


'''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    ):





    """simple docstring"""






    def  lowercase_							(				self      )							->	Optional[int]:
         __lowerCamelCase  :      Any														=						tempfile.mkdtemp()

         # fmt: off
         __lowerCamelCase  :      Optional[Any]														=						['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
         __lowerCamelCase  :      str														=						dict(zip(SCREAMING_SNAKE_CASE_     ,	range(len(SCREAMING_SNAKE_CASE_      )      )      )      )
         __lowerCamelCase  :      Tuple														=						['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>', '']
         __lowerCamelCase  :      str														=						{'unk_token': '<unk>'}

         __lowerCamelCase  :      Any														=						os.path.join(self.tmpdirname     ,	VOCAB_FILES_NAMES['vocab_file']      )
         __lowerCamelCase  :      Union[str, 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(SCREAMING_SNAKE_CASE_      ) + '\n'      )
         with open(self.merges_file     ,	'w'     ,	encoding='utf-8'      ) as fp:
              fp.write('\n'.join(SCREAMING_SNAKE_CASE_      )      )

         __lowerCamelCase  :      Union[str, 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],
         }
         __lowerCamelCase  :      Optional[Any]														=						os.path.join(self.tmpdirname     ,	SCREAMING_SNAKE_CASE_      )
         with open(self.image_processor_file     ,	'w'     ,	encoding='utf-8'      ) as fp:
              json.dump(SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_      )







    def  lowercase_							(				self     ,	**SCREAMING_SNAKE_CASE_      )							->	Tuple:
         return CLIPTokenizer.from_pretrained(self.tmpdirname     ,	**SCREAMING_SNAKE_CASE_      )







    def  lowercase_							(				self     ,	**SCREAMING_SNAKE_CASE_      )							->	Union[str, Any]:
         return CLIPTokenizerFast.from_pretrained(self.tmpdirname     ,	**SCREAMING_SNAKE_CASE_      )







    def  lowercase_							(				self     ,	**SCREAMING_SNAKE_CASE_      )							->	Union[str, Any]:
         return CLIPImageProcessor.from_pretrained(self.tmpdirname     ,	**SCREAMING_SNAKE_CASE_      )







    def  lowercase_							(				self      )							->	int:
         shutil.rmtree(self.tmpdirname      )







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

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

         return image_inputs







    def  lowercase_							(				self      )							->	Tuple:
         __lowerCamelCase  :      str														=						self.get_tokenizer()
         __lowerCamelCase  :      Any														=						self.get_rust_tokenizer()
         __lowerCamelCase  :      int														=						self.get_image_processor()

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

         __lowerCamelCase  :      Optional[Any]														=						CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )
         processor_fast.save_pretrained(self.tmpdirname      )
         __lowerCamelCase  :      Dict														=						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     ,	SCREAMING_SNAKE_CASE_      )
         self.assertIsInstance(processor_fast.tokenizer     ,	SCREAMING_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     ,	SCREAMING_SNAKE_CASE_      )
         self.assertIsInstance(processor_fast.image_processor     ,	SCREAMING_SNAKE_CASE_      )







    def  lowercase_							(				self      )							->	Dict:
         __lowerCamelCase  :      Tuple														=						CLIPProcessor(tokenizer=self.get_tokenizer()     ,	image_processor=self.get_image_processor()      )
         processor.save_pretrained(self.tmpdirname      )

         __lowerCamelCase  :      Any														=						self.get_tokenizer(bos_token='(BOS)'     ,	eos_token='(EOS)'      )
         __lowerCamelCase  :      Any														=						self.get_image_processor(do_normalize=SCREAMING_SNAKE_CASE_     ,	padding_value=1.0      )

         __lowerCamelCase  :      Optional[Any]														=						CLIPProcessor.from_pretrained(
             self.tmpdirname     ,	bos_token='(BOS)'     ,	eos_token='(EOS)'     ,	do_normalize=SCREAMING_SNAKE_CASE_     ,	padding_value=1.0      )

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

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







    def  lowercase_							(				self      )							->	str:
         __lowerCamelCase  :      Union[str, Any]														=						self.get_image_processor()
         __lowerCamelCase  :      Dict														=						self.get_tokenizer()

         __lowerCamelCase  :      Optional[Any]														=						CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      int														=						self.prepare_image_inputs()

         __lowerCamelCase  :      List[Any]														=						image_processor(SCREAMING_SNAKE_CASE_     ,	return_tensors='np'      )
         __lowerCamelCase  :      Tuple														=						processor(images=SCREAMING_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  lowercase_							(				self      )							->	Any:
         __lowerCamelCase  :      Dict														=						self.get_image_processor()
         __lowerCamelCase  :      Any														=						self.get_tokenizer()

         __lowerCamelCase  :      str														=						CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Optional[int]														=						'lower newer'

         __lowerCamelCase  :      Optional[int]														=						processor(text=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      int														=						tokenizer(SCREAMING_SNAKE_CASE_      )

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







    def  lowercase_							(				self      )							->	List[Any]:
         __lowerCamelCase  :      Dict														=						self.get_image_processor()
         __lowerCamelCase  :      Optional[int]														=						self.get_tokenizer()

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

         __lowerCamelCase  :      Dict														=						'lower newer'
         __lowerCamelCase  :      Optional[Any]														=						self.prepare_image_inputs()

         __lowerCamelCase  :      Any														=						processor(text=SCREAMING_SNAKE_CASE_     ,	images=SCREAMING_SNAKE_CASE_      )

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

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







    def  lowercase_							(				self      )							->	int:
         __lowerCamelCase  :      Tuple														=						self.get_image_processor()
         __lowerCamelCase  :      Any														=						self.get_tokenizer()

         __lowerCamelCase  :      Tuple														=						CLIPProcessor(tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Optional[Any]														=						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         __lowerCamelCase  :      Tuple														=						processor.batch_decode(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      List[Any]														=						tokenizer.batch_decode(SCREAMING_SNAKE_CASE_      )

         self.assertListEqual(SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_      )







    def  lowercase_							(				self      )							->	str:
         __lowerCamelCase  :      int														=						self.get_image_processor()
         __lowerCamelCase  :      Union[str, Any]														=						self.get_tokenizer()

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

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

         __lowerCamelCase  :      List[str]														=						processor(text=SCREAMING_SNAKE_CASE_     ,	images=SCREAMING_SNAKE_CASE_      )

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










'''simple docstring'''



from __future__ import annotations

A__						:   int				=    10



def      UpperCAmelCase__   (      UpperCAmelCase_       :							list[int]				)	->						list[int]:
     __lowerCamelCase  :      List[Any]														=						1
     __lowerCamelCase  :      Any														=						max(UpperCAmelCase_				)
     while placement <= max_digit:
          # declare and initialize empty buckets
          __lowerCamelCase  :      list[list]														=						[[] for _ in range(UpperCAmelCase_				)]
          # split list_of_ints between the buckets
          for i in list_of_ints:
               __lowerCamelCase  :      List[Any]														=						int((i / placement) % RADIX				)
               buckets[tmp].append(UpperCAmelCase_				)
          # put each buckets' contents into list_of_ints
          __lowerCamelCase  :      Tuple														=						0
          for b in range(UpperCAmelCase_				):
               for i in buckets[b]:
                    __lowerCamelCase  :      List[Any]														=						i
                    a += 1
        # move to next
          placement *= RADIX
     return list_of_ints


if __name__ == "__main__":
      import doctest

      doctest.testmod()






