code: 
  
  
  
  
  
  """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    ):
  
  
  
  
  
  		'''simple docstring'''
  
  
  
  
  
  
  		def      lowerCamelCase (     self							:			Optional[int]			):
  				lowerCAmelCase_     :							Any             =    tempfile.mkdtemp()
  
  				lowerCAmelCase_     :							Tuple             =    CLIPImageProcessor()
  				lowerCAmelCase_     :							str             =    BertTokenizer.from_pretrained(
  				    "hf-internal-testing/tiny-random-BertModel"		,    model_input_names=["input_ids", "attention_mask"]			)
  
  				lowerCAmelCase_     :							Dict             =    GitProcessor(a_		,    a_			)
  
  				processor.save_pretrained(self.tmpdirname			)
  
  
  
  
  
  		def      lowerCamelCase (     self							:			Optional[Any]		,    **a_							:			List[Any]			):
  				return AutoProcessor.from_pretrained(self.tmpdirname		,    **a_			).tokenizer
  
  
  
  
  
  		def      lowerCamelCase (     self							:			Dict		,    **a_							:			Dict			):
  				return AutoProcessor.from_pretrained(self.tmpdirname		,    **a_			).image_processor
  
  
  
  
  
  		def      lowerCamelCase (     self							:			Tuple			):
  				shutil.rmtree(self.tmpdirname			)
  
  
  
  
  
  		def      lowerCamelCase (     self							:			str			):
  				lowerCAmelCase_     :							Union[str, Any]             =    [np.random.randint(2_55		,    size=(3, 30, 4_00)		,    dtype=np.uinta			)]
  
  				lowerCAmelCase_     :							Optional[Any]             =    [Image.fromarray(np.moveaxis(a_		,    0		,    -1			)			) for x in image_inputs]
  
  				return image_inputs
  
  
  
  
  
  		def      lowerCamelCase (     self							:			Tuple			):
  				lowerCAmelCase_     :							str             =    GitProcessor(tokenizer=self.get_tokenizer()		,    image_processor=self.get_image_processor()			)
  				processor.save_pretrained(self.tmpdirname			)
  
  				lowerCAmelCase_     :							Dict             =    self.get_tokenizer(bos_token="(BOS)"		,    eos_token="(EOS)"			)
  				lowerCAmelCase_     :							List[str]             =    self.get_image_processor(do_normalize=a_		,    padding_value=1.0			)
  
  				lowerCAmelCase_     :							Dict             =    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      lowerCamelCase (     self							:			Optional[int]			):
  				lowerCAmelCase_     :							int             =    self.get_image_processor()
  				lowerCAmelCase_     :							Optional[int]             =    self.get_tokenizer()
  
  				lowerCAmelCase_     :							List[Any]             =    GitProcessor(tokenizer=a_		,    image_processor=a_			)
  
  				lowerCAmelCase_     :							int             =    self.prepare_image_inputs()
  
  				lowerCAmelCase_     :							str             =    image_processor(a_		,    return_tensors="np"			)
  				lowerCAmelCase_     :							Any             =    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      lowerCamelCase (     self							:			Tuple			):
  				lowerCAmelCase_     :							List[Any]             =    self.get_image_processor()
  				lowerCAmelCase_     :							Union[str, Any]             =    self.get_tokenizer()
  
  				lowerCAmelCase_     :							Union[str, Any]             =    GitProcessor(tokenizer=a_		,    image_processor=a_			)
  
  				lowerCAmelCase_     :							int             =    "lower newer"
  
  				lowerCAmelCase_     :							Union[str, Any]             =    processor(text=a_			)
  
  				lowerCAmelCase_     :							Dict             =    tokenizer(a_		,    return_token_type_ids=a_			)
  
  				for key in encoded_tok.keys():
  						self.assertListEqual(encoded_tok[key]		,    encoded_processor[key]			)
  
  
  
  
  
  		def      lowerCamelCase (     self							:			List[str]			):
  				lowerCAmelCase_     :							Tuple             =    self.get_image_processor()
  				lowerCAmelCase_     :							Tuple             =    self.get_tokenizer()
  
  				lowerCAmelCase_     :							int             =    GitProcessor(tokenizer=a_		,    image_processor=a_			)
  
  				lowerCAmelCase_     :							List[str]             =    "lower newer"
  				lowerCAmelCase_     :							Any             =    self.prepare_image_inputs()
  
  				lowerCAmelCase_     :							List[str]             =    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      lowerCamelCase (     self							:			Dict			):
  				lowerCAmelCase_     :							Any             =    self.get_image_processor()
  				lowerCAmelCase_     :							Any             =    self.get_tokenizer()
  
  				lowerCAmelCase_     :							List[Any]             =    GitProcessor(tokenizer=a_		,    image_processor=a_			)
  
  				lowerCAmelCase_     :							Dict             =    [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]
  
  				lowerCAmelCase_     :							List[str]             =    processor.batch_decode(a_			)
  				lowerCAmelCase_     :							str             =    tokenizer.batch_decode(a_			)
  
  				self.assertListEqual(a_		,    a_			)
  
  
  
  
  
  		def      lowerCamelCase (     self							:			Optional[int]			):
  				lowerCAmelCase_     :							List[Any]             =    self.get_image_processor()
  				lowerCAmelCase_     :							List[str]             =    self.get_tokenizer()
  
  				lowerCAmelCase_     :							Optional[Any]             =    GitProcessor(tokenizer=a_		,    image_processor=a_			)
  
  				lowerCAmelCase_     :							List[str]             =    "lower newer"
  				lowerCAmelCase_     :							int             =    self.prepare_image_inputs()
  
  				lowerCAmelCase_     :							Dict             =    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: 
  
  
  
  
  
  
  """simple docstring"""
  
  from .pipeline_kandinskya_a import KandinskyVaaPipeline
  from .pipeline_kandinsky2_2_controlnet import KandinskyVaaControlnetPipeline
  from .pipeline_kandinsky2_2_controlnet_img2img import KandinskyVaaControlnetImgaImgPipeline
  from .pipeline_kandinsky2_2_img2img import KandinskyVaaImgaImgPipeline
  from .pipeline_kandinsky2_2_inpainting import KandinskyVaaInpaintPipeline
  from .pipeline_kandinsky2_2_prior import KandinskyVaaPriorPipeline
  from .pipeline_kandinsky2_2_prior_emb2emb import KandinskyVaaPriorEmbaEmbPipeline
  