




"""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 					__magic_name__							( unittest.TestCase       ):






				'''simple docstring'''





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase       =      tempfile.mkdtemp()

							lowerCamelCase       =      BlipImageProcessor()
							lowerCamelCase       =      BertTokenizer.from_pretrained("""hf-internal-testing/tiny-random-BertModel"""				)

							lowerCamelCase       =      BlipProcessor(lowerCamelCase__	,				lowerCamelCase__				)

							processor.save_pretrained(self.tmpdirname				)





				def      _lowerCAmelCase       ( self	,				**_a				):





							"""simple docstring"""
							return AutoProcessor.from_pretrained(self.tmpdirname	,				**lowerCamelCase__				).tokenizer





				def      _lowerCAmelCase       ( self	,				**_a				):





							"""simple docstring"""
							return AutoProcessor.from_pretrained(self.tmpdirname	,				**lowerCamelCase__				).image_processor





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							shutil.rmtree(self.tmpdirname				)





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase       =      [np.random.randint(255	,				size=(3, 30, 400)	,				dtype=np.uinta				)]

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

							return image_inputs





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase       =      BlipProcessor(tokenizer=self.get_tokenizer()	,				image_processor=self.get_image_processor()				)
							processor.save_pretrained(self.tmpdirname				)

							lowerCamelCase       =      self.get_tokenizer(bos_token="""(BOS)"""	,				eos_token="""(EOS)"""				)
							lowerCamelCase       =      self.get_image_processor(do_normalize=lowerCamelCase__	,				padding_value=1.0				)

							lowerCamelCase       =      BlipProcessor.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				):





							"""simple docstring"""
							lowerCamelCase       =      self.get_image_processor()
							lowerCamelCase       =      self.get_tokenizer()

							lowerCamelCase       =      BlipProcessor(tokenizer=lowerCamelCase__	,				image_processor=lowerCamelCase__				)

							lowerCamelCase       =      self.prepare_image_inputs()

							lowerCamelCase       =      image_processor(lowerCamelCase__	,				return_tensors="""np"""				)
							lowerCamelCase       =      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				):





							"""simple docstring"""
							lowerCamelCase       =      self.get_image_processor()
							lowerCamelCase       =      self.get_tokenizer()

							lowerCamelCase       =      BlipProcessor(tokenizer=lowerCamelCase__	,				image_processor=lowerCamelCase__				)

							lowerCamelCase       =      "lower newer"

							lowerCamelCase       =      processor(text=lowerCamelCase__				)

							lowerCamelCase       =      tokenizer(lowerCamelCase__	,				return_token_type_ids=lowerCamelCase__				)

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





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase       =      self.get_image_processor()
							lowerCamelCase       =      self.get_tokenizer()

							lowerCamelCase       =      BlipProcessor(tokenizer=lowerCamelCase__	,				image_processor=lowerCamelCase__				)

							lowerCamelCase       =      "lower newer"
							lowerCamelCase       =      self.prepare_image_inputs()

							lowerCamelCase       =      processor(text=lowerCamelCase__	,				images=lowerCamelCase__				)

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

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





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase       =      self.get_image_processor()
							lowerCamelCase       =      self.get_tokenizer()

							lowerCamelCase       =      BlipProcessor(tokenizer=lowerCamelCase__	,				image_processor=lowerCamelCase__				)

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

							lowerCamelCase       =      processor.batch_decode(lowerCamelCase__				)
							lowerCamelCase       =      tokenizer.batch_decode(lowerCamelCase__				)

							self.assertListEqual(lowerCamelCase__	,				lowerCamelCase__				)





				def      _lowerCAmelCase       ( self				):





							"""simple docstring"""
							lowerCamelCase       =      self.get_image_processor()
							lowerCamelCase       =      self.get_tokenizer()

							lowerCamelCase       =      BlipProcessor(tokenizer=lowerCamelCase__	,				image_processor=lowerCamelCase__				)

							lowerCamelCase       =      "lower newer"
							lowerCamelCase       =      self.prepare_image_inputs()

							lowerCamelCase       =      processor(text=lowerCamelCase__	,				images=lowerCamelCase__				)

							# 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"""




from __future__ import annotations



def 					a__				(       snake_case__ ,				snake_case__ = None ,				snake_case__ = None       )		->      None:
			if start is None:
						lowerCamelCase       =      0

			if end is None:
						lowerCamelCase       =      len(snake_case__       ) - 1

			if start >= end:
						return

			lowerCamelCase       =      (start + end) // 2

			slowsort(snake_case__ ,				snake_case__ ,				snake_case__       )
			slowsort(snake_case__ ,				mid + 1 ,				snake_case__       )

			if sequence[end] < sequence[mid]:
						lowerCamelCase   ,     lowerCamelCase       =      sequence[mid], sequence[end]

			slowsort(snake_case__ ,				snake_case__ ,				end - 1       )


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

					testmod()



