
  
  
  def 			__a  (	):
     UpperCAmelCase_      :      Optional[Any]      =					bool(os.getenv("RUN_SLOW",	0						)						)
     if run_slow:
        assert True
     else:
        assert False, "should have been skipped"
  
  
  
  
  
  
  
  def 			__a  (	):
     UpperCAmelCase_      :      Optional[Any]      =					bool(os.getenv("RUN_SLOW",	0						)						)
     if run_slow and torch_device == "cuda":
        assert True
     else:
        assert False, "should have been skipped"
  
  
  @require_torch
  class A_			(unittest.TestCase   ):
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    @slow
    @require_torch_gpu
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       check_slow_torch_cuda()
  
  
  
  
  
  
  
    @require_torch_gpu
    @slow
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       check_slow_torch_cuda()
  
  
  
  
  
  
  
    @parameterized.expand(lowercase_						)
    @slow
    def  UpperCamelCase__      (	self       ,     lowercase_=None						):
  
       """simple docstring"""
       check_slow()
  
  
  
  
  
  
  
  @slow
  @require_torch_gpu
  def 			__a  (	):
     check_slow_torch_cuda()
  
  
  
  
  
  
  
  @require_torch_gpu
  @slow
  def 			__a  (	):
     check_slow_torch_cuda()
  
  
  
  
  
  
  
  @slow
  @pytest.mark.parametrize("param",	[1]						)
  def 			__a  (	__lowerCamelCase						):
     check_slow()
  
  
  
  
  
  
  
  @pytest.mark.parametrize("param",	[1]						)
  @slow
  def 			__a  (	__lowerCamelCase						):
     check_slow()
  
style_context: 
  """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 A_			(unittest.TestCase   ):
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       UpperCAmelCase_      :      Optional[int]      =					tempfile.mkdtemp()
  
       UpperCAmelCase_      :      List[Any]      =					CLIPImageProcessor()
       UpperCAmelCase_      :      Any      =					BertTokenizer.from_pretrained(
           "hf-internal-testing/tiny-random-BertModel"       ,     model_input_names=["input_ids", "attention_mask"]						)
  
       UpperCAmelCase_      :      Tuple      =					GitProcessor(lowercase_       ,     lowercase_						)
  
       processor.save_pretrained(self.tmpdirname						)
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self       ,     **lowercase_						):
  
       """simple docstring"""
       return AutoProcessor.from_pretrained(self.tmpdirname       ,     **lowercase_						).tokenizer
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self       ,     **lowercase_						):
  
       """simple docstring"""
       return AutoProcessor.from_pretrained(self.tmpdirname       ,     **lowercase_						).image_processor
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       shutil.rmtree(self.tmpdirname						)
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       UpperCAmelCase_      :      Optional[int]      =					[np.random.randint(255       ,     size=(3, 30, 400)       ,     dtype=np.uinta						)]
  
       UpperCAmelCase_      :      Optional[Any]      =					[Image.fromarray(np.moveaxis(lowercase_       ,     0       ,     -1						)						) for x in image_inputs]
  
       return image_inputs
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       UpperCAmelCase_      :      List[Any]      =					GitProcessor(tokenizer=self.get_tokenizer()       ,     image_processor=self.get_image_processor()						)
       processor.save_pretrained(self.tmpdirname						)
  
       UpperCAmelCase_      :      Optional[int]      =					self.get_tokenizer(bos_token="(BOS)"       ,     eos_token="(EOS)"						)
       UpperCAmelCase_      :      Union[str, Any]      =					self.get_image_processor(do_normalize=lowercase_       ,     padding_value=1.0						)
  
       UpperCAmelCase_      :      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  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       UpperCAmelCase_      :      Dict      =					self.get_image_processor()
       UpperCAmelCase_      :      Union[str, Any]      =					self.get_tokenizer()
  
       UpperCAmelCase_      :      Union[str, Any]      =					GitProcessor(tokenizer=lowercase_       ,     image_processor=lowercase_						)
  
       UpperCAmelCase_      :      List[Any]      =					self.prepare_image_inputs()
  
       UpperCAmelCase_      :      Optional[Any]      =					image_processor(lowercase_       ,     return_tensors="np"						)
       UpperCAmelCase_      :      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  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       UpperCAmelCase_      :      Union[str, Any]      =					self.get_image_processor()
       UpperCAmelCase_      :      Tuple      =					self.get_tokenizer()
  
       UpperCAmelCase_      :      int      =					GitProcessor(tokenizer=lowercase_       ,     image_processor=lowercase_						)
  
       UpperCAmelCase_      :      Optional[Any]      =					"lower newer"
  
       UpperCAmelCase_      :      Any      =					processor(text=lowercase_						)
  
       UpperCAmelCase_      :      int      =					tokenizer(lowercase_       ,     return_token_type_ids=lowercase_						)
  
       for key in encoded_tok.keys():
          self.assertListEqual(encoded_tok[key]       ,     encoded_processor[key]						)
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       UpperCAmelCase_      :      Optional[int]      =					self.get_image_processor()
       UpperCAmelCase_      :      Union[str, Any]      =					self.get_tokenizer()
  
       UpperCAmelCase_      :      Optional[int]      =					GitProcessor(tokenizer=lowercase_       ,     image_processor=lowercase_						)
  
       UpperCAmelCase_      :      List[str]      =					"lower newer"
       UpperCAmelCase_      :      Dict      =					self.prepare_image_inputs()
  
       UpperCAmelCase_      :      Any      =					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  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       UpperCAmelCase_      :      Optional[Any]      =					self.get_image_processor()
       UpperCAmelCase_      :      str      =					self.get_tokenizer()
  
       UpperCAmelCase_      :      int      =					GitProcessor(tokenizer=lowercase_       ,     image_processor=lowercase_						)
  
       UpperCAmelCase_      :      Tuple      =					[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]
  
       UpperCAmelCase_      :      Any      =					processor.batch_decode(lowercase_						)
       UpperCAmelCase_      :      Optional[Any]      =					tokenizer.batch_decode(lowercase_						)
  
       self.assertListEqual(lowercase_       ,     lowercase_						)
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       UpperCAmelCase_      :      Union[str, Any]      =					self.get_image_processor()
       UpperCAmelCase_      :      Optional[Any]      =					self.get_tokenizer()
  
       UpperCAmelCase_      :      str      =					GitProcessor(tokenizer=lowercase_       ,     image_processor=lowercase_						)
  
       UpperCAmelCase_      :      int      =					"lower newer"
       UpperCAmelCase_      :      Tuple      =					self.prepare_image_inputs()
  
       UpperCAmelCase_      :      Optional[Any]      =					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"]						)
  
  
  