
"""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 FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
      from PIL import Image

      from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor

@require_vision
class __lowerCAmelCase		(				unittest.TestCase      ):





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	tempfile.mkdtemp()

      __UpperCamelCase      =	[
          '[UNK]',
          '[CLS]',
          '[SEP]',
          '[PAD]',
          '[MASK]',
          '的',
          '价',
          '格',
          '是',
          '15',
          '便',
          'alex',
          '##andra',
          '，',
          '。',
          '-',
          't',
          'shirt',
      ]
      __UpperCamelCase      =	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      =	{
          'do_resize': True,
          'size': {'height': 224, 'width': 224},
          '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,
      }
      __UpperCamelCase      =	os.path.join(self.tmpdirname     ,					__UpperCAmelCase				)
      with open(self.image_processor_file     ,					'w'     ,					encoding='utf-8'				) as fp:
       json.dump(__UpperCAmelCase     ,					__UpperCAmelCase				)





     def 						UpperCAmelCase (     self     ,					**__UpperCAmelCase				):

      '''simple docstring'''




      return BertTokenizer.from_pretrained(self.tmpdirname     ,					**__UpperCAmelCase				)





     def 						UpperCAmelCase (     self     ,					**__UpperCAmelCase				):

      '''simple docstring'''




      return BertTokenizerFast.from_pretrained(self.tmpdirname     ,					**__UpperCAmelCase				)





     def 						UpperCAmelCase (     self     ,					**__UpperCAmelCase				):

      '''simple docstring'''




      return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname     ,					**__UpperCAmelCase				)





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      shutil.rmtree(self.tmpdirname				)





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	[np.random.randint(255     ,					size=(3, 30, 400)     ,					dtype=np.uinta				)]

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

      return image_inputs





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	self.get_tokenizer()
      __UpperCamelCase      =	self.get_rust_tokenizer()
      __UpperCamelCase      =	self.get_image_processor()

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

      __UpperCamelCase      =	ChineseCLIPProcessor(tokenizer=__UpperCAmelCase     ,					image_processor=__UpperCAmelCase				)
      processor_fast.save_pretrained(self.tmpdirname				)
      __UpperCamelCase      =	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 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	ChineseCLIPProcessor(tokenizer=self.get_tokenizer()     ,					image_processor=self.get_image_processor()				)
      processor.save_pretrained(self.tmpdirname				)

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

      __UpperCamelCase      =	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 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	self.get_image_processor()
      __UpperCamelCase      =	self.get_tokenizer()

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

      __UpperCamelCase      =	self.prepare_image_inputs()

      __UpperCamelCase      =	image_processor(__UpperCAmelCase     ,					return_tensors='np'				)
      __UpperCamelCase      =	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 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	self.get_image_processor()
      __UpperCamelCase      =	self.get_tokenizer()

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

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

      __UpperCamelCase      =	processor(text=__UpperCAmelCase				)

      __UpperCamelCase      =	tokenizer(__UpperCAmelCase				)

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





     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	self.get_image_processor()
      __UpperCamelCase      =	self.get_tokenizer()

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

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

      __UpperCamelCase      =	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 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	self.get_image_processor()
      __UpperCamelCase      =	self.get_tokenizer()

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

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

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

      self.assertListEqual(__UpperCAmelCase     ,					__UpperCAmelCase				)







     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




      __UpperCamelCase      =	self.get_image_processor()
      __UpperCamelCase      =	self.get_tokenizer()

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

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

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

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





"""simple docstring"""

from math import factorial

UpperCamelCase     :    List[Any]       =			{str(d): factorial(d) for d in range(1_0)}






def 							A						(    snake_case				:int		)				->     int:
 return sum(DIGIT_FACTORIAL[d] for d in str(snake_case		)		)






def 							A						(    )				->     int:
 __UpperCamelCase      =	7 * factorial(9		) + 1
 return sum(i for i in range(3    , snake_case		) if sum_of_digit_factorial(snake_case		) == i		)


if __name__ == "__main__":
      print(f'''{solution() = }''')



