


"""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, BlipaProcessor, BlipImageProcessor, GPTaTokenizer, PreTrainedTokenizerFast


@require_vision
class 				SCREAMING_SNAKE_CASE__    (		unittest.TestCase    ):
							"""simple docstring"""


							def 	lowercase__							(						self						):






									"""simple docstring"""





									lowerCAmelCase					:					Optional[int]								=							tempfile.mkdtemp()

									lowerCAmelCase					:					Dict								=							BlipImageProcessor()
									lowerCAmelCase					:					Optional[Any]								=							GPTaTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPT2Model"						)

									lowerCAmelCase					:					Dict								=							BlipaProcessor(snake_case__		,					snake_case__						)

									processor.save_pretrained(self.tmpdirname						)

							def 	lowercase__							(						self		,					**snake_case__						):






									"""simple docstring"""





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

							def 	lowercase__							(						self		,					**snake_case__						):






									"""simple docstring"""





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

							def 	lowercase__							(						self						):






									"""simple docstring"""





									shutil.rmtree(self.tmpdirname						)

							def 	lowercase__							(						self						):






									"""simple docstring"""





									lowerCAmelCase					:					Optional[Any]								=							[np.random.randint(255		,					size=(3, 30, 400)		,					dtype=np.uinta						)]

									lowerCAmelCase					:					Optional[Any]								=							[Image.fromarray(np.moveaxis(snake_case__		,					0		,					-1						)						) for x in image_inputs]

									return image_inputs

							def 	lowercase__							(						self						):






									"""simple docstring"""





									lowerCAmelCase					:					List[Any]								=							BlipaProcessor(tokenizer=self.get_tokenizer()		,					image_processor=self.get_image_processor()						)
									processor.save_pretrained(self.tmpdirname						)

									lowerCAmelCase					:					Optional[int]								=							self.get_tokenizer(bos_token="(BOS)"		,					eos_token="(EOS)"						)
									lowerCAmelCase					:					Optional[int]								=							self.get_image_processor(do_normalize=snake_case__		,					padding_value=1.0						)

									lowerCAmelCase					:					str								=							BlipaProcessor.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 	lowercase__							(						self						):






									"""simple docstring"""





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

									lowerCAmelCase					:					List[Any]								=							BlipaProcessor(tokenizer=snake_case__		,					image_processor=snake_case__						)

									lowerCAmelCase					:					Union[str, Any]								=							self.prepare_image_inputs()

									lowerCAmelCase					:					Union[str, Any]								=							image_processor(snake_case__		,					return_tensors="np"						)
									lowerCAmelCase					:					Optional[int]								=							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 	lowercase__							(						self						):






									"""simple docstring"""





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

									lowerCAmelCase					:					Union[str, Any]								=							BlipaProcessor(tokenizer=snake_case__		,					image_processor=snake_case__						)

									lowerCAmelCase					:					Optional[int]								=							"lower newer"

									lowerCAmelCase					:					int								=							processor(text=snake_case__						)

									lowerCAmelCase					:					int								=							tokenizer(snake_case__		,					return_token_type_ids=snake_case__						)

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

							def 	lowercase__							(						self						):






									"""simple docstring"""





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

									lowerCAmelCase					:					str								=							BlipaProcessor(tokenizer=snake_case__		,					image_processor=snake_case__						)

									lowerCAmelCase					:					List[str]								=							"lower newer"
									lowerCAmelCase					:					List[Any]								=							self.prepare_image_inputs()

									lowerCAmelCase					:					List[str]								=							processor(text=snake_case__		,					images=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(snake_case__						):
											processor()

							def 	lowercase__							(						self						):






									"""simple docstring"""





									lowerCAmelCase					:					Optional[int]								=							self.get_image_processor()
									lowerCAmelCase					:					str								=							self.get_tokenizer()

									lowerCAmelCase					:					Optional[Any]								=							BlipaProcessor(tokenizer=snake_case__		,					image_processor=snake_case__						)

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

									lowerCAmelCase					:					Dict								=							processor.batch_decode(snake_case__						)
									lowerCAmelCase					:					Union[str, Any]								=							tokenizer.batch_decode(snake_case__						)

									self.assertListEqual(snake_case__		,					snake_case__						)







							def 	lowercase__							(						self						):






									"""simple docstring"""





									lowerCAmelCase					:					int								=							self.get_image_processor()
									lowerCAmelCase					:					Dict								=							self.get_tokenizer()

									lowerCAmelCase					:					List[str]								=							BlipaProcessor(tokenizer=snake_case__		,					image_processor=snake_case__						)

									lowerCAmelCase					:					int								=							"lower newer"
									lowerCAmelCase					:					List[Any]								=							self.prepare_image_inputs()

									lowerCAmelCase					:					Any								=							processor(text=snake_case__		,					images=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__      (    SCREAMING_SNAKE_CASE   :   list[int]    ):


  '''simple docstring'''







  lowerCAmelCase					:					str								=							len(SCREAMING_SNAKE_CASE    )
  for i in range(SCREAMING_SNAKE_CASE    ):
    for j in range(i + 1    ,				SCREAMING_SNAKE_CASE    ):
      if numbers[j] < numbers[i]:
        lowerCAmelCase						,  lowerCAmelCase					:					Any								=							numbers[j], numbers[i]
  return numbers


if __name__ == "__main__":
     lowerCAmelCase__				    =       input('''Enter numbers separated by a comma:\n''').strip()
     lowerCAmelCase__				    =       [int(item) for item in user_input.split(''',''')]
     print(exchange_sort(unsorted))





