






def 				_a     (   UpperCamelCase_    : Tuple      )       ->      Tuple:
						"""simple docstring"""







						return " ".join(input_str.split()[::-1]      )


if __name__ == "__main__":
	import doctest

	doctest.testmod()









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  lowercase				(       unittest.TestCase			):




				def     a							(					self       ):
											snake_case_							=    tempfile.mkdtemp()

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

											snake_case_							=    {
											    'do_resize': True,
											    'size': {'height': 224, 'width': 224},
											    'do_center_crop': True,
											    'crop_size': {'height': 18, 'width': 18},
											    'do_normalize': True,
											    'image_mean': [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73],
											    'image_std': [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11],
											    'do_convert_rgb': True,
											}
											snake_case_							=    os.path.join(self.tmpdirname      ,   snake_case       )
											with open(self.image_processor_file      ,   'w'      ,   encoding='utf-8'       ) as fp:
																		json.dump(snake_case      ,   snake_case       )




				def     a							(					self      ,   **snake_case       ):
											return BertTokenizer.from_pretrained(self.tmpdirname      ,   **snake_case       )




				def     a							(					self      ,   **snake_case       ):
											return BertTokenizerFast.from_pretrained(self.tmpdirname      ,   **snake_case       )




				def     a							(					self      ,   **snake_case       ):
											return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname      ,   **snake_case       )




				def     a							(					self       ):
											shutil.rmtree(self.tmpdirname       )




				def     a							(					self       ):
											snake_case_							=    [np.random.randint(255      ,   size=(3, 30, 400)      ,   dtype=np.uinta       )]

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

											return image_inputs




				def     a							(					self       ):
											snake_case_							=    self.get_tokenizer()
											snake_case_							=    self.get_rust_tokenizer()
											snake_case_							=    self.get_image_processor()

											snake_case_							=    ChineseCLIPProcessor(tokenizer=snake_case      ,   image_processor=snake_case       )
											processor_slow.save_pretrained(self.tmpdirname       )
											snake_case_							=    ChineseCLIPProcessor.from_pretrained(self.tmpdirname      ,   use_fast=snake_case       )

											snake_case_							=    ChineseCLIPProcessor(tokenizer=snake_case      ,   image_processor=snake_case       )
											processor_fast.save_pretrained(self.tmpdirname       )
											snake_case_							=    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      ,   snake_case       )
											self.assertIsInstance(processor_fast.tokenizer      ,   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      ,   snake_case       )
											self.assertIsInstance(processor_fast.image_processor      ,   snake_case       )




				def     a							(					self       ):
											snake_case_							=    ChineseCLIPProcessor(tokenizer=self.get_tokenizer()      ,   image_processor=self.get_image_processor()       )
											processor.save_pretrained(self.tmpdirname       )

											snake_case_							=    self.get_tokenizer(cls_token='(CLS)'      ,   sep_token='(SEP)'       )
											snake_case_							=    self.get_image_processor(do_normalize=snake_case       )

											snake_case_							=    ChineseCLIPProcessor.from_pretrained(
											    self.tmpdirname      ,   cls_token='(CLS)'      ,   sep_token='(SEP)'      ,   do_normalize=snake_case       )

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

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




				def     a							(					self       ):
											snake_case_							=    self.get_image_processor()
											snake_case_							=    self.get_tokenizer()

											snake_case_							=    ChineseCLIPProcessor(tokenizer=snake_case      ,   image_processor=snake_case       )

											snake_case_							=    self.prepare_image_inputs()

											snake_case_							=    image_processor(snake_case      ,   return_tensors='np'       )
											snake_case_							=    processor(images=snake_case      ,   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       ):
											snake_case_							=    self.get_image_processor()
											snake_case_							=    self.get_tokenizer()

											snake_case_							=    ChineseCLIPProcessor(tokenizer=snake_case      ,   image_processor=snake_case       )

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

											snake_case_							=    processor(text=snake_case       )

											snake_case_							=    tokenizer(snake_case       )

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




				def     a							(					self       ):
											snake_case_							=    self.get_image_processor()
											snake_case_							=    self.get_tokenizer()

											snake_case_							=    ChineseCLIPProcessor(tokenizer=snake_case      ,   image_processor=snake_case       )

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

											snake_case_							=    processor(text=snake_case      ,   images=snake_case       )

											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(snake_case       ):
																		processor()




				def     a							(					self       ):
											snake_case_							=    self.get_image_processor()
											snake_case_							=    self.get_tokenizer()

											snake_case_							=    ChineseCLIPProcessor(tokenizer=snake_case      ,   image_processor=snake_case       )

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

											snake_case_							=    processor.batch_decode(snake_case       )
											snake_case_							=    tokenizer.batch_decode(snake_case       )

											self.assertListEqual(snake_case      ,   snake_case       )




				def     a							(					self       ):
											snake_case_							=    self.get_image_processor()
											snake_case_							=    self.get_tokenizer()

											snake_case_							=    ChineseCLIPProcessor(tokenizer=snake_case      ,   image_processor=snake_case       )

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

											snake_case_							=    processor(text=snake_case      ,   images=snake_case       )

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




