
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  lowercase__(				unittest.TestCase							):



	"""simple docstring"""




	def 						_lowercase  (       self  :			Any       )       ->     str:
					lowercase_       =					tempfile.mkdtemp()

					# fmt: off
					lowercase_       =					['''[UNK]''', '''[CLS]''', '''[SEP]''', '''[PAD]''', '''[MASK]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''', ''',''', '''low''', '''lowest''']
					# fmt: on
					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''': 1_8, '''width''': 1_8},
					    '''do_normalize''': True,
					    '''image_mean''': [0.5, 0.5, 0.5],
					    '''image_std''': [0.5, 0.5, 0.5],
					}
					lowercase_       =					os.path.join(self.tmpdirname       ,							SCREAMING_SNAKE_CASE_       )
					with open(self.image_processor_file       ,							'''w'''       ,							encoding='''utf-8'''       ) as fp:
									json.dump(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			Any       ,							**SCREAMING_SNAKE_CASE_  :			Any       )       ->     Optional[Any]:
					return BertTokenizer.from_pretrained(self.tmpdirname       ,							**SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			Optional[int]       ,							**SCREAMING_SNAKE_CASE_  :			List[Any]       )       ->     Optional[int]:
					return ViTImageProcessor.from_pretrained(self.tmpdirname       ,							**SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			str       )       ->     Optional[int]:
					shutil.rmtree(self.tmpdirname       )
	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     Union[str, Any]:
					lowercase_       =					[np.random.randint(2_5_5       ,							size=(3, 3_0, 4_0_0)       ,							dtype=np.uinta       )]

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

					return image_inputs
	def 						_lowercase  (       self  :			Dict       )       ->     Optional[int]:
					lowercase_       =					self.get_tokenizer()
					lowercase_       =					self.get_image_processor()

					lowercase_       =					VisionTextDualEncoderProcessor(tokenizer=SCREAMING_SNAKE_CASE_       ,							image_processor=SCREAMING_SNAKE_CASE_       )

					processor.save_pretrained(self.tmpdirname       )
					lowercase_       =					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       ,							SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     List[Any]:
					lowercase_       =					VisionTextDualEncoderProcessor(
					    tokenizer=self.get_tokenizer()       ,							image_processor=self.get_image_processor()       )
					processor.save_pretrained(self.tmpdirname       )

					lowercase_       =					self.get_tokenizer(bos_token='''(BOS)'''       ,							eos_token='''(EOS)'''       )
					lowercase_       =					self.get_image_processor(do_normalize=SCREAMING_SNAKE_CASE_       ,							padding_value=1.0       )

					lowercase_       =					VisionTextDualEncoderProcessor.from_pretrained(
					    self.tmpdirname       ,							bos_token='''(BOS)'''       ,							eos_token='''(EOS)'''       ,							do_normalize=SCREAMING_SNAKE_CASE_       ,							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       ,							SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			Union[str, Any]       )       ->     Optional[int]:
					lowercase_       =					self.get_image_processor()
					lowercase_       =					self.get_tokenizer()

					lowercase_       =					VisionTextDualEncoderProcessor(tokenizer=SCREAMING_SNAKE_CASE_       ,							image_processor=SCREAMING_SNAKE_CASE_       )

					lowercase_       =					self.prepare_image_inputs()

					lowercase_       =					image_processor(SCREAMING_SNAKE_CASE_       ,							return_tensors='''np'''       )
					lowercase_       =					processor(images=SCREAMING_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 						_lowercase  (       self  :			List[str]       )       ->     Optional[int]:
					lowercase_       =					self.get_image_processor()
					lowercase_       =					self.get_tokenizer()

					lowercase_       =					VisionTextDualEncoderProcessor(tokenizer=SCREAMING_SNAKE_CASE_       ,							image_processor=SCREAMING_SNAKE_CASE_       )

					lowercase_       =					'''lower newer'''

					lowercase_       =					processor(text=SCREAMING_SNAKE_CASE_       )

					lowercase_       =					tokenizer(SCREAMING_SNAKE_CASE_       )

					for key in encoded_tok.keys():
									self.assertListEqual(encoded_tok[key]       ,							encoded_processor[key]       )
	def 						_lowercase  (       self  :			List[Any]       )       ->     Optional[int]:
					lowercase_       =					self.get_image_processor()
					lowercase_       =					self.get_tokenizer()

					lowercase_       =					VisionTextDualEncoderProcessor(tokenizer=SCREAMING_SNAKE_CASE_       ,							image_processor=SCREAMING_SNAKE_CASE_       )

					lowercase_       =					'''lower newer'''
					lowercase_       =					self.prepare_image_inputs()

					lowercase_       =					processor(text=SCREAMING_SNAKE_CASE_       ,							images=SCREAMING_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 self.assertRaises(SCREAMING_SNAKE_CASE_       ):
									processor()
	def 						_lowercase  (       self  :			Tuple       )       ->     Optional[Any]:
					lowercase_       =					self.get_image_processor()
					lowercase_       =					self.get_tokenizer()

					lowercase_       =					VisionTextDualEncoderProcessor(tokenizer=SCREAMING_SNAKE_CASE_       ,							image_processor=SCREAMING_SNAKE_CASE_       )

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

					lowercase_       =					processor.batch_decode(SCREAMING_SNAKE_CASE_       )
					lowercase_       =					tokenizer.batch_decode(SCREAMING_SNAKE_CASE_       )

					self.assertListEqual(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )




	def 						_lowercase  (       self  :			Optional[Any]       )       ->     Dict:
					lowercase_       =					self.get_image_processor()
					lowercase_       =					self.get_tokenizer()

					lowercase_       =					VisionTextDualEncoderProcessor(tokenizer=SCREAMING_SNAKE_CASE_       ,							image_processor=SCREAMING_SNAKE_CASE_       )

					lowercase_       =					'''lower newer'''
					lowercase_       =					self.prepare_image_inputs()

					lowercase_       =					processor(text=SCREAMING_SNAKE_CASE_       ,							images=SCREAMING_SNAKE_CASE_       )

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






def 				a						(							snake_case__:					int = 100					):


				'''simple docstring'''
				lowercase_       =					(n * (n + 1) // 2) ** 2
				lowercase_       =					n * (n + 1) * (2 * n + 1) // 6
				return sum_cubes - sum_squares


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




