






'''simple docstring'''







def 			SCREAMING_SNAKE_CASE_	(UpperCamelCase				)				->	bool:
							lowerCamelCase__ :     Union[str, Any]	  =	[int(UpperCamelCase				) for i in ip_va_address.split("""."""				) if i.isdigit()]
							return len(UpperCamelCase				) == 4 and all(0 <= int(UpperCamelCase				) <= 254 for octet in octets				)


if __name__ == "__main__":
			_A     :      List[str]   					=input().strip()
			_A     :      Any   					='''valid''' if is_ip_va_address_valid(ip) else '''invalid'''
			print(F'{ip} is a {valid_or_invalid} IP v4 address.')









'''simple docstring'''







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 		lowerCamelCase_    (							self:    Union[str, Any]					):
														lowerCamelCase__ :     Any	  =	tempfile.mkdtemp()

														lowerCamelCase__ :     Any	  =	[
														    """[UNK]""",
														    """[CLS]""",
														    """[SEP]""",
														    """[PAD]""",
														    """[MASK]""",
														    """的""",
														    """价""",
														    """格""",
														    """是""",
														    """15""",
														    """便""",
														    """alex""",
														    """##andra""",
														    """，""",
														    """。""",
														    """-""",
														    """t""",
														    """shirt""",
														]
														lowerCamelCase__ :     Optional[int]	  =	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]					)					)

														lowerCamelCase__ :     Union[str, 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,
														}
														lowerCamelCase__ :     Optional[int]	  =	os.path.join(self.tmpdirname      ,							UpperCamelCase__					)
														with open(self.image_processor_file      ,							"""w"""      ,							encoding="""utf-8"""					) as fp:
																					json.dump(UpperCamelCase__      ,							UpperCamelCase__					)




							def 		lowerCamelCase_    (							self:    List[Any]      ,							**UpperCamelCase__:    Optional[int]					):
														return BertTokenizer.from_pretrained(self.tmpdirname      ,							**UpperCamelCase__					)




							def 		lowerCamelCase_    (							self:    Any      ,							**UpperCamelCase__:    List[str]					):
														return BertTokenizerFast.from_pretrained(self.tmpdirname      ,							**UpperCamelCase__					)




							def 		lowerCamelCase_    (							self:    str      ,							**UpperCamelCase__:    int					):
														return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname      ,							**UpperCamelCase__					)




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




							def 		lowerCamelCase_    (							self:    List[str]					):
														lowerCamelCase__ :     int	  =	[np.random.randint(255      ,							size=(3, 30, 400)      ,							dtype=np.uinta					)]

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

														return image_inputs




							def 		lowerCamelCase_    (							self:    List[str]					):
														lowerCamelCase__ :     Tuple	  =	self.get_tokenizer()
														lowerCamelCase__ :     Any	  =	self.get_rust_tokenizer()
														lowerCamelCase__ :     str	  =	self.get_image_processor()

														lowerCamelCase__ :     str	  =	ChineseCLIPProcessor(tokenizer=UpperCamelCase__      ,							image_processor=UpperCamelCase__					)
														processor_slow.save_pretrained(self.tmpdirname					)
														lowerCamelCase__ :     List[Any]	  =	ChineseCLIPProcessor.from_pretrained(self.tmpdirname      ,							use_fast=UpperCamelCase__					)

														lowerCamelCase__ :     Any	  =	ChineseCLIPProcessor(tokenizer=UpperCamelCase__      ,							image_processor=UpperCamelCase__					)
														processor_fast.save_pretrained(self.tmpdirname					)
														lowerCamelCase__ :     List[Any]	  =	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      ,							UpperCamelCase__					)
														self.assertIsInstance(processor_fast.tokenizer      ,							UpperCamelCase__					)

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




							def 		lowerCamelCase_    (							self:    Optional[int]					):
														lowerCamelCase__ :     Optional[int]	  =	ChineseCLIPProcessor(tokenizer=self.get_tokenizer()      ,							image_processor=self.get_image_processor()					)
														processor.save_pretrained(self.tmpdirname					)

														lowerCamelCase__ :     str	  =	self.get_tokenizer(cls_token="""(CLS)"""      ,							sep_token="""(SEP)"""					)
														lowerCamelCase__ :     Optional[int]	  =	self.get_image_processor(do_normalize=UpperCamelCase__					)

														lowerCamelCase__ :     Optional[int]	  =	ChineseCLIPProcessor.from_pretrained(
														    self.tmpdirname      ,							cls_token="""(CLS)"""      ,							sep_token="""(SEP)"""      ,							do_normalize=UpperCamelCase__					)

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

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




							def 		lowerCamelCase_    (							self:    Tuple					):
														lowerCamelCase__ :     Optional[Any]	  =	self.get_image_processor()
														lowerCamelCase__ :     Optional[int]	  =	self.get_tokenizer()

														lowerCamelCase__ :     int	  =	ChineseCLIPProcessor(tokenizer=UpperCamelCase__      ,							image_processor=UpperCamelCase__					)

														lowerCamelCase__ :     Tuple	  =	self.prepare_image_inputs()

														lowerCamelCase__ :     str	  =	image_processor(UpperCamelCase__      ,							return_tensors="""np"""					)
														lowerCamelCase__ :     Optional[int]	  =	processor(images=UpperCamelCase__      ,							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 		lowerCamelCase_    (							self:    Tuple					):
														lowerCamelCase__ :     int	  =	self.get_image_processor()
														lowerCamelCase__ :     Optional[int]	  =	self.get_tokenizer()

														lowerCamelCase__ :     Union[str, Any]	  =	ChineseCLIPProcessor(tokenizer=UpperCamelCase__      ,							image_processor=UpperCamelCase__					)

														lowerCamelCase__ :     Union[str, Any]	  =	"""Alexandra，T-shirt的价格是15便士。"""

														lowerCamelCase__ :     Optional[Any]	  =	processor(text=UpperCamelCase__					)

														lowerCamelCase__ :     Optional[Any]	  =	tokenizer(UpperCamelCase__					)

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




							def 		lowerCamelCase_    (							self:    Optional[Any]					):
														lowerCamelCase__ :     Optional[int]	  =	self.get_image_processor()
														lowerCamelCase__ :     List[Any]	  =	self.get_tokenizer()

														lowerCamelCase__ :     Optional[Any]	  =	ChineseCLIPProcessor(tokenizer=UpperCamelCase__      ,							image_processor=UpperCamelCase__					)

														lowerCamelCase__ :     Dict	  =	"""Alexandra，T-shirt的价格是15便士。"""
														lowerCamelCase__ :     Any	  =	self.prepare_image_inputs()

														lowerCamelCase__ :     Optional[int]	  =	processor(text=UpperCamelCase__      ,							images=UpperCamelCase__					)

														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(UpperCamelCase__					):
																					processor()




							def 		lowerCamelCase_    (							self:    Dict					):
														lowerCamelCase__ :     Dict	  =	self.get_image_processor()
														lowerCamelCase__ :     Any	  =	self.get_tokenizer()

														lowerCamelCase__ :     Union[str, Any]	  =	ChineseCLIPProcessor(tokenizer=UpperCamelCase__      ,							image_processor=UpperCamelCase__					)

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

														lowerCamelCase__ :     Any	  =	processor.batch_decode(UpperCamelCase__					)
														lowerCamelCase__ :     int	  =	tokenizer.batch_decode(UpperCamelCase__					)

														self.assertListEqual(UpperCamelCase__      ,							UpperCamelCase__					)




							def 		lowerCamelCase_    (							self:    Optional[Any]					):
														lowerCamelCase__ :     Dict	  =	self.get_image_processor()
														lowerCamelCase__ :     int	  =	self.get_tokenizer()

														lowerCamelCase__ :     Optional[Any]	  =	ChineseCLIPProcessor(tokenizer=UpperCamelCase__      ,							image_processor=UpperCamelCase__					)

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

														lowerCamelCase__ :     str	  =	processor(text=UpperCamelCase__      ,							images=UpperCamelCase__					)

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

