import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
				from PIL import Image

				from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor
@require_vision
class     UpperCamelCase__(			unittest.TestCase ):





						def 				snake_case__	(       self     )					->				int:
													A__	     =							tempfile.mkdtemp()

													A__	     =							[
													    '[UNK]',
													    '[CLS]',
													    '[SEP]',
													    '[PAD]',
													    '[MASK]',
													    '的',
													    '价',
													    '格',
													    '是',
													    '15',
													    '便',
													    'alex',
													    '##andra',
													    '，',
													    '。',
													    '-',
													    't',
													    'shirt',
													]
													A__	     =							os.path.join(self.tmpdirname		,VOCAB_FILES_NAMES['vocab_file']     )
													with open(self.vocab_file		,'w'		,encoding='utf-8'     ) as vocab_writer:
																				vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]     )     )

													A__	     =							{
													    'do_resize': True,
													    'size': {'height': 2_24, 'width': 2_24},
													    'do_center_crop': True,
													    'crop_size': {'height': 18, 'width': 18},
													    'do_normalize': True,
													    'image_mean': [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
													    'image_std': [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
													    'do_convert_rgb': True,
													}
													A__	     =							os.path.join(self.tmpdirname		,__UpperCAmelCase     )
													with open(self.image_processor_file		,'w'		,encoding='utf-8'     ) as fp:
																				json.dump(__UpperCAmelCase		,__UpperCAmelCase     )





						def 				snake_case__	(       self		,**__UpperCAmelCase     )					->				int:
													return BertTokenizer.from_pretrained(self.tmpdirname		,**__UpperCAmelCase     )





						def 				snake_case__	(       self		,**__UpperCAmelCase     )					->				List[str]:
													return BertTokenizerFast.from_pretrained(self.tmpdirname		,**__UpperCAmelCase     )





						def 				snake_case__	(       self		,**__UpperCAmelCase     )					->				Any:
													return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname		,**__UpperCAmelCase     )





						def 				snake_case__	(       self     )					->				Union[str, Any]:
													shutil.rmtree(self.tmpdirname     )





						def 				snake_case__	(       self     )					->				Optional[int]:
													A__	     =							[np.random.randint(2_55		,size=(3, 30, 4_00)		,dtype=np.uinta     )]

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

													return image_inputs





						def 				snake_case__	(       self     )					->				Optional[Any]:
													A__	     =							self.get_tokenizer()
													A__	     =							self.get_rust_tokenizer()
													A__	     =							self.get_image_processor()

													A__	     =							ChineseCLIPProcessor(tokenizer=__UpperCAmelCase		,image_processor=__UpperCAmelCase     )
													processor_slow.save_pretrained(self.tmpdirname     )
													A__	     =							ChineseCLIPProcessor.from_pretrained(self.tmpdirname		,use_fast=__UpperCAmelCase     )

													A__	     =							ChineseCLIPProcessor(tokenizer=__UpperCAmelCase		,image_processor=__UpperCAmelCase     )
													processor_fast.save_pretrained(self.tmpdirname     )
													A__	     =							ChineseCLIPProcessor.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		,__UpperCAmelCase     )
													self.assertIsInstance(processor_fast.tokenizer		,__UpperCAmelCase     )

													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		,__UpperCAmelCase     )
													self.assertIsInstance(processor_fast.image_processor		,__UpperCAmelCase     )





						def 				snake_case__	(       self     )					->				Optional[int]:
													A__	     =							ChineseCLIPProcessor(tokenizer=self.get_tokenizer()		,image_processor=self.get_image_processor()     )
													processor.save_pretrained(self.tmpdirname     )

													A__	     =							self.get_tokenizer(cls_token='(CLS)'		,sep_token='(SEP)'     )
													A__	     =							self.get_image_processor(do_normalize=__UpperCAmelCase     )

													A__	     =							ChineseCLIPProcessor.from_pretrained(
													    self.tmpdirname		,cls_token='(CLS)'		,sep_token='(SEP)'		,do_normalize=__UpperCAmelCase     )

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

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





						def 				snake_case__	(       self     )					->				List[str]:
													A__	     =							self.get_image_processor()
													A__	     =							self.get_tokenizer()

													A__	     =							ChineseCLIPProcessor(tokenizer=__UpperCAmelCase		,image_processor=__UpperCAmelCase     )

													A__	     =							self.prepare_image_inputs()

													A__	     =							image_processor(__UpperCAmelCase		,return_tensors='np'     )
													A__	     =							processor(images=__UpperCAmelCase		,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 				snake_case__	(       self     )					->				int:
													A__	     =							self.get_image_processor()
													A__	     =							self.get_tokenizer()

													A__	     =							ChineseCLIPProcessor(tokenizer=__UpperCAmelCase		,image_processor=__UpperCAmelCase     )

													A__	     =							'Alexandra，T-shirt的价格是15便士。'

													A__	     =							processor(text=__UpperCAmelCase     )

													A__	     =							tokenizer(__UpperCAmelCase     )

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





						def 				snake_case__	(       self     )					->				List[str]:
													A__	     =							self.get_image_processor()
													A__	     =							self.get_tokenizer()

													A__	     =							ChineseCLIPProcessor(tokenizer=__UpperCAmelCase		,image_processor=__UpperCAmelCase     )

													A__	     =							'Alexandra，T-shirt的价格是15便士。'
													A__	     =							self.prepare_image_inputs()

													A__	     =							processor(text=__UpperCAmelCase		,images=__UpperCAmelCase     )

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

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





						def 				snake_case__	(       self     )					->				Optional[int]:
													A__	     =							self.get_image_processor()
													A__	     =							self.get_tokenizer()

													A__	     =							ChineseCLIPProcessor(tokenizer=__UpperCAmelCase		,image_processor=__UpperCAmelCase     )

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

													A__	     =							processor.batch_decode(__UpperCAmelCase     )
													A__	     =							tokenizer.batch_decode(__UpperCAmelCase     )

													self.assertListEqual(__UpperCAmelCase		,__UpperCAmelCase     )





						def 				snake_case__	(       self     )					->				Dict:
													A__	     =							self.get_image_processor()
													A__	     =							self.get_tokenizer()

													A__	     =							ChineseCLIPProcessor(tokenizer=__UpperCAmelCase		,image_processor=__UpperCAmelCase     )

													A__	     =							'Alexandra，T-shirt的价格是15便士。'
													A__	     =							self.prepare_image_inputs()

													A__	     =							processor(text=__UpperCAmelCase		,images=__UpperCAmelCase     )

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






"""simple docstring"""




def   UpperCAmelCase					(	UpperCamelCase__				):






							"""simple docstring"""





							A__     ,  A__	     =							[], []
							while len(UpperCamelCase__				) > 1:
														A__     ,  A__	     =							min(UpperCamelCase__				), max(UpperCamelCase__				)
														start.append(UpperCamelCase__				)
														end.append(UpperCamelCase__				)
														collection.remove(UpperCamelCase__				)
														collection.remove(UpperCamelCase__				)
							end.reverse()
							return start + collection + end


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





