






"""simple docstring"""



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 IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
 from PIL import Image

 from transformers import AlignProcessor, EfficientNetImageProcessor




@require_vision
class 			lowerCAmelCase__			(    unittest.TestCase   ):
   def       __a							(		self      :	Optional[Any]							):


        '''simple docstring'''
        UpperCAmelCase__						:    str							=							tempfile.mkdtemp()

        UpperCAmelCase__						:    Any							=							[
            "[UNK]",
            "[CLS]",
            "[SEP]",
            "[PAD]",
            "[MASK]",
            "want",
            "##want",
            "##ed",
            "wa",
            "un",
            "runn",
            "##ing",
            ",",
            "low",
            "lowest",
        ]
        UpperCAmelCase__						:    Dict							=							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]							)							)

        UpperCAmelCase__						:    Union[str, Any]							=							{
            "do_resize": True,
            "size": 2_0,
            "do_center_crop": True,
            "crop_size": 1_8,
            "do_normalize": True,
            "image_mean": [0.4814_5466, 0.457_8275, 0.4082_1073],
            "image_std": [0.2686_2954, 0.2613_0258, 0.2757_7711],
        }
        UpperCAmelCase__						:    Optional[Any]							=							os.path.join(self.tmpdirname							,			snake_case__							)
        with open(self.image_processor_file							,			"w"							,			encoding="utf-8"							) as fp:
             json.dump(snake_case__							,			snake_case__							)
   def       __a							(		self      :	Any							,			**snake_case__      :	Tuple							):


        '''simple docstring'''
        return BertTokenizer.from_pretrained(self.tmpdirname							,			**snake_case__							)
   def       __a							(		self      :	List[Any]							,			**snake_case__      :	Dict							):


        '''simple docstring'''
        return BertTokenizerFast.from_pretrained(self.tmpdirname							,			**snake_case__							)
   def       __a							(		self      :	Any							,			**snake_case__      :	str							):


        '''simple docstring'''
        return EfficientNetImageProcessor.from_pretrained(self.tmpdirname							,			**snake_case__							)
   def       __a							(		self      :	str							):


        '''simple docstring'''
        shutil.rmtree(self.tmpdirname							)
   def       __a							(		self      :	List[str]							):


        '''simple docstring'''
        UpperCAmelCase__						:    List[Any]							=							[np.random.randint(2_5_5							,			size=(3, 3_0, 4_0_0)							,			dtype=np.uinta							)]
        UpperCAmelCase__						:    List[Any]							=							[Image.fromarray(np.moveaxis(snake_case__							,			0							,			-1							)							) for x in image_inputs]
        return image_inputs
   def       __a							(		self      :	Optional[Any]							):


        '''simple docstring'''
        UpperCAmelCase__						:    Tuple							=							self.get_tokenizer()
        UpperCAmelCase__						:    Any							=							self.get_rust_tokenizer()
        UpperCAmelCase__						:    List[str]							=							self.get_image_processor()

        UpperCAmelCase__						:    Union[str, Any]							=							AlignProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)
        processor_slow.save_pretrained(self.tmpdirname							)
        UpperCAmelCase__						:    Union[str, Any]							=							AlignProcessor.from_pretrained(self.tmpdirname							,			use_fast=snake_case__							)

        UpperCAmelCase__						:    int							=							AlignProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)
        processor_fast.save_pretrained(self.tmpdirname							)
        UpperCAmelCase__						:    Dict							=							AlignProcessor.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							,			snake_case__							)
        self.assertIsInstance(processor_fast.tokenizer							,			snake_case__							)

        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							,			snake_case__							)
        self.assertIsInstance(processor_fast.image_processor							,			snake_case__							)
   def       __a							(		self      :	List[str]							):


        '''simple docstring'''
        UpperCAmelCase__						:    Tuple							=							AlignProcessor(tokenizer=self.get_tokenizer()							,			image_processor=self.get_image_processor()							)
        processor.save_pretrained(self.tmpdirname							)

        UpperCAmelCase__						:    List[str]							=							self.get_tokenizer(bos_token="(BOS)"							,			eos_token="(EOS)"							)
        UpperCAmelCase__						:    Tuple							=							self.get_image_processor(do_normalize=snake_case__							,			padding_value=1.0							)

        UpperCAmelCase__						:    List[str]							=							AlignProcessor.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       __a							(		self      :	List[Any]							):


        '''simple docstring'''
        UpperCAmelCase__						:    Any							=							self.get_image_processor()
        UpperCAmelCase__						:    Any							=							self.get_tokenizer()

        UpperCAmelCase__						:    Optional[Any]							=							AlignProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)

        UpperCAmelCase__						:    int							=							self.prepare_image_inputs()

        UpperCAmelCase__						:    str							=							image_processor(snake_case__							,			return_tensors="np"							)
        UpperCAmelCase__						:    Tuple							=							processor(images=snake_case__							,			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       __a							(		self      :	Dict							):


        '''simple docstring'''
        UpperCAmelCase__						:    int							=							self.get_image_processor()
        UpperCAmelCase__						:    List[str]							=							self.get_tokenizer()

        UpperCAmelCase__						:    Optional[int]							=							AlignProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)

        UpperCAmelCase__						:    Optional[Any]							=							"lower newer"

        UpperCAmelCase__						:    int							=							processor(text=snake_case__							)

        UpperCAmelCase__						:    str							=							tokenizer(snake_case__							,			padding="max_length"							,			max_length=6_4							)

        for key in encoded_tok.keys():
             self.assertListEqual(encoded_tok[key]							,			encoded_processor[key]							)
   def       __a							(		self      :	Optional[int]							):


        '''simple docstring'''
        UpperCAmelCase__						:    Union[str, Any]							=							self.get_image_processor()
        UpperCAmelCase__						:    Optional[Any]							=							self.get_tokenizer()

        UpperCAmelCase__						:    Optional[int]							=							AlignProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)

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

        UpperCAmelCase__						:    Any							=							processor(text=snake_case__							,			images=snake_case__							)

        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(snake_case__							):
             processor()
   def       __a							(		self      :	Union[str, Any]							):


        '''simple docstring'''
        UpperCAmelCase__						:    Dict							=							self.get_image_processor()
        UpperCAmelCase__						:    Dict							=							self.get_tokenizer()

        UpperCAmelCase__						:    int							=							AlignProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)

        UpperCAmelCase__						:    int							=							[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        UpperCAmelCase__						:    Optional[Any]							=							processor.batch_decode(snake_case__							)
        UpperCAmelCase__						:    List[str]							=							tokenizer.batch_decode(snake_case__							)

        self.assertListEqual(snake_case__							,			snake_case__							)




   def       __a							(		self      :	List[Any]							):


        '''simple docstring'''
        UpperCAmelCase__						:    Any							=							self.get_image_processor()
        UpperCAmelCase__						:    Optional[int]							=							self.get_tokenizer()

        UpperCAmelCase__						:    List[str]							=							AlignProcessor(tokenizer=snake_case__							,			image_processor=snake_case__							)

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

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

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










"""simple docstring"""



def 	SCREAMING_SNAKE_CASE__       (  snake_case       : Tuple				)->		str:






     '''simple docstring'''



     UpperCAmelCase__						:    List[str]							=							len(snake_case				)
     for i in range(length - 1				):
          UpperCAmelCase__						:    Any							=							i
          for k in range(i + 1			,					snake_case				):
               if collection[k] < collection[least]:
                    UpperCAmelCase__						:    Union[str, Any]							=							k
          if least != i:
               UpperCAmelCase__							,				UpperCAmelCase__						:    Union[str, Any]							=							(collection[i], collection[least])
     return collection


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


