

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   A__     (				self					)  -> int:
        '''simple docstring'''






        _lowercase	       =tempfile.mkdtemp()

        _lowercase	       =[
            '[UNK]',
            '[CLS]',
            '[SEP]',
            '[PAD]',
            '[MASK]',
            '的',
            '价',
            '格',
            '是',
            '15',
            '便',
            'alex',
            '##andra',
            '，',
            '。',
            '-',
            't',
            'shirt',
        ]
        _lowercase	       =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]					)					)

        _lowercase	       ={
            'do_resize': True,
            'size': {'height': 224, 'width': 224},
            'do_center_crop': True,
            'crop_size': {'height': 18, 'width': 18},
            'do_normalize': True,
            'image_mean': [0.48145466, 0.4578275, 0.40821073],
            'image_std': [0.26862954, 0.26130258, 0.27577711],
            'do_convert_rgb': True,
        }
        _lowercase	       =os.path.join(self.tmpdirname							,   lowerCAmelCase					)
        with open(self.image_processor_file							,   'w'							,   encoding='utf-8'					) as fp:
              json.dump(lowerCAmelCase							,   lowerCAmelCase					)




  def   A__     (				self							,   **lowerCAmelCase					)  -> Union[str, Any]:
        '''simple docstring'''






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




  def   A__     (				self							,   **lowerCAmelCase					)  -> str:
        '''simple docstring'''






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




  def   A__     (				self							,   **lowerCAmelCase					)  -> Any:
        '''simple docstring'''






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




  def   A__     (				self					)  -> Optional[int]:
        '''simple docstring'''






        shutil.rmtree(self.tmpdirname					)




  def   A__     (				self					)  -> Optional[Any]:
        '''simple docstring'''






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

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

        return image_inputs




  def   A__     (				self					)  -> Tuple:
        '''simple docstring'''






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

        _lowercase	       =ChineseCLIPProcessor(tokenizer=lowerCAmelCase							,   image_processor=lowerCAmelCase					)
        processor_slow.save_pretrained(self.tmpdirname					)
        _lowercase	       =ChineseCLIPProcessor.from_pretrained(self.tmpdirname							,   use_fast=lowerCAmelCase					)

        _lowercase	       =ChineseCLIPProcessor(tokenizer=lowerCAmelCase							,   image_processor=lowerCAmelCase					)
        processor_fast.save_pretrained(self.tmpdirname					)
        _lowercase	       =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							,   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   A__     (				self					)  -> str:
        '''simple docstring'''






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

        _lowercase	       =self.get_tokenizer(cls_token='(CLS)'							,   sep_token='(SEP)'					)
        _lowercase	       =self.get_image_processor(do_normalize=lowerCAmelCase					)

        _lowercase	       =ChineseCLIPProcessor.from_pretrained(
            self.tmpdirname							,   cls_token='(CLS)'							,   sep_token='(SEP)'							,   do_normalize=lowerCAmelCase					)

        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   A__     (				self					)  -> Any:
        '''simple docstring'''






        _lowercase	       =self.get_image_processor()
        _lowercase	       =self.get_tokenizer()

        _lowercase	       =ChineseCLIPProcessor(tokenizer=lowerCAmelCase							,   image_processor=lowerCAmelCase					)

        _lowercase	       =self.prepare_image_inputs()

        _lowercase	       =image_processor(lowerCAmelCase							,   return_tensors='np'					)
        _lowercase	       =processor(images=lowerCAmelCase							,   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   A__     (				self					)  -> Tuple:
        '''simple docstring'''






        _lowercase	       =self.get_image_processor()
        _lowercase	       =self.get_tokenizer()

        _lowercase	       =ChineseCLIPProcessor(tokenizer=lowerCAmelCase							,   image_processor=lowerCAmelCase					)

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

        _lowercase	       =processor(text=lowerCAmelCase					)

        _lowercase	       =tokenizer(lowerCAmelCase					)

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




  def   A__     (				self					)  -> Union[str, Any]:
        '''simple docstring'''






        _lowercase	       =self.get_image_processor()
        _lowercase	       =self.get_tokenizer()

        _lowercase	       =ChineseCLIPProcessor(tokenizer=lowerCAmelCase							,   image_processor=lowerCAmelCase					)

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

        _lowercase	       =processor(text=lowerCAmelCase							,   images=lowerCAmelCase					)

        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(lowerCAmelCase					):
              processor()




  def   A__     (				self					)  -> str:
        '''simple docstring'''






        _lowercase	       =self.get_image_processor()
        _lowercase	       =self.get_tokenizer()

        _lowercase	       =ChineseCLIPProcessor(tokenizer=lowerCAmelCase							,   image_processor=lowerCAmelCase					)

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

        _lowercase	       =processor.batch_decode(lowerCAmelCase					)
        _lowercase	       =tokenizer.batch_decode(lowerCAmelCase					)

        self.assertListEqual(lowerCAmelCase							,   lowerCAmelCase					)




  def   A__     (				self					)  -> List[str]:
        '''simple docstring'''






        _lowercase	       =self.get_image_processor()
        _lowercase	       =self.get_tokenizer()

        _lowercase	       =ChineseCLIPProcessor(tokenizer=lowerCAmelCase							,   image_processor=lowerCAmelCase					)

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

        _lowercase	       =processor(text=lowerCAmelCase							,   images=lowerCAmelCase					)

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





def 					__lowerCamelCase	( UpperCamelCase__      ):







							'''simple docstring'''






							if edge <= 0 or not isinstance(UpperCamelCase__   ,							UpperCamelCase__      ):
														raise ValueError('Length must be a positive.'      )
							return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)





def 					__lowerCamelCase	( UpperCamelCase__      ):







							'''simple docstring'''






							if edge <= 0 or not isinstance(UpperCamelCase__   ,							UpperCamelCase__      ):
														raise ValueError('Length must be a positive.'      )
							return ((15 + (7 * (5 ** (1 / 2)))) / 4) * (edge**3)


if __name__ == "__main__":
					import doctest

					doctest.testmod()




