



"""simple docstring"""




import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
   from PIL import Image

   from transformers import CLIPImageProcessor, CLIPProcessor






@require_vision
class      UpperCAmelCase_  (    unittest.TestCase						):



      def 						snake_case_ (					self					:     Optional[Any]						):
           _UpperCAmelCase      :     List[str]        =   tempfile.mkdtemp()

           # fmt: off
           _UpperCAmelCase      :     int        =   ["""l""", """o""", """w""", """e""", """r""", """s""", """t""", """i""", """d""", """n""", """lo""", """l</w>""", """w</w>""", """r</w>""", """t</w>""", """low</w>""", """er</w>""", """lowest</w>""", """newer</w>""", """wider""", """<unk>""", """<|startoftext|>""", """<|endoftext|>"""]
           # fmt: on
           _UpperCAmelCase      :     Tuple        =   dict(zip(__lowerCamelCase					,     range(len(__lowerCamelCase						)						)						)						)
           _UpperCAmelCase      :     Union[str, Any]        =   ["""#version: 0.2""", """l o""", """lo w</w>""", """e r</w>""", """"""]
           _UpperCAmelCase      :     Optional[int]        =   {"""unk_token""": """<unk>"""}

           _UpperCAmelCase      :     Optional[int]        =   os.path.join(self.tmpdirname					,     VOCAB_FILES_NAMES["vocab_file"]						)
           _UpperCAmelCase      :     Any        =   os.path.join(self.tmpdirname					,     VOCAB_FILES_NAMES["merges_file"]						)
           with open(self.vocab_file					,     "w"					,     encoding="utf-8"						) as fp:
                fp.write(json.dumps(__lowerCamelCase						) + "\n"						)
           with open(self.merges_file					,     "w"					,     encoding="utf-8"						) as fp:
                fp.write("\n".join(__lowerCamelCase						)						)

           _UpperCAmelCase      :     Dict        =   {
               """do_resize""": True,
               """size""": 2_0,
               """do_center_crop""": True,
               """crop_size""": 1_8,
               """do_normalize""": True,
               """image_mean""": [0.48_145_466, 0.4_578_275, 0.40_821_073],
               """image_std""": [0.26_862_954, 0.26_130_258, 0.27_577_711],
           }
           _UpperCAmelCase      :     Union[str, Any]        =   os.path.join(self.tmpdirname					,     __lowerCamelCase						)
           with open(self.image_processor_file					,     "w"					,     encoding="utf-8"						) as fp:
                json.dump(__lowerCamelCase					,     __lowerCamelCase						)



      def 						snake_case_ (					self					:     str					,     **A					:     Union[str, Any]						):
           return CLIPTokenizer.from_pretrained(self.tmpdirname					,     **__lowerCamelCase						)



      def 						snake_case_ (					self					:     str					,     **A					:     List[str]						):
           return CLIPTokenizerFast.from_pretrained(self.tmpdirname					,     **__lowerCamelCase						)



      def 						snake_case_ (					self					:     List[Any]					,     **A					:     Any						):
           return CLIPImageProcessor.from_pretrained(self.tmpdirname					,     **__lowerCamelCase						)



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



      def 						snake_case_ (					self					:     Any						):
           _UpperCAmelCase      :     Union[str, Any]        =   [np.random.randint(2_5_5					,     size=(3, 3_0, 4_0_0)					,     dtype=np.uinta						)]

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

           return image_inputs



      def 						snake_case_ (					self					:     Optional[int]						):
           _UpperCAmelCase      :     List[str]        =   self.get_tokenizer()
           _UpperCAmelCase      :     List[Any]        =   self.get_rust_tokenizer()
           _UpperCAmelCase      :     Any        =   self.get_image_processor()

           _UpperCAmelCase      :     Optional[int]        =   CLIPProcessor(tokenizer=__lowerCamelCase					,     image_processor=__lowerCamelCase						)
           processor_slow.save_pretrained(self.tmpdirname						)
           _UpperCAmelCase      :     Any        =   CLIPProcessor.from_pretrained(self.tmpdirname					,     use_fast=__lowerCamelCase						)

           _UpperCAmelCase      :     Dict        =   CLIPProcessor(tokenizer=__lowerCamelCase					,     image_processor=__lowerCamelCase						)
           processor_fast.save_pretrained(self.tmpdirname						)
           _UpperCAmelCase      :     Union[str, Any]        =   CLIPProcessor.from_pretrained(self.tmpdirname						)

           self.assertEqual(processor_slow.tokenizer.get_vocab()					,     tokenizer_slow.get_vocab()						)
           self.assertEqual(processor_fast.tokenizer.get_vocab()					,     tokenizer_fast.get_vocab()						)
           self.assertEqual(tokenizer_slow.get_vocab()					,     tokenizer_fast.get_vocab()						)
           self.assertIsInstance(processor_slow.tokenizer					,     __lowerCamelCase						)
           self.assertIsInstance(processor_fast.tokenizer					,     __lowerCamelCase						)

           self.assertEqual(processor_slow.image_processor.to_json_string()					,     image_processor.to_json_string()						)
           self.assertEqual(processor_fast.image_processor.to_json_string()					,     image_processor.to_json_string()						)
           self.assertIsInstance(processor_slow.image_processor					,     __lowerCamelCase						)
           self.assertIsInstance(processor_fast.image_processor					,     __lowerCamelCase						)



      def 						snake_case_ (					self					:     int						):
           _UpperCAmelCase      :     Union[str, Any]        =   CLIPProcessor(tokenizer=self.get_tokenizer()					,     image_processor=self.get_image_processor()						)
           processor.save_pretrained(self.tmpdirname						)

           _UpperCAmelCase      :     Dict        =   self.get_tokenizer(bos_token="(BOS)"					,     eos_token="(EOS)"						)
           _UpperCAmelCase      :     Union[str, Any]        =   self.get_image_processor(do_normalize=__lowerCamelCase					,     padding_value=1.0						)

           _UpperCAmelCase      :     Union[str, Any]        =   CLIPProcessor.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 						snake_case_ (					self					:     Tuple						):
           _UpperCAmelCase      :     Dict        =   self.get_image_processor()
           _UpperCAmelCase      :     Dict        =   self.get_tokenizer()

           _UpperCAmelCase      :     List[str]        =   CLIPProcessor(tokenizer=__lowerCamelCase					,     image_processor=__lowerCamelCase						)

           _UpperCAmelCase      :     str        =   self.prepare_image_inputs()

           _UpperCAmelCase      :     List[Any]        =   image_processor(__lowerCamelCase					,     return_tensors="np"						)
           _UpperCAmelCase      :     Tuple        =   processor(images=__lowerCamelCase					,     return_tensors="np"						)

           for key in input_image_proc.keys():
                self.assertAlmostEqual(input_image_proc[key].sum()					,     input_processor[key].sum()					,     delta=1e-2						)



      def 						snake_case_ (					self					:     Dict						):
           _UpperCAmelCase      :     Any        =   self.get_image_processor()
           _UpperCAmelCase      :     Tuple        =   self.get_tokenizer()

           _UpperCAmelCase      :     int        =   CLIPProcessor(tokenizer=__lowerCamelCase					,     image_processor=__lowerCamelCase						)

           _UpperCAmelCase      :     Optional[int]        =   """lower newer"""

           _UpperCAmelCase      :     int        =   processor(text=__lowerCamelCase						)

           _UpperCAmelCase      :     Optional[Any]        =   tokenizer(__lowerCamelCase						)

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



      def 						snake_case_ (					self					:     Union[str, Any]						):
           _UpperCAmelCase      :     List[str]        =   self.get_image_processor()
           _UpperCAmelCase      :     List[str]        =   self.get_tokenizer()

           _UpperCAmelCase      :     Optional[int]        =   CLIPProcessor(tokenizer=__lowerCamelCase					,     image_processor=__lowerCamelCase						)

           _UpperCAmelCase      :     Optional[Any]        =   """lower newer"""
           _UpperCAmelCase      :     Union[str, Any]        =   self.prepare_image_inputs()

           _UpperCAmelCase      :     Optional[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 						snake_case_ (					self					:     Optional[int]						):
           _UpperCAmelCase      :     Dict        =   self.get_image_processor()
           _UpperCAmelCase      :     List[str]        =   self.get_tokenizer()

           _UpperCAmelCase      :     List[Any]        =   CLIPProcessor(tokenizer=__lowerCamelCase					,     image_processor=__lowerCamelCase						)

           _UpperCAmelCase      :     Tuple        =   [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

           _UpperCAmelCase      :     List[str]        =   processor.batch_decode(__lowerCamelCase						)
           _UpperCAmelCase      :     Dict        =   tokenizer.batch_decode(__lowerCamelCase						)

           self.assertListEqual(__lowerCamelCase					,     __lowerCamelCase						)



      def 						snake_case_ (					self					:     int						):
           _UpperCAmelCase      :     List[Any]        =   self.get_image_processor()
           _UpperCAmelCase      :     str        =   self.get_tokenizer()

           _UpperCAmelCase      :     int        =   CLIPProcessor(tokenizer=__lowerCamelCase					,     image_processor=__lowerCamelCase						)

           _UpperCAmelCase      :     Optional[int]        =   """lower newer"""
           _UpperCAmelCase      :     Optional[int]        =   self.prepare_image_inputs()

           _UpperCAmelCase      :     Union[str, Any]        =   processor(text=__lowerCamelCase					,     images=__lowerCamelCase						)

           self.assertListEqual(list(inputs.keys()						)					,     processor.model_input_names						)





"""simple docstring"""




def 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						list    )  ->       list:





     '''simple docstring'''

     if len(SCREAMING_SNAKE_CASE__    ) < 2:
          return collection

     def circle_sort_util(SCREAMING_SNAKE_CASE__     :						list						,  SCREAMING_SNAKE_CASE__     :						int						,  SCREAMING_SNAKE_CASE__     :						int    ) -> bool:
          _UpperCAmelCase      :     Dict        =   False

          if low == high:
               return swapped

          _UpperCAmelCase      :     str        =   low
          _UpperCAmelCase      :     Dict        =   high

          while left < right:
               if collection[left] > collection[right]:
                    _UpperCAmelCase    ,	_UpperCAmelCase      :     List[str]        =   (
                        collection[right],
                        collection[left],
                    )
                    _UpperCAmelCase      :     Optional[int]        =   True

               left += 1
               right -= 1

          if left == right and collection[left] > collection[right + 1]:
               _UpperCAmelCase    ,	_UpperCAmelCase      :     int        =   (
                   collection[right + 1],
                   collection[left],
               )

               _UpperCAmelCase      :     Union[str, Any]        =   True

          _UpperCAmelCase      :     Dict        =   low + int((high - low) / 2    )
          _UpperCAmelCase      :     Any        =   circle_sort_util(SCREAMING_SNAKE_CASE__						,  SCREAMING_SNAKE_CASE__						,  SCREAMING_SNAKE_CASE__    )
          _UpperCAmelCase      :     Optional[Any]        =   circle_sort_util(SCREAMING_SNAKE_CASE__						,  mid + 1						,  SCREAMING_SNAKE_CASE__    )

          return swapped or left_swap or right_swap

     _UpperCAmelCase      :     Tuple        =   True

     while is_not_sorted is True:
          _UpperCAmelCase      :     Dict        =   circle_sort_util(SCREAMING_SNAKE_CASE__						,  0						,  len(SCREAMING_SNAKE_CASE__    ) - 1    )

     return collection


if __name__ == "__main__":
 _lowerCAmelCase    : Dict							=							input("Enter numbers separated by a comma:\n").strip()
 _lowerCAmelCase    : Optional[Any]							=							[int(item) for item in user_input.split(",")]
 print(circle_sort(unsorted))
