




'''simple docstring'''





import json
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
	from PIL import Image

	from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor




@require_tokenizers
@require_vision
class 			_snake_case		(     unittest.TestCase							):




			def        lowerCAmelCase__    ( self							)    ->    Optional[int]:

										'''simple docstring'''




										snake_case_      =				tempfile.mkdtemp()

										# fmt: off
										snake_case_      =				["[UNK]", "[CLS]", "[SEP]", "[PAD]", "[MASK]", "want", "##want", "##ed", "wa", "un", "runn", "##ing", ",", "low", "lowest"]
										# fmt: on
										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": 18, "width": 18},
										    "do_normalize": True,
										    "image_mean": [0.5, 0.5, 0.5],
										    "image_std": [0.5, 0.5, 0.5],
										}
										snake_case_      =				os.path.join(self.tmpdirname    ,							a__							)
										with open(self.image_processor_file    ,							"w"    ,							encoding="utf-8"							) as fp:
																	json.dump(a__    ,							a__							)




			def        lowerCAmelCase__    ( self    ,							**a__							)    ->    Any:

										'''simple docstring'''




										return BertTokenizer.from_pretrained(self.tmpdirname    ,							**a__							)




			def        lowerCAmelCase__    ( self    ,							**a__							)    ->    List[str]:

										'''simple docstring'''




										return ViTImageProcessor.from_pretrained(self.tmpdirname    ,							**a__							)




			def        lowerCAmelCase__    ( self							)    ->    List[str]:

										'''simple docstring'''




										shutil.rmtree(self.tmpdirname							)




			def        lowerCAmelCase__    ( self							)    ->    Optional[Any]:

										'''simple docstring'''




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

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

										return image_inputs




			def        lowerCAmelCase__    ( self							)    ->    Any:

										'''simple docstring'''




										snake_case_      =				self.get_tokenizer()
										snake_case_      =				self.get_image_processor()

										snake_case_      =				VisionTextDualEncoderProcessor(tokenizer=a__    ,							image_processor=a__							)

										processor.save_pretrained(self.tmpdirname							)
										snake_case_      =				VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname							)

										self.assertEqual(processor.tokenizer.get_vocab()    ,							tokenizer.get_vocab()							)
										self.assertIsInstance(processor.tokenizer    ,							(BertTokenizer, BertTokenizerFast)							)

										self.assertEqual(processor.image_processor.to_json_string()    ,							image_processor.to_json_string()							)
										self.assertIsInstance(processor.image_processor    ,							a__							)




			def        lowerCAmelCase__    ( self							)    ->    Union[str, Any]:

										'''simple docstring'''




										snake_case_      =				VisionTextDualEncoderProcessor(
										    tokenizer=self.get_tokenizer()    ,							image_processor=self.get_image_processor()							)
										processor.save_pretrained(self.tmpdirname							)

										snake_case_      =				self.get_tokenizer(bos_token="(BOS)"    ,							eos_token="(EOS)"							)
										snake_case_      =				self.get_image_processor(do_normalize=a__    ,							padding_value=1.0							)

										snake_case_      =				VisionTextDualEncoderProcessor.from_pretrained(
										    self.tmpdirname    ,							bos_token="(BOS)"    ,							eos_token="(EOS)"    ,							do_normalize=a__    ,							padding_value=1.0							)

										self.assertEqual(processor.tokenizer.get_vocab()    ,							tokenizer_add_kwargs.get_vocab()							)
										self.assertIsInstance(processor.tokenizer    ,							(BertTokenizer, BertTokenizerFast)							)

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




			def        lowerCAmelCase__    ( self							)    ->    str:

										'''simple docstring'''




										snake_case_      =				self.get_image_processor()
										snake_case_      =				self.get_tokenizer()

										snake_case_      =				VisionTextDualEncoderProcessor(tokenizer=a__    ,							image_processor=a__							)

										snake_case_      =				self.prepare_image_inputs()

										snake_case_      =				image_processor(a__    ,							return_tensors="np"							)
										snake_case_      =				processor(images=a__    ,							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							)    ->    Optional[int]:

										'''simple docstring'''




										snake_case_      =				self.get_image_processor()
										snake_case_      =				self.get_tokenizer()

										snake_case_      =				VisionTextDualEncoderProcessor(tokenizer=a__    ,							image_processor=a__							)

										snake_case_      =				"lower newer"

										snake_case_      =				processor(text=a__							)

										snake_case_      =				tokenizer(a__							)

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




			def        lowerCAmelCase__    ( self							)    ->    Tuple:

										'''simple docstring'''




										snake_case_      =				self.get_image_processor()
										snake_case_      =				self.get_tokenizer()

										snake_case_      =				VisionTextDualEncoderProcessor(tokenizer=a__    ,							image_processor=a__							)

										snake_case_      =				"lower newer"
										snake_case_      =				self.prepare_image_inputs()

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

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

										# test if it raises when no input is passed
										with self.assertRaises(a__							):
																	processor()




			def        lowerCAmelCase__    ( self							)    ->    List[Any]:

										'''simple docstring'''




										snake_case_      =				self.get_image_processor()
										snake_case_      =				self.get_tokenizer()

										snake_case_      =				VisionTextDualEncoderProcessor(tokenizer=a__    ,							image_processor=a__							)

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

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

										self.assertListEqual(a__    ,							a__							)




			def        lowerCAmelCase__    ( self							)    ->    Union[str, Any]:

										'''simple docstring'''




										snake_case_      =				self.get_image_processor()
										snake_case_      =				self.get_tokenizer()

										snake_case_      =				VisionTextDualEncoderProcessor(tokenizer=a__    ,							image_processor=a__							)

										snake_case_      =				"lower newer"
										snake_case_      =				self.prepare_image_inputs()

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

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










'''simple docstring'''





def 					UpperCamelCase_(     snake_case							:	int = 1_0_0_0					):

							'''simple docstring'''






							snake_case_      =				3
							snake_case_      =				0
							while a < n:
														if a % 3 == 0 or a % 5 == 0:
																					result += a
														elif a % 1_5 == 0:
																					result -= a
														a += 1
							return result


if __name__ == "__main__":
		print(F"{solution() = }")




