





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 	__magic_name__			(unittest.TestCase ):




					def 					__a     (       self						)			->					Union[str, Any]:
							lowerCAmelCase_												=				tempfile.mkdtemp()

							# fmt: off
							lowerCAmelCase_												=				['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_												=				dict(zip(snake_case__	,   range(len(snake_case__						)						)						)						)
							lowerCAmelCase_												=				['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>', '']
							lowerCAmelCase_												=				{'unk_token': '<unk>'}

							lowerCAmelCase_												=				os.path.join(self.tmpdirname	,   VOCAB_FILES_NAMES["vocab_file"]						)
							lowerCAmelCase_												=				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(snake_case__						) + "\n"						)
							with open(self.merges_file	,   "w"	,   encoding="utf-8"						) as fp:
									fp.write("\n".join(snake_case__						)						)

							lowerCAmelCase_												=				{
							    'do_resize': True,
							    'size': 20,
							    'do_center_crop': True,
							    'crop_size': 18,
							    'do_normalize': True,
							    'image_mean': [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
							    'image_std': [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
							}
							lowerCAmelCase_												=				os.path.join(self.tmpdirname	,   snake_case__						)
							with open(self.image_processor_file	,   "w"	,   encoding="utf-8"						) as fp:
									json.dump(snake_case__	,   snake_case__						)




					def 					__a     (       self	,   **_a						)			->					Any:
							return CLIPTokenizer.from_pretrained(self.tmpdirname	,   **snake_case__						)




					def 					__a     (       self	,   **_a						)			->					Any:
							return CLIPTokenizerFast.from_pretrained(self.tmpdirname	,   **snake_case__						)




					def 					__a     (       self	,   **_a						)			->					int:
							return ViTImageProcessor.from_pretrained(self.tmpdirname	,   **snake_case__						)




					def 					__a     (       self						)			->					Any:
							shutil.rmtree(self.tmpdirname						)




					def 					__a     (       self						)			->					Dict:
							lowerCAmelCase_												=				[np.random.randint(255	,   size=(3, 30, 400)	,   dtype=np.uinta						)]

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

							return image_inputs




					def 					__a     (       self						)			->					Tuple:
							lowerCAmelCase_												=				self.get_tokenizer()
							lowerCAmelCase_												=				self.get_rust_tokenizer()
							lowerCAmelCase_												=				self.get_image_processor()

							lowerCAmelCase_												=				CLIPSegProcessor(tokenizer=snake_case__	,   image_processor=snake_case__						)
							processor_slow.save_pretrained(self.tmpdirname						)
							lowerCAmelCase_												=				CLIPSegProcessor.from_pretrained(self.tmpdirname	,   use_fast=snake_case__						)

							lowerCAmelCase_												=				CLIPSegProcessor(tokenizer=snake_case__	,   image_processor=snake_case__						)
							processor_fast.save_pretrained(self.tmpdirname						)
							lowerCAmelCase_												=				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	,   snake_case__						)
							self.assertIsInstance(processor_fast.tokenizer	,   snake_case__						)

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




					def 					__a     (       self						)			->					Optional[Any]:
							lowerCAmelCase_												=				CLIPSegProcessor(tokenizer=self.get_tokenizer()	,   image_processor=self.get_image_processor()						)
							processor.save_pretrained(self.tmpdirname						)

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

							lowerCAmelCase_												=				CLIPSegProcessor.from_pretrained(
							    self.tmpdirname	,   bos_token="(BOS)"	,   eos_token="(EOS)"	,   do_normalize=snake_case__	,   padding_value=1.0						)

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

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




					def 					__a     (       self						)			->					Optional[Any]:
							lowerCAmelCase_												=				self.get_image_processor()
							lowerCAmelCase_												=				self.get_tokenizer()

							lowerCAmelCase_												=				CLIPSegProcessor(tokenizer=snake_case__	,   image_processor=snake_case__						)

							lowerCAmelCase_												=				self.prepare_image_inputs()

							lowerCAmelCase_												=				image_processor(snake_case__	,   return_tensors="np"						)
							lowerCAmelCase_												=				processor(images=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 					__a     (       self						)			->					List[Any]:
							lowerCAmelCase_												=				self.get_image_processor()
							lowerCAmelCase_												=				self.get_tokenizer()

							lowerCAmelCase_												=				CLIPSegProcessor(tokenizer=snake_case__	,   image_processor=snake_case__						)

							lowerCAmelCase_												=				'lower newer'

							lowerCAmelCase_												=				processor(text=snake_case__						)

							lowerCAmelCase_												=				tokenizer(snake_case__						)

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




					def 					__a     (       self						)			->					Optional[int]:
							lowerCAmelCase_												=				self.get_image_processor()
							lowerCAmelCase_												=				self.get_tokenizer()

							lowerCAmelCase_												=				CLIPSegProcessor(tokenizer=snake_case__	,   image_processor=snake_case__						)

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

							lowerCAmelCase_												=				processor(text=snake_case__	,   images=snake_case__						)

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

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




					def 					__a     (       self						)			->					Tuple:
							lowerCAmelCase_												=				self.get_image_processor()
							lowerCAmelCase_												=				self.get_tokenizer()

							lowerCAmelCase_												=				CLIPSegProcessor(tokenizer=snake_case__	,   image_processor=snake_case__						)

							lowerCAmelCase_												=				self.prepare_image_inputs()
							lowerCAmelCase_												=				self.prepare_image_inputs()

							lowerCAmelCase_												=				processor(images=snake_case__	,   visual_prompt=snake_case__						)

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

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




					def 					__a     (       self						)			->					Optional[int]:
							lowerCAmelCase_												=				self.get_image_processor()
							lowerCAmelCase_												=				self.get_tokenizer()

							lowerCAmelCase_												=				CLIPSegProcessor(tokenizer=snake_case__	,   image_processor=snake_case__						)

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

							lowerCAmelCase_												=				processor.batch_decode(snake_case__						)
							lowerCAmelCase_												=				tokenizer.batch_decode(snake_case__						)

							self.assertListEqual(snake_case__	,   snake_case__						)







def        __UpperCAmelCase						(							lowerCamelCase_ :     str  )       ->  bool:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Any					  =      0
			for ch in input_str:
						SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      ord(lowerCamelCase_  )
						SCREAMING_SNAKE_CASE_   : Tuple					  =      pow(2  ,							lowerCamelCase_  )

						# If we already turned on bit for current character's unicode
						if bitmap >> ch_unicode & 1 == 1:
									return False
						bitmap |= ch_bit_index_on
			return True


if __name__ == "__main__":
						import doctest

						doctest.testmod()



