



"""simple docstring"""




def 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						int    )  ->       bool:





     '''simple docstring'''

     if not isinstance(SCREAMING_SNAKE_CASE__						,  SCREAMING_SNAKE_CASE__    ):
          _UpperCAmelCase      :     Optional[int]        =   f'Input value of [number={number}] must be an integer'
          raise TypeError(SCREAMING_SNAKE_CASE__    )
     if number < 0:
          return False
     _UpperCAmelCase      :     Tuple        =   number * number
     while number > 0:
          if number % 10 != number_square % 10:
               return False
          number //= 10
          number_square //= 10
     return True


if __name__ == "__main__":
 import doctest

 doctest.testmod()





"""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						):



      def 						snake_case_ (					self					:     List[Any]						):
           _UpperCAmelCase      :     List[str]        =   tempfile.mkdtemp()

           # fmt: off
           _UpperCAmelCase      :     Union[str, 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
           _UpperCAmelCase      :     List[Any]        =   dict(zip(A					,     range(len(A						)						)						)						)
           _UpperCAmelCase      :     Union[str, Any]        =   ["#version: 0.2", "l o", "lo w</w>", "e r</w>", ""]
           _UpperCAmelCase      :     Optional[int]        =   {"unk_token": "<unk>"}

           _UpperCAmelCase      :     Optional[Any]        =   os.path.join(self.tmpdirname					,     VOCAB_FILES_NAMES["vocab_file"]						)
           _UpperCAmelCase      :     Optional[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(A						) + "\n"						)
           with open(self.merges_file					,     "w"					,     encoding="utf-8"						) as fp:
                fp.write("\n".join(A						)						)

           _UpperCAmelCase      :     List[str]        =   {
               "do_resize": True,
               "size": 2_0,
               "do_center_crop": True,
               "crop_size": 1_8,
               "do_normalize": True,
               "image_mean": [0.48_145_466, 0.4_578_275, 0.40_821_073],
               "image_std": [0.26_862_954, 0.26_130_258, 0.27_577_711],
           }
           _UpperCAmelCase      :     Any        =   os.path.join(self.tmpdirname					,     A						)
           with open(self.image_processor_file					,     "w"					,     encoding="utf-8"						) as fp:
                json.dump(A					,     A						)



      def 						snake_case_ (					self					:     List[Any]					,     **A					:     Union[str, Any]						):
           return CLIPTokenizer.from_pretrained(self.tmpdirname					,     **A						)



      def 						snake_case_ (					self					:     int					,     **A					:     Any						):
           return CLIPTokenizerFast.from_pretrained(self.tmpdirname					,     **A						)



      def 						snake_case_ (					self					:     List[str]					,     **A					:     Optional[Any]						):
           return CLIPImageProcessor.from_pretrained(self.tmpdirname					,     **A						)



      def 						snake_case_ (					self					:     Optional[int]						):
           shutil.rmtree(self.tmpdirname						)



      def 						snake_case_ (					self					:     str						):
           _UpperCAmelCase      :     int        =   [np.random.randint(2_5_5					,     size=(3, 3_0, 4_0_0)					,     dtype=np.uinta						)]

           _UpperCAmelCase      :     Dict        =   [Image.fromarray(np.moveaxis(A					,     0					,     -1						)						) for x in image_inputs]

           return image_inputs



      def 						snake_case_ (					self					:     List[str]						):
           _UpperCAmelCase      :     int        =   self.get_tokenizer()
           _UpperCAmelCase      :     Dict        =   self.get_rust_tokenizer()
           _UpperCAmelCase      :     int        =   self.get_image_processor()

           _UpperCAmelCase      :     List[Any]        =   CLIPProcessor(tokenizer=A					,     image_processor=A						)
           processor_slow.save_pretrained(self.tmpdirname						)
           _UpperCAmelCase      :     Optional[Any]        =   CLIPProcessor.from_pretrained(self.tmpdirname					,     use_fast=A						)

           _UpperCAmelCase      :     Optional[Any]        =   CLIPProcessor(tokenizer=A					,     image_processor=A						)
           processor_fast.save_pretrained(self.tmpdirname						)
           _UpperCAmelCase      :     Optional[int]        =   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					,     A						)
           self.assertIsInstance(processor_fast.tokenizer					,     A						)

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



      def 						snake_case_ (					self					:     List[str]						):
           _UpperCAmelCase      :     List[str]        =   CLIPProcessor(tokenizer=self.get_tokenizer()					,     image_processor=self.get_image_processor()						)
           processor.save_pretrained(self.tmpdirname						)

           _UpperCAmelCase      :     Any        =   self.get_tokenizer(bos_token="(BOS)"					,     eos_token="(EOS)"						)
           _UpperCAmelCase      :     Any        =   self.get_image_processor(do_normalize=A					,     padding_value=1.0						)

           _UpperCAmelCase      :     Any        =   CLIPProcessor.from_pretrained(
               self.tmpdirname					,     bos_token="(BOS)"					,     eos_token="(EOS)"					,     do_normalize=A					,     padding_value=1.0						)

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

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



      def 						snake_case_ (					self					:     List[Any]						):
           _UpperCAmelCase      :     str        =   self.get_image_processor()
           _UpperCAmelCase      :     List[str]        =   self.get_tokenizer()

           _UpperCAmelCase      :     Any        =   CLIPProcessor(tokenizer=A					,     image_processor=A						)

           _UpperCAmelCase      :     Dict        =   self.prepare_image_inputs()

           _UpperCAmelCase      :     Optional[int]        =   image_processor(A					,     return_tensors="np"						)
           _UpperCAmelCase      :     Any        =   processor(images=A					,     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 						snake_case_ (					self					:     str						):
           _UpperCAmelCase      :     Tuple        =   self.get_image_processor()
           _UpperCAmelCase      :     int        =   self.get_tokenizer()

           _UpperCAmelCase      :     List[str]        =   CLIPProcessor(tokenizer=A					,     image_processor=A						)

           _UpperCAmelCase      :     Optional[int]        =   "lower newer"

           _UpperCAmelCase      :     Union[str, Any]        =   processor(text=A						)

           _UpperCAmelCase      :     Optional[int]        =   tokenizer(A						)

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



      def 						snake_case_ (					self					:     List[str]						):
           _UpperCAmelCase      :     Union[str, Any]        =   self.get_image_processor()
           _UpperCAmelCase      :     Tuple        =   self.get_tokenizer()

           _UpperCAmelCase      :     str        =   CLIPProcessor(tokenizer=A					,     image_processor=A						)

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

           _UpperCAmelCase      :     str        =   processor(text=A					,     images=A						)

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

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



      def 						snake_case_ (					self					:     int						):
           _UpperCAmelCase      :     List[str]        =   self.get_image_processor()
           _UpperCAmelCase      :     Dict        =   self.get_tokenizer()

           _UpperCAmelCase      :     List[Any]        =   CLIPProcessor(tokenizer=A					,     image_processor=A						)

           _UpperCAmelCase      :     str        =   [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

           _UpperCAmelCase      :     List[str]        =   processor.batch_decode(A						)
           _UpperCAmelCase      :     int        =   tokenizer.batch_decode(A						)

           self.assertListEqual(A					,     A						)



      def 						snake_case_ (					self					:     Optional[int]						):
           _UpperCAmelCase      :     Optional[Any]        =   self.get_image_processor()
           _UpperCAmelCase      :     int        =   self.get_tokenizer()

           _UpperCAmelCase      :     int        =   CLIPProcessor(tokenizer=A					,     image_processor=A						)

           _UpperCAmelCase      :     str        =   "lower newer"
           _UpperCAmelCase      :     int        =   self.prepare_image_inputs()

           _UpperCAmelCase      :     Optional[Any]        =   processor(text=A					,     images=A						)

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