'''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       __lowercase		(    unittest.TestCase    ):







     """simple docstring"""






     def lowerCAmelCase  (		self     ):
         __UpperCamelCase						:						List[str]		     =	tempfile.mkdtemp()

         __UpperCamelCase						:						Any		     =	CLIPImageProcessor()
         __UpperCamelCase						:						Optional[Any]		     =	BertTokenizer.from_pretrained(
             'hf-internal-testing/tiny-random-BertModel'  ,      model_input_names=['input_ids', 'attention_mask']     )

         __UpperCamelCase						:						Optional[Any]		     =	GitProcessor(lowerCAmelCase_  ,      lowerCAmelCase_     )

         processor.save_pretrained(self.tmpdirname     )







     def lowerCAmelCase  (		self  ,      **_lowerCamelCase     ):
         return AutoProcessor.from_pretrained(self.tmpdirname  ,      **lowerCAmelCase_     ).tokenizer







     def lowerCAmelCase  (		self  ,      **_lowerCamelCase     ):
         return AutoProcessor.from_pretrained(self.tmpdirname  ,      **lowerCAmelCase_     ).image_processor







     def lowerCAmelCase  (		self     ):
         shutil.rmtree(self.tmpdirname     )







     def lowerCAmelCase  (		self     ):
         __UpperCamelCase						:						Any		     =	[np.random.randint(2_5_5  ,      size=(3, 3_0, 4_0_0)  ,      dtype=np.uinta     )]

         __UpperCamelCase						:						str		     =	[Image.fromarray(np.moveaxis(lowerCAmelCase_  ,      0  ,      -1     )     ) for x in image_inputs]

         return image_inputs







     def lowerCAmelCase  (		self     ):
         __UpperCamelCase						:						List[str]		     =	GitProcessor(tokenizer=self.get_tokenizer()  ,      image_processor=self.get_image_processor()     )
         processor.save_pretrained(self.tmpdirname     )

         __UpperCamelCase						:						str		     =	self.get_tokenizer(bos_token='(BOS)'  ,      eos_token='(EOS)'     )
         __UpperCamelCase						:						int		     =	self.get_image_processor(do_normalize=lowerCAmelCase_  ,      padding_value=1.0     )

         __UpperCamelCase						:						str		     =	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 lowerCAmelCase  (		self     ):
         __UpperCamelCase						:						List[Any]		     =	self.get_image_processor()
         __UpperCamelCase						:						Any		     =	self.get_tokenizer()

         __UpperCamelCase						:						Dict		     =	GitProcessor(tokenizer=lowerCAmelCase_  ,      image_processor=lowerCAmelCase_     )

         __UpperCamelCase						:						int		     =	self.prepare_image_inputs()

         __UpperCamelCase						:						Optional[Any]		     =	image_processor(lowerCAmelCase_  ,      return_tensors='np'     )
         __UpperCamelCase						:						str		     =	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 lowerCAmelCase  (		self     ):
         __UpperCamelCase						:						List[Any]		     =	self.get_image_processor()
         __UpperCamelCase						:						Tuple		     =	self.get_tokenizer()

         __UpperCamelCase						:						Union[str, Any]		     =	GitProcessor(tokenizer=lowerCAmelCase_  ,      image_processor=lowerCAmelCase_     )

         __UpperCamelCase						:						List[str]		     =	'lower newer'

         __UpperCamelCase						:						List[str]		     =	processor(text=lowerCAmelCase_     )

         __UpperCamelCase						:						Tuple		     =	tokenizer(lowerCAmelCase_  ,      return_token_type_ids=lowerCAmelCase_     )

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







     def lowerCAmelCase  (		self     ):
         __UpperCamelCase						:						Tuple		     =	self.get_image_processor()
         __UpperCamelCase						:						Any		     =	self.get_tokenizer()

         __UpperCamelCase						:						Any		     =	GitProcessor(tokenizer=lowerCAmelCase_  ,      image_processor=lowerCAmelCase_     )

         __UpperCamelCase						:						Optional[int]		     =	'lower newer'
         __UpperCamelCase						:						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 lowerCAmelCase  (		self     ):
         __UpperCamelCase						:						Optional[int]		     =	self.get_image_processor()
         __UpperCamelCase						:						str		     =	self.get_tokenizer()

         __UpperCamelCase						:						Dict		     =	GitProcessor(tokenizer=lowerCAmelCase_  ,      image_processor=lowerCAmelCase_     )

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

         __UpperCamelCase						:						List[Any]		     =	processor.batch_decode(lowerCAmelCase_     )
         __UpperCamelCase						:						Optional[Any]		     =	tokenizer.batch_decode(lowerCAmelCase_     )

         self.assertListEqual(lowerCAmelCase_  ,      lowerCAmelCase_     )







     def lowerCAmelCase  (		self     ):
         __UpperCamelCase						:						Any		     =	self.get_image_processor()
         __UpperCamelCase						:						str		     =	self.get_tokenizer()

         __UpperCamelCase						:						int		     =	GitProcessor(tokenizer=lowerCAmelCase_  ,      image_processor=lowerCAmelCase_     )

         __UpperCamelCase						:						Any		     =	'lower newer'
         __UpperCamelCase						:						Tuple		     =	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'''





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

