'''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 	__SCREAMING_SNAKE_CASE		(			unittest.TestCase			):







  '''simple docstring'''






  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       UpperCAmelCase_				:  Any  = tempfile.mkdtemp()

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

       UpperCAmelCase_				:  List[str]  = GitProcessor(snake_case_ ,						snake_case_		)

       processor.save_pretrained(self.tmpdirname		)


  def _UpperCamelCase	(					self ,						**snake_case_		):




       '''simple docstring'''

       return AutoProcessor.from_pretrained(self.tmpdirname ,						**snake_case_		).tokenizer


  def _UpperCamelCase	(					self ,						**snake_case_		):




       '''simple docstring'''

       return AutoProcessor.from_pretrained(self.tmpdirname ,						**snake_case_		).image_processor


  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       shutil.rmtree(self.tmpdirname		)


  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       UpperCAmelCase_				:  Tuple  = [np.random.randint(2_5_5 ,						size=(3, 3_0, 4_0_0) ,						dtype=np.uinta		)]

       UpperCAmelCase_				:  Dict  = [Image.fromarray(np.moveaxis(snake_case_ ,						0 ,						-1		)		) for x in image_inputs]

       return image_inputs


  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       UpperCAmelCase_				:  Union[str, Any]  = GitProcessor(tokenizer=self.get_tokenizer() ,						image_processor=self.get_image_processor()		)
       processor.save_pretrained(self.tmpdirname		)

       UpperCAmelCase_				:  Union[str, Any]  = self.get_tokenizer(bos_token='(BOS)' ,						eos_token='(EOS)'		)
       UpperCAmelCase_				:  Union[str, Any]  = self.get_image_processor(do_normalize=snake_case_ ,						padding_value=1.0		)

       UpperCAmelCase_				:  List[str]  = GitProcessor.from_pretrained(
           self.tmpdirname ,						bos_token='(BOS)' ,						eos_token='(EOS)' ,						do_normalize=snake_case_ ,						padding_value=1.0		)

       self.assertEqual(processor.tokenizer.get_vocab() ,						tokenizer_add_kwargs.get_vocab()		)
       self.assertIsInstance(processor.tokenizer ,						snake_case_		)

       self.assertEqual(processor.image_processor.to_json_string() ,						image_processor_add_kwargs.to_json_string()		)
       self.assertIsInstance(processor.image_processor ,						snake_case_		)


  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       UpperCAmelCase_				:  Optional[Any]  = self.get_image_processor()
       UpperCAmelCase_				:  Optional[int]  = self.get_tokenizer()

       UpperCAmelCase_				:  Optional[Any]  = GitProcessor(tokenizer=snake_case_ ,						image_processor=snake_case_		)

       UpperCAmelCase_				:  Tuple  = self.prepare_image_inputs()

       UpperCAmelCase_				:  int  = image_processor(snake_case_ ,						return_tensors='np'		)
       UpperCAmelCase_				:  Optional[Any]  = processor(images=snake_case_ ,						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_				:  Optional[int]  = self.get_image_processor()
       UpperCAmelCase_				:  Tuple  = self.get_tokenizer()

       UpperCAmelCase_				:  List[str]  = GitProcessor(tokenizer=snake_case_ ,						image_processor=snake_case_		)

       UpperCAmelCase_				:  Dict  = 'lower newer'

       UpperCAmelCase_				:  Optional[int]  = processor(text=snake_case_		)

       UpperCAmelCase_				:  List[str]  = tokenizer(snake_case_ ,						return_token_type_ids=snake_case_		)

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


  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       UpperCAmelCase_				:  Optional[Any]  = self.get_image_processor()
       UpperCAmelCase_				:  List[str]  = self.get_tokenizer()

       UpperCAmelCase_				:  Dict  = GitProcessor(tokenizer=snake_case_ ,						image_processor=snake_case_		)

       UpperCAmelCase_				:  Optional[int]  = 'lower newer'
       UpperCAmelCase_				:  Any  = self.prepare_image_inputs()

       UpperCAmelCase_				:  str  = processor(text=snake_case_ ,						images=snake_case_		)

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

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


  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       UpperCAmelCase_				:  Any  = self.get_image_processor()
       UpperCAmelCase_				:  Any  = self.get_tokenizer()

       UpperCAmelCase_				:  List[Any]  = GitProcessor(tokenizer=snake_case_ ,						image_processor=snake_case_		)

       UpperCAmelCase_				:  List[str]  = [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

       UpperCAmelCase_				:  Optional[int]  = processor.batch_decode(snake_case_		)
       UpperCAmelCase_				:  Optional[Any]  = tokenizer.batch_decode(snake_case_		)

       self.assertListEqual(snake_case_ ,						snake_case_		)






  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       UpperCAmelCase_				:  Dict  = self.get_image_processor()
       UpperCAmelCase_				:  List[str]  = self.get_tokenizer()

       UpperCAmelCase_				:  Tuple  = GitProcessor(tokenizer=snake_case_ ,						image_processor=snake_case_		)

       UpperCAmelCase_				:  Tuple  = 'lower newer'
       UpperCAmelCase_				:  Optional[int]  = self.prepare_image_inputs()

       UpperCAmelCase_				:  int  = processor(text=snake_case_ ,						images=snake_case_		)

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












def        __SCREAMING_SNAKE_CASE (	lowercase_   )							->						str:

    """simple docstring"""


    return " ".join(sorted(set(sentence.split()   )   )   )


if __name__ == "__main__":
 import doctest

 doctest.testmod()






