


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   __a			(    unittest.TestCase      ):
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Optional[int]:




        '''simple docstring'''
        lowercase__:   List[Any]  			=   tempfile.mkdtemp()

        # fmt: off
        lowercase__:   Optional[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
        lowercase__:   int  			=   dict(zip(lowerCAmelCase__				, range(len(lowerCAmelCase__ ) ) ) )
        lowercase__:   Optional[int]  			=   ['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>', '']
        lowercase__:   Dict  			=   {'unk_token': '<unk>'}

        lowercase__:   Optional[Any]  			=   os.path.join(self.tmpdirname				, VOCAB_FILES_NAMES['vocab_file'] )
        lowercase__:   Tuple  			=   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__ ) )

        lowercase__:   Optional[Any]  			=   {
            'do_resize': True,
            'size': 20,
            'do_center_crop': True,
            'crop_size': 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],
        }
        lowercase__:   Dict  			=   os.path.join(self.tmpdirname				, lowerCAmelCase__ )
        with open(self.image_processor_file				, 'w'				, encoding='utf-8' ) as fp:
               json.dump(lowerCAmelCase__				, lowerCAmelCase__ )
 def 		SCREAMING_SNAKE_CASE__   (   self				, **lowerCAmelCase__ )					->				int:




        '''simple docstring'''
        return CLIPTokenizer.from_pretrained(self.tmpdirname				, **lowerCAmelCase__ )
 def 		SCREAMING_SNAKE_CASE__   (   self				, **lowerCAmelCase__ )					->				List[str]:




        '''simple docstring'''
        return CLIPTokenizerFast.from_pretrained(self.tmpdirname				, **lowerCAmelCase__ )
 def 		SCREAMING_SNAKE_CASE__   (   self				, **lowerCAmelCase__ )					->				int:




        '''simple docstring'''
        return CLIPImageProcessor.from_pretrained(self.tmpdirname				, **lowerCAmelCase__ )
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				str:




        '''simple docstring'''
        shutil.rmtree(self.tmpdirname )
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				str:




        '''simple docstring'''
        lowercase__:   Optional[int]  			=   [np.random.randint(255				, size=(3, 30, 400)				, dtype=np.uinta )]

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

        return image_inputs
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Optional[Any]:




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

        lowercase__:   Union[str, Any]  			=   CLIPProcessor(tokenizer=lowerCAmelCase__				, image_processor=lowerCAmelCase__ )
        processor_slow.save_pretrained(self.tmpdirname )
        lowercase__:   Union[str, Any]  			=   CLIPProcessor.from_pretrained(self.tmpdirname				, use_fast=lowerCAmelCase__ )

        lowercase__:   List[Any]  			=   CLIPProcessor(tokenizer=lowerCAmelCase__				, image_processor=lowerCAmelCase__ )
        processor_fast.save_pretrained(self.tmpdirname )
        lowercase__:   Tuple  			=   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 		SCREAMING_SNAKE_CASE__   (   self )					->				Union[str, Any]:




        '''simple docstring'''
        lowercase__:   Optional[int]  			=   CLIPProcessor(tokenizer=self.get_tokenizer()				, image_processor=self.get_image_processor() )
        processor.save_pretrained(self.tmpdirname )

        lowercase__:   List[str]  			=   self.get_tokenizer(bos_token='(BOS)'				, eos_token='(EOS)' )
        lowercase__:   str  			=   self.get_image_processor(do_normalize=lowerCAmelCase__				, padding_value=1.0 )

        lowercase__:   Tuple  			=   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 		SCREAMING_SNAKE_CASE__   (   self )					->				Tuple:




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

        lowercase__:   Any  			=   CLIPProcessor(tokenizer=lowerCAmelCase__				, image_processor=lowerCAmelCase__ )

        lowercase__:   Any  			=   self.prepare_image_inputs()

        lowercase__:   List[str]  			=   image_processor(lowerCAmelCase__				, return_tensors='np' )
        lowercase__:   List[Any]  			=   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 		SCREAMING_SNAKE_CASE__   (   self )					->				Any:




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

        lowercase__:   List[Any]  			=   CLIPProcessor(tokenizer=lowerCAmelCase__				, image_processor=lowerCAmelCase__ )

        lowercase__:   Union[str, Any]  			=   'lower newer'

        lowercase__:   str  			=   processor(text=lowerCAmelCase__ )

        lowercase__:   Union[str, Any]  			=   tokenizer(lowerCAmelCase__ )

        for key in encoded_tok.keys():
               self.assertListEqual(encoded_tok[key]				, encoded_processor[key] )
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Optional[Any]:




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

        lowercase__:   int  			=   CLIPProcessor(tokenizer=lowerCAmelCase__				, image_processor=lowerCAmelCase__ )

        lowercase__:   int  			=   'lower newer'
        lowercase__:   int  			=   self.prepare_image_inputs()

        lowercase__:   Dict  			=   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 		SCREAMING_SNAKE_CASE__   (   self )					->				Optional[Any]:




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

        lowercase__:   Dict  			=   CLIPProcessor(tokenizer=lowerCAmelCase__				, image_processor=lowerCAmelCase__ )

        lowercase__:   List[Any]  			=   [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        lowercase__:   Optional[Any]  			=   processor.batch_decode(lowerCAmelCase__ )
        lowercase__:   Tuple  			=   tokenizer.batch_decode(lowerCAmelCase__ )

        self.assertListEqual(lowerCAmelCase__				, lowerCAmelCase__ )
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Optional[int]:




        '''simple docstring'''
        lowercase__:   str  			=   self.get_image_processor()
        lowercase__:   Optional[int]  			=   self.get_tokenizer()

        lowercase__:   int  			=   CLIPProcessor(tokenizer=lowerCAmelCase__				, image_processor=lowerCAmelCase__ )

        lowercase__:   Tuple  			=   'lower newer'
        lowercase__:   List[str]  			=   self.prepare_image_inputs()

        lowercase__:   Any  			=   processor(text=lowerCAmelCase__				, images=lowerCAmelCase__ )

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






from __future__ import annotations




def    snake_case_     (  snake_case			,							snake_case     )  ->				bool:
       if len(snake_case     ) == 0:
              return False
       lowercase__:   Any  			=   len(snake_case     ) // 2
       if a_list[midpoint] == item:
              return True
       if item < a_list[midpoint]:
              return binary_search(a_list[:midpoint]			,							snake_case     )
       else:
              return binary_search(a_list[midpoint + 1 :]			,							snake_case     )


if __name__ == "__main__":
 __lowerCAmelCase		       =							input('''Enter numbers separated by comma:\n''').strip()
 __lowerCAmelCase		       =							[int(item.strip()) for item in user_input.split(''',''')]
 __lowerCAmelCase		       =							int(input('''Enter the number to be found in the list:\n''').strip())
 __lowerCAmelCase		       =							'''''' if binary_search(sequence, target) else '''not '''
 print(F'''{target} was {not_str}found in {sequence}''')


