
import re

from filelock import FileLock


try:
	import nltk

	UpperCAmelCase	      = True
except (ImportError, ModuleNotFoundError):
	UpperCAmelCase	      = False

if NLTK_AVAILABLE:
	with FileLock('''.lock''') as lock:
		nltk.download('''punkt''', quiet=True)






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE							):
	re.sub('<n>' ,							'' ,							__SCREAMING_SNAKE_CASE							)  # remove pegasus newline char
	assert NLTK_AVAILABLE, "nltk must be installed to separate newlines between sentences. (pip install nltk)"
	return "\n".join(nltk.sent_tokenize(__SCREAMING_SNAKE_CASE							)							)



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        A_   (			unittest.TestCase   ):




	'''simple docstring'''


	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		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': [0.48_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       =    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       ):
		return BertTokenizer.from_pretrained(self.tmpdirname		,    **snake_case       )





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





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





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





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

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

		return image_inputs





	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		lowercase       =    self.get_tokenizer()
		lowercase       =    self.get_rust_tokenizer()
		lowercase       =    self.get_image_processor()

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

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

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

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

		lowercase       =    self.prepare_image_inputs()

		lowercase       =    image_processor(snake_case		,    return_tensors='np'       )
		lowercase       =    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       ):
		lowercase       =    self.get_image_processor()
		lowercase       =    self.get_tokenizer()

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

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

		lowercase       =    processor(text=snake_case       )

		lowercase       =    tokenizer(snake_case       )

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





	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		lowercase       =    self.get_image_processor()
		lowercase       =    self.get_tokenizer()

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

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

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

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

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

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

		self.assertListEqual(snake_case		,    snake_case       )





	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		lowercase       =    self.get_image_processor()
		lowercase       =    self.get_tokenizer()

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

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

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

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

