

"""simple docstring"""


import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
			from PIL import Image

			from transformers import AutoProcessor, BertTokenizer, CLIPImageProcessor, GitProcessor, PreTrainedTokenizerFast





@require_vision
class 					snake_case			(       unittest.TestCase						):

				def 							lowercase_  (			self							:       Dict)->     str:



						'''simple docstring'''


						__lowerCAmelCase: Any					   =    tempfile.mkdtemp()

						__lowerCAmelCase: List[Any]					   =    CLIPImageProcessor()
						__lowerCAmelCase: Dict					   =    BertTokenizer.from_pretrained(
						    "hf-internal-testing/tiny-random-BertModel"  ,						model_input_names=["input_ids", "attention_mask"])

						__lowerCAmelCase: List[Any]					   =    GitProcessor(_lowerCamelCase  ,						_lowerCamelCase)

						processor.save_pretrained(self.tmpdirname)

				def 							lowercase_  (			self							:       int  ,						**UpperCamelCase__							:       Dict)->     Union[str, Any]:



						'''simple docstring'''


						return AutoProcessor.from_pretrained(self.tmpdirname  ,						**_lowerCamelCase).tokenizer

				def 							lowercase_  (			self							:       List[Any]  ,						**UpperCamelCase__							:       Union[str, Any])->     Dict:



						'''simple docstring'''


						return AutoProcessor.from_pretrained(self.tmpdirname  ,						**_lowerCamelCase).image_processor

				def 							lowercase_  (			self							:       Tuple)->     List[Any]:



						'''simple docstring'''


						shutil.rmtree(self.tmpdirname)

				def 							lowercase_  (			self							:       Optional[Any])->     Tuple:



						'''simple docstring'''


						__lowerCAmelCase: Optional[Any]					   =    [np.random.randint(2_5_5  ,						size=(3, 3_0, 4_0_0)  ,						dtype=np.uinta)]

						__lowerCAmelCase: Union[str, Any]					   =    [Image.fromarray(np.moveaxis(_lowerCamelCase  ,						0  ,						-1)) for x in image_inputs]

						return image_inputs

				def 							lowercase_  (			self							:       Optional[Any])->     Dict:



						'''simple docstring'''


						__lowerCAmelCase: List[str]					   =    GitProcessor(tokenizer=self.get_tokenizer()  ,						image_processor=self.get_image_processor())
						processor.save_pretrained(self.tmpdirname)

						__lowerCAmelCase: str					   =    self.get_tokenizer(bos_token="(BOS)"  ,						eos_token="(EOS)")
						__lowerCAmelCase: List[str]					   =    self.get_image_processor(do_normalize=_lowerCamelCase  ,						padding_value=1.0)

						__lowerCAmelCase: Any					   =    GitProcessor.from_pretrained(
						    self.tmpdirname  ,						bos_token="(BOS)"  ,						eos_token="(EOS)"  ,						do_normalize=_lowerCamelCase  ,						padding_value=1.0)

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

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

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



						'''simple docstring'''


						__lowerCAmelCase: int					   =    self.get_image_processor()
						__lowerCAmelCase: List[str]					   =    self.get_tokenizer()

						__lowerCAmelCase: Union[str, Any]					   =    GitProcessor(tokenizer=_lowerCamelCase  ,						image_processor=_lowerCamelCase)

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

						__lowerCAmelCase: str					   =    image_processor(_lowerCamelCase  ,						return_tensors="np")
						__lowerCAmelCase: Union[str, Any]					   =    processor(images=_lowerCamelCase  ,						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							:       Union[str, Any])->     List[Any]:



						'''simple docstring'''


						__lowerCAmelCase: Optional[int]					   =    self.get_image_processor()
						__lowerCAmelCase: int					   =    self.get_tokenizer()

						__lowerCAmelCase: Any					   =    GitProcessor(tokenizer=_lowerCamelCase  ,						image_processor=_lowerCamelCase)

						__lowerCAmelCase: Dict					   =    """lower newer"""

						__lowerCAmelCase: Dict					   =    processor(text=_lowerCamelCase)

						__lowerCAmelCase: Optional[Any]					   =    tokenizer(_lowerCamelCase  ,						return_token_type_ids=_lowerCamelCase)

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

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



						'''simple docstring'''


						__lowerCAmelCase: Optional[int]					   =    self.get_image_processor()
						__lowerCAmelCase: List[str]					   =    self.get_tokenizer()

						__lowerCAmelCase: str					   =    GitProcessor(tokenizer=_lowerCamelCase  ,						image_processor=_lowerCamelCase)

						__lowerCAmelCase: str					   =    """lower newer"""
						__lowerCAmelCase: List[str]					   =    self.prepare_image_inputs()

						__lowerCAmelCase: Union[str, Any]					   =    processor(text=_lowerCamelCase  ,						images=_lowerCamelCase)

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

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

				def 							lowercase_  (			self							:       Dict)->     Optional[int]:



						'''simple docstring'''


						__lowerCAmelCase: Optional[int]					   =    self.get_image_processor()
						__lowerCAmelCase: Any					   =    self.get_tokenizer()

						__lowerCAmelCase: Optional[Any]					   =    GitProcessor(tokenizer=_lowerCamelCase  ,						image_processor=_lowerCamelCase)

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

						__lowerCAmelCase: Union[str, Any]					   =    processor.batch_decode(_lowerCamelCase)
						__lowerCAmelCase: Any					   =    tokenizer.batch_decode(_lowerCamelCase)

						self.assertListEqual(_lowerCamelCase  ,						_lowerCamelCase)




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



						'''simple docstring'''


						__lowerCAmelCase: Dict					   =    self.get_image_processor()
						__lowerCAmelCase: Tuple					   =    self.get_tokenizer()

						__lowerCAmelCase: Union[str, Any]					   =    GitProcessor(tokenizer=_lowerCamelCase  ,						image_processor=_lowerCamelCase)

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

						__lowerCAmelCase: str					   =    processor(text=_lowerCamelCase  ,						images=_lowerCamelCase)

						# For now the processor supports only ['input_ids', 'attention_mask', 'pixel_values']
						self.assertListEqual(list(inputs.keys())  ,						["input_ids", "attention_mask", "pixel_values"])





"""simple docstring"""


def 					a__					(					__SCREAMING_SNAKE_CASE = 1_0_0_0				)			->			int:
		__lowerCAmelCase: int					   =    0
		__lowerCAmelCase: Optional[int]					   =    0
		while 1:
				num += 3
				if num >= n:
						break
				total += num
				num += 2
				if num >= n:
						break
				total += num
				num += 1
				if num >= n:
						break
				total += num
				num += 3
				if num >= n:
						break
				total += num
				num += 1
				if num >= n:
						break
				total += num
				num += 2
				if num >= n:
						break
				total += num
				num += 3
				if num >= n:
						break
				total += num
		return total


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


