






"""simple docstring"""



import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
						from PIL import Image

						from transformers import CLIPSegProcessor, ViTImageProcessor







@require_vision
class   lowercase__     (				unittest.TestCase  ):


			def       UpperCAmelCase__		( self	:    List[Any]   ):
										lowerCamelCase_			:				str										=tempfile.mkdtemp()

										# fmt: off
										lowerCamelCase_			:				Optional[int]										=["l", "o", "w", "e", "r", "s", "t", "i", "d", "n", "lo", "l</w>", "w</w>", "r</w>", "t</w>", "low</w>", "er</w>", "lowest</w>", "newer</w>", "wider", "<unk>", "<|startoftext|>", "<|endoftext|>"]
										# fmt: on
										lowerCamelCase_			:				int										=dict(zip(lowercase_  ,			range(len(lowercase_   )   )   )   )
										lowerCamelCase_			:				Optional[int]										=["#version: 0.2", "l o", "lo w</w>", "e r</w>", ""]
										lowerCamelCase_			:				str										={"unk_token": "<unk>"}

										lowerCamelCase_			:				Any										=os.path.join(self.tmpdirname  ,			VOCAB_FILES_NAMES["vocab_file"]   )
										lowerCamelCase_			:				Dict										=os.path.join(self.tmpdirname  ,			VOCAB_FILES_NAMES["merges_file"]   )
										with open(self.vocab_file  ,			"w"  ,			encoding="utf-8"   ) as fp:
																	fp.write(json.dumps(lowercase_   ) + "\n"   )
										with open(self.merges_file  ,			"w"  ,			encoding="utf-8"   ) as fp:
																	fp.write("\n".join(lowercase_   )   )

										lowerCamelCase_			:				List[str]										={
										    "do_resize": True,
										    "size": 20,
										    "do_center_crop": True,
										    "crop_size": 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],
										}
										lowerCamelCase_			:				Dict										=os.path.join(self.tmpdirname  ,			lowercase_   )
										with open(self.image_processor_file  ,			"w"  ,			encoding="utf-8"   ) as fp:
																	json.dump(lowercase_  ,			lowercase_   )


			def       UpperCAmelCase__		( self	:    List[str]  ,			**snake_case__	:    str   ):
										return CLIPTokenizer.from_pretrained(self.tmpdirname  ,			**lowercase_   )


			def       UpperCAmelCase__		( self	:    List[str]  ,			**snake_case__	:    List[Any]   ):
										return CLIPTokenizerFast.from_pretrained(self.tmpdirname  ,			**lowercase_   )


			def       UpperCAmelCase__		( self	:    Dict  ,			**snake_case__	:    Any   ):
										return ViTImageProcessor.from_pretrained(self.tmpdirname  ,			**lowercase_   )


			def       UpperCAmelCase__		( self	:    List[str]   ):
										shutil.rmtree(self.tmpdirname   )


			def       UpperCAmelCase__		( self	:    List[Any]   ):
										lowerCamelCase_			:				Tuple										=[np.random.randint(255  ,			size=(3, 30, 400)  ,			dtype=np.uinta   )]

										lowerCamelCase_			:				Optional[Any]										=[Image.fromarray(np.moveaxis(lowercase_  ,			0  ,			-1   )   ) for x in image_inputs]

										return image_inputs


			def       UpperCAmelCase__		( self	:    Union[str, Any]   ):
										lowerCamelCase_			:				int										=self.get_tokenizer()
										lowerCamelCase_			:				Any										=self.get_rust_tokenizer()
										lowerCamelCase_			:				Dict										=self.get_image_processor()

										lowerCamelCase_			:				Optional[int]										=CLIPSegProcessor(tokenizer=lowercase_  ,			image_processor=lowercase_   )
										processor_slow.save_pretrained(self.tmpdirname   )
										lowerCamelCase_			:				List[str]										=CLIPSegProcessor.from_pretrained(self.tmpdirname  ,			use_fast=lowercase_   )

										lowerCamelCase_			:				Tuple										=CLIPSegProcessor(tokenizer=lowercase_  ,			image_processor=lowercase_   )
										processor_fast.save_pretrained(self.tmpdirname   )
										lowerCamelCase_			:				int										=CLIPSegProcessor.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  ,			lowercase_   )
										self.assertIsInstance(processor_fast.tokenizer  ,			lowercase_   )

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


			def       UpperCAmelCase__		( self	:    str   ):
										lowerCamelCase_			:				List[Any]										=CLIPSegProcessor(tokenizer=self.get_tokenizer()  ,			image_processor=self.get_image_processor()   )
										processor.save_pretrained(self.tmpdirname   )

										lowerCamelCase_			:				Optional[int]										=self.get_tokenizer(bos_token="(BOS)"  ,			eos_token="(EOS)"   )
										lowerCamelCase_			:				Dict										=self.get_image_processor(do_normalize=lowercase_  ,			padding_value=1.0   )

										lowerCamelCase_			:				Tuple										=CLIPSegProcessor.from_pretrained(
										    self.tmpdirname  ,			bos_token="(BOS)"  ,			eos_token="(EOS)"  ,			do_normalize=lowercase_  ,			padding_value=1.0   )

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

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


			def       UpperCAmelCase__		( self	:    Dict   ):
										lowerCamelCase_			:				Optional[int]										=self.get_image_processor()
										lowerCamelCase_			:				List[str]										=self.get_tokenizer()

										lowerCamelCase_			:				Dict										=CLIPSegProcessor(tokenizer=lowercase_  ,			image_processor=lowercase_   )

										lowerCamelCase_			:				List[str]										=self.prepare_image_inputs()

										lowerCamelCase_			:				Any										=image_processor(lowercase_  ,			return_tensors="np"   )
										lowerCamelCase_			:				List[Any]										=processor(images=lowercase_  ,			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       UpperCAmelCase__		( self	:    str   ):
										lowerCamelCase_			:				str										=self.get_image_processor()
										lowerCamelCase_			:				List[Any]										=self.get_tokenizer()

										lowerCamelCase_			:				str										=CLIPSegProcessor(tokenizer=lowercase_  ,			image_processor=lowercase_   )

										lowerCamelCase_			:				Union[str, Any]										="lower newer"

										lowerCamelCase_			:				Optional[int]										=processor(text=lowercase_   )

										lowerCamelCase_			:				Optional[int]										=tokenizer(lowercase_   )

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


			def       UpperCAmelCase__		( self	:    int   ):
										lowerCamelCase_			:				int										=self.get_image_processor()
										lowerCamelCase_			:				str										=self.get_tokenizer()

										lowerCamelCase_			:				Dict										=CLIPSegProcessor(tokenizer=lowercase_  ,			image_processor=lowercase_   )

										lowerCamelCase_			:				List[str]										="lower newer"
										lowerCamelCase_			:				Optional[int]										=self.prepare_image_inputs()

										lowerCamelCase_			:				Union[str, Any]										=processor(text=lowercase_  ,			images=lowercase_   )

										self.assertListEqual(list(inputs.keys()   )  ,			["input_ids", "attention_mask", "pixel_values"]   )

										# test if it raises when no input is passed
										with pytest.raises(lowercase_   ):
																	processor()


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

										lowerCamelCase_			:				Optional[Any]										=CLIPSegProcessor(tokenizer=lowercase_  ,			image_processor=lowercase_   )

										lowerCamelCase_			:				Any										=self.prepare_image_inputs()
										lowerCamelCase_			:				Any										=self.prepare_image_inputs()

										lowerCamelCase_			:				Optional[Any]										=processor(images=lowercase_  ,			visual_prompt=lowercase_   )

										self.assertListEqual(list(inputs.keys()   )  ,			["pixel_values", "conditional_pixel_values"]   )

										# test if it raises when no input is passed
										with pytest.raises(lowercase_   ):
																	processor()


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

										lowerCamelCase_			:				int										=CLIPSegProcessor(tokenizer=lowercase_  ,			image_processor=lowercase_   )

										lowerCamelCase_			:				Tuple										=[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

										lowerCamelCase_			:				int										=processor.batch_decode(lowercase_   )
										lowerCamelCase_			:				List[Any]										=tokenizer.batch_decode(lowercase_   )

										self.assertListEqual(lowercase_  ,			lowercase_   )





"""simple docstring"""

def      lowercase__    (       lowerCAmelCase					:       str			)			->   bool:






    """simple docstring"""




    UpperCAmelCase          =       [int(lowerCAmelCase			) for i in ip_va_address.split('.'			) if i.isdigit()]
    return len(lowerCAmelCase			) == 4 and all(0 <= int(lowerCAmelCase			) <= 254 for octet in octets			)


if __name__ == "__main__":
   SCREAMING_SNAKE_CASE_            =    input().strip()
   SCREAMING_SNAKE_CASE_            =    '''valid''' if is_ip_va_address_valid(ip) else '''invalid'''
   print(F'{ip} is a {valid_or_invalid} IP v4 address.')



