
from abc import ABC, abstractmethod
from argparse import ArgumentParser

class __snake_case		(				lowerCAmelCase					):
    @staticmethod
    @abstractmethod
    def 				_SCREAMING_SNAKE_CASE	(  snake_case				):



           '''simple docstring'''







           raise NotImplementedError()
    @abstractmethod
    def 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           raise NotImplementedError()


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 __snake_case		(				unittest.TestCase					):
    def 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           lowercase							:					str	     =				tempfile.mkdtemp()

           lowercase							:					List[str]	     =				[
               """[UNK]""",
               """[CLS]""",
               """[SEP]""",
               """[PAD]""",
               """[MASK]""",
               """的""",
               """价""",
               """格""",
               """是""",
               """15""",
               """便""",
               """alex""",
               """##andra""",
               """，""",
               """。""",
               """-""",
               """t""",
               """shirt""",
           ]
           lowercase							:					Dict	     =				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							:					Any	     =				{
               """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_145_466, 0.4_578_275, 0.40_821_073],
               """image_std""": [0.26_862_954, 0.26_130_258, 0.27_577_711],
               """do_convert_rgb""": True,
           }
           lowercase							:					List[str]	     =				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 				_SCREAMING_SNAKE_CASE	(  self		,**snake_case				):



           '''simple docstring'''







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



           '''simple docstring'''







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



           '''simple docstring'''







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



           '''simple docstring'''







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



           '''simple docstring'''







           lowercase							:					Optional[int]	     =				[np.random.randint(255		,size=(3, 30, 400)		,dtype=np.uinta				)]

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

           return image_inputs
    def 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           lowercase							:					List[str]	     =				self.get_tokenizer()
           lowercase							:					Dict	     =				self.get_rust_tokenizer()
           lowercase							:					Union[str, Any]	     =				self.get_image_processor()

           lowercase							:					Optional[Any]	     =				ChineseCLIPProcessor(tokenizer=snake_case		,image_processor=snake_case				)
           processor_slow.save_pretrained(self.tmpdirname				)
           lowercase							:					Any	     =				ChineseCLIPProcessor.from_pretrained(self.tmpdirname		,use_fast=snake_case				)

           lowercase							:					List[Any]	     =				ChineseCLIPProcessor(tokenizer=snake_case		,image_processor=snake_case				)
           processor_fast.save_pretrained(self.tmpdirname				)
           lowercase							:					Tuple	     =				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 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           lowercase							:					List[Any]	     =				ChineseCLIPProcessor(tokenizer=self.get_tokenizer()		,image_processor=self.get_image_processor()				)
           processor.save_pretrained(self.tmpdirname				)

           lowercase							:					int	     =				self.get_tokenizer(cls_token="""(CLS)"""		,sep_token="""(SEP)"""				)
           lowercase							:					Dict	     =				self.get_image_processor(do_normalize=snake_case				)

           lowercase							:					Optional[Any]	     =				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 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           lowercase							:					str	     =				self.get_image_processor()
           lowercase							:					List[str]	     =				self.get_tokenizer()

           lowercase							:					Optional[Any]	     =				ChineseCLIPProcessor(tokenizer=snake_case		,image_processor=snake_case				)

           lowercase							:					Optional[int]	     =				self.prepare_image_inputs()

           lowercase							:					Tuple	     =				image_processor(snake_case		,return_tensors="""np"""				)
           lowercase							:					Optional[int]	     =				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 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           lowercase							:					str	     =				self.get_image_processor()
           lowercase							:					Union[str, Any]	     =				self.get_tokenizer()

           lowercase							:					Any	     =				ChineseCLIPProcessor(tokenizer=snake_case		,image_processor=snake_case				)

           lowercase							:					Any	     =				"""Alexandra，T-shirt的价格是15便士。"""

           lowercase							:					int	     =				processor(text=snake_case				)

           lowercase							:					Dict	     =				tokenizer(snake_case				)

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



           '''simple docstring'''







           lowercase							:					Optional[Any]	     =				self.get_image_processor()
           lowercase							:					Optional[Any]	     =				self.get_tokenizer()

           lowercase							:					Dict	     =				ChineseCLIPProcessor(tokenizer=snake_case		,image_processor=snake_case				)

           lowercase							:					List[str]	     =				"""Alexandra，T-shirt的价格是15便士。"""
           lowercase							:					Any	     =				self.prepare_image_inputs()

           lowercase							:					Optional[Any]	     =				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 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           lowercase							:					str	     =				self.get_image_processor()
           lowercase							:					str	     =				self.get_tokenizer()

           lowercase							:					Dict	     =				ChineseCLIPProcessor(tokenizer=snake_case		,image_processor=snake_case				)

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

           lowercase							:					Any	     =				processor.batch_decode(snake_case				)
           lowercase							:					str	     =				tokenizer.batch_decode(snake_case				)

           self.assertListEqual(snake_case		,snake_case				)
    def 				_SCREAMING_SNAKE_CASE	(  self				):



           '''simple docstring'''







           lowercase							:					Dict	     =				self.get_image_processor()
           lowercase							:					Dict	     =				self.get_tokenizer()

           lowercase							:					List[Any]	     =				ChineseCLIPProcessor(tokenizer=snake_case		,image_processor=snake_case				)

           lowercase							:					str	     =				"""Alexandra，T-shirt的价格是15便士。"""
           lowercase							:					Optional[Any]	     =				self.prepare_image_inputs()

           lowercase							:					Dict	     =				processor(text=snake_case		,images=snake_case				)

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