




"""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, BlipImageProcessor, BlipProcessor, PreTrainedTokenizerFast





@require_vision
class 							lowercase_			(	unittest.TestCase				):



 '''simple docstring'''

 def      lowerCAmelCase_				(					self			:			Optional[int]						):
       _A     =  tempfile.mkdtemp()

       _A     =  BlipImageProcessor()
       _A     =  BertTokenizer.from_pretrained('hf-internal-testing/tiny-random-BertModel'						)

       _A     =  BlipProcessor(SCREAMING_SNAKE_CASE__       ,				SCREAMING_SNAKE_CASE__						)

       processor.save_pretrained(self.tmpdirname						)

 def      lowerCAmelCase_				(					self			:			Optional[int]       ,				**_UpperCAmelCase			:			Optional[Any]						):
       return AutoProcessor.from_pretrained(self.tmpdirname       ,				**SCREAMING_SNAKE_CASE__						).tokenizer

 def      lowerCAmelCase_				(					self			:			Dict       ,				**_UpperCAmelCase			:			Tuple						):
       return AutoProcessor.from_pretrained(self.tmpdirname       ,				**SCREAMING_SNAKE_CASE__						).image_processor

 def      lowerCAmelCase_				(					self			:			List[str]						):
       shutil.rmtree(self.tmpdirname						)

 def      lowerCAmelCase_				(					self			:			Union[str, Any]						):
       _A     =  [np.random.randint(255       ,				size=(3, 30, 400)       ,				dtype=np.uinta						)]

       _A     =  [Image.fromarray(np.moveaxis(SCREAMING_SNAKE_CASE__       ,				0       ,				-1						)						) for x in image_inputs]

       return image_inputs

 def      lowerCAmelCase_				(					self			:			Union[str, Any]						):
       _A     =  BlipProcessor(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=SCREAMING_SNAKE_CASE__       ,				padding_value=1.0						)

       _A     =  BlipProcessor.from_pretrained(
           self.tmpdirname       ,				bos_token='(BOS)'       ,				eos_token='(EOS)'       ,				do_normalize=SCREAMING_SNAKE_CASE__       ,				padding_value=1.0						)

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

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

 def      lowerCAmelCase_				(					self			:			List[Any]						):
       _A     =  self.get_image_processor()
       _A     =  self.get_tokenizer()

       _A     =  BlipProcessor(tokenizer=SCREAMING_SNAKE_CASE__       ,				image_processor=SCREAMING_SNAKE_CASE__						)

       _A     =  self.prepare_image_inputs()

       _A     =  image_processor(SCREAMING_SNAKE_CASE__       ,				return_tensors='np'						)
       _A     =  processor(images=SCREAMING_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      lowerCAmelCase_				(					self			:			int						):
       _A     =  self.get_image_processor()
       _A     =  self.get_tokenizer()

       _A     =  BlipProcessor(tokenizer=SCREAMING_SNAKE_CASE__       ,				image_processor=SCREAMING_SNAKE_CASE__						)

       _A     =  '''lower newer'''

       _A     =  processor(text=SCREAMING_SNAKE_CASE__						)

       _A     =  tokenizer(SCREAMING_SNAKE_CASE__       ,				return_token_type_ids=SCREAMING_SNAKE_CASE__						)

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

 def      lowerCAmelCase_				(					self			:			List[str]						):
       _A     =  self.get_image_processor()
       _A     =  self.get_tokenizer()

       _A     =  BlipProcessor(tokenizer=SCREAMING_SNAKE_CASE__       ,				image_processor=SCREAMING_SNAKE_CASE__						)

       _A     =  '''lower newer'''
       _A     =  self.prepare_image_inputs()

       _A     =  processor(text=SCREAMING_SNAKE_CASE__       ,				images=SCREAMING_SNAKE_CASE__						)

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

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

 def      lowerCAmelCase_				(					self			:			Dict						):
       _A     =  self.get_image_processor()
       _A     =  self.get_tokenizer()

       _A     =  BlipProcessor(tokenizer=SCREAMING_SNAKE_CASE__       ,				image_processor=SCREAMING_SNAKE_CASE__						)

       _A     =  [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

       _A     =  processor.batch_decode(SCREAMING_SNAKE_CASE__						)
       _A     =  tokenizer.batch_decode(SCREAMING_SNAKE_CASE__						)

       self.assertListEqual(SCREAMING_SNAKE_CASE__       ,				SCREAMING_SNAKE_CASE__						)



 def      lowerCAmelCase_				(					self			:			Union[str, Any]						):
       _A     =  self.get_image_processor()
       _A     =  self.get_tokenizer()

       _A     =  BlipProcessor(tokenizer=SCREAMING_SNAKE_CASE__       ,				image_processor=SCREAMING_SNAKE_CASE__						)

       _A     =  '''lower newer'''
       _A     =  self.prepare_image_inputs()

       _A     =  processor(text=SCREAMING_SNAKE_CASE__       ,				images=SCREAMING_SNAKE_CASE__						)

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





"""simple docstring"""






def 				A_       ( snake_case__       ,					snake_case__ = " "		)					->  list:
			_UpperCamelCase					:List[str]					     =	[]

			_UpperCamelCase					:int					     =	0
			for index, char in enumerate(snake_case__		):
						if char == separator:
									split_words.append(string[last_index:index]		)
									_UpperCamelCase					:Dict					     =	index + 1
						elif index + 1 == len(snake_case__		):
									split_words.append(string[last_index : index + 1]		)
			return split_words


if __name__ == "__main__":
					from doctest import testmod

					testmod()

