





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 CLIPImageProcessor, CLIPProcessor


@require_vision
class 			lowercase				(							unittest.TestCase     ):



						"""simple docstring"""

						def 		__UpperCAmelCase       (    self			:		Union[str, Any]					):





										'''simple docstring'''







										_snake_case :			Optional[Any]  						=   tempfile.mkdtemp()

										# fmt: off
										_snake_case :			Optional[Any]  						=   ['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
										_snake_case :			str  						=   dict(zip(lowerCamelCase_ ,				range(len(lowerCamelCase_					)					)					)					)
										_snake_case :			List[Any]  						=   ['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>', '']
										_snake_case :			Optional[Any]  						=   {'unk_token': '<unk>'}

										_snake_case :			Union[str, Any]  						=   os.path.join(self.tmpdirname ,				VOCAB_FILES_NAMES['vocab_file']					)
										_snake_case :			Union[str, Any]  						=   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(lowerCamelCase_					) + '\n'					)
										with open(self.merges_file ,				'w' ,				encoding='utf-8'					) as fp:
														fp.write('\n'.join(lowerCamelCase_					)					)

										_snake_case :			Dict  						=   {
										    'do_resize': True,
										    'size': 20,
										    'do_center_crop': True,
										    'crop_size': 18,
										    'do_normalize': True,
										    'image_mean': [0.4814_5466, 0.457_8275, 0.4082_1073],
										    'image_std': [0.2686_2954, 0.2613_0258, 0.2757_7711],
										}
										_snake_case :			str  						=   os.path.join(self.tmpdirname ,				lowerCamelCase_					)
										with open(self.image_processor_file ,				'w' ,				encoding='utf-8'					) as fp:
														json.dump(lowerCamelCase_ ,				lowerCamelCase_					)







						def 		__UpperCAmelCase       (    self			:		Dict ,				**lowerCamelCase_			:		Optional[Any]					):





										'''simple docstring'''







										return CLIPTokenizer.from_pretrained(self.tmpdirname ,				**lowerCamelCase_					)







						def 		__UpperCAmelCase       (    self			:		List[Any] ,				**lowerCamelCase_			:		int					):





										'''simple docstring'''







										return CLIPTokenizerFast.from_pretrained(self.tmpdirname ,				**lowerCamelCase_					)







						def 		__UpperCAmelCase       (    self			:		Optional[Any] ,				**lowerCamelCase_			:		Tuple					):





										'''simple docstring'''







										return CLIPImageProcessor.from_pretrained(self.tmpdirname ,				**lowerCamelCase_					)







						def 		__UpperCAmelCase       (    self			:		List[str]					):





										'''simple docstring'''







										shutil.rmtree(self.tmpdirname					)







						def 		__UpperCAmelCase       (    self			:		Dict					):





										'''simple docstring'''







										_snake_case :			List[Any]  						=   [np.random.randint(2_55 ,				size=(3, 30, 4_00) ,				dtype=np.uinta					)]

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

										return image_inputs







						def 		__UpperCAmelCase       (    self			:		Any					):





										'''simple docstring'''







										_snake_case :			List[Any]  						=   self.get_tokenizer()
										_snake_case :			Dict  						=   self.get_rust_tokenizer()
										_snake_case :			List[Any]  						=   self.get_image_processor()

										_snake_case :			Dict  						=   CLIPProcessor(tokenizer=lowerCamelCase_ ,				image_processor=lowerCamelCase_					)
										processor_slow.save_pretrained(self.tmpdirname					)
										_snake_case :			str  						=   CLIPProcessor.from_pretrained(self.tmpdirname ,				use_fast=lowerCamelCase_					)

										_snake_case :			Tuple  						=   CLIPProcessor(tokenizer=lowerCamelCase_ ,				image_processor=lowerCamelCase_					)
										processor_fast.save_pretrained(self.tmpdirname					)
										_snake_case :			Tuple  						=   CLIPProcessor.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 ,				lowerCamelCase_					)
										self.assertIsInstance(processor_fast.tokenizer ,				lowerCamelCase_					)

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







						def 		__UpperCAmelCase       (    self			:		int					):





										'''simple docstring'''







										_snake_case :			Dict  						=   CLIPProcessor(tokenizer=self.get_tokenizer() ,				image_processor=self.get_image_processor()					)
										processor.save_pretrained(self.tmpdirname					)

										_snake_case :			Any  						=   self.get_tokenizer(bos_token='(BOS)' ,				eos_token='(EOS)'					)
										_snake_case :			Any  						=   self.get_image_processor(do_normalize=lowerCamelCase_ ,				padding_value=1.0					)

										_snake_case :			str  						=   CLIPProcessor.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 		__UpperCAmelCase       (    self			:		List[str]					):





										'''simple docstring'''







										_snake_case :			List[Any]  						=   self.get_image_processor()
										_snake_case :			Optional[Any]  						=   self.get_tokenizer()

										_snake_case :			int  						=   CLIPProcessor(tokenizer=lowerCamelCase_ ,				image_processor=lowerCamelCase_					)

										_snake_case :			Optional[int]  						=   self.prepare_image_inputs()

										_snake_case :			Tuple  						=   image_processor(lowerCamelCase_ ,				return_tensors='np'					)
										_snake_case :			List[str]  						=   processor(images=lowerCamelCase_ ,				return_tensors='np'					)

										for key in input_image_proc.keys():
														self.assertAlmostEqual(input_image_proc[key].sum() ,				input_processor[key].sum() ,				delta=1e-2					)







						def 		__UpperCAmelCase       (    self			:		List[Any]					):





										'''simple docstring'''







										_snake_case :			Optional[Any]  						=   self.get_image_processor()
										_snake_case :			List[Any]  						=   self.get_tokenizer()

										_snake_case :			str  						=   CLIPProcessor(tokenizer=lowerCamelCase_ ,				image_processor=lowerCamelCase_					)

										_snake_case :			Optional[Any]  						=   'lower newer'

										_snake_case :			List[str]  						=   processor(text=lowerCamelCase_					)

										_snake_case :			str  						=   tokenizer(lowerCamelCase_					)

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







						def 		__UpperCAmelCase       (    self			:		List[str]					):





										'''simple docstring'''







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

										_snake_case :			Any  						=   CLIPProcessor(tokenizer=lowerCamelCase_ ,				image_processor=lowerCamelCase_					)

										_snake_case :			Dict  						=   'lower newer'
										_snake_case :			Optional[Any]  						=   self.prepare_image_inputs()

										_snake_case :			Dict  						=   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 		__UpperCAmelCase       (    self			:		Optional[int]					):





										'''simple docstring'''







										_snake_case :			Union[str, Any]  						=   self.get_image_processor()
										_snake_case :			int  						=   self.get_tokenizer()

										_snake_case :			List[Any]  						=   CLIPProcessor(tokenizer=lowerCamelCase_ ,				image_processor=lowerCamelCase_					)

										_snake_case :			Dict  						=   [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

										_snake_case :			Optional[Any]  						=   processor.batch_decode(lowerCamelCase_					)
										_snake_case :			Optional[Any]  						=   tokenizer.batch_decode(lowerCamelCase_					)

										self.assertListEqual(lowerCamelCase_ ,				lowerCamelCase_					)







						def 		__UpperCAmelCase       (    self			:		Any					):





										'''simple docstring'''







										_snake_case :			Tuple  						=   self.get_image_processor()
										_snake_case :			List[str]  						=   self.get_tokenizer()

										_snake_case :			Dict  						=   CLIPProcessor(tokenizer=lowerCamelCase_ ,				image_processor=lowerCamelCase_					)

										_snake_case :			List[Any]  						=   'lower newer'
										_snake_case :			Optional[int]  						=   self.prepare_image_inputs()

										_snake_case :			List[str]  						=   processor(text=lowerCamelCase_ ,				images=lowerCamelCase_					)

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













from __future__ import annotations

def       A__(		__lowerCAmelCase	,			__lowerCAmelCase	,			__lowerCAmelCase ):
				_snake_case :			Dict  						=   list(range(len(__lowerCAmelCase ) ) )
				_snake_case :			Optional[int]  						=   [v / w for v, w in zip(__lowerCAmelCase	,			__lowerCAmelCase )]
				index.sort(key=lambda __lowerCAmelCase : ratio[i]	,			reverse=__lowerCAmelCase )

				_snake_case :			float  						=   0
				_snake_case :			list[float]  						=   [0] * len(__lowerCAmelCase )
				for i in index:
								if weight[i] <= capacity:
												_snake_case :			List[Any]  						=   1
												max_value += value[i]
												capacity -= weight[i]
								else:
												_snake_case :			Any  						=   capacity / weight[i]
												max_value += value[i] * capacity / weight[i]
												break

				return max_value, fractions


if __name__ == "__main__":
		import doctest

		doctest.testmod()






