



'''simple docstring'''




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     UpperCamelCase_				(							unittest.TestCase    ):





	def 				_lowercase(						self					)    ->    List[Any]:
								UpperCAmelCase  :	Optional[Any]							  =	tempfile.mkdtemp()

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

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

								UpperCAmelCase  :	Optional[int]							  =	{
								    """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],
								}
								UpperCAmelCase  :	List[str]							  =	os.path.join(self.tmpdirname	,	A__					)
								with open(self.image_processor_file	,	"""w"""	,	encoding="""utf-8"""					) as fp:
															json.dump(A__	,	A__					)





	def 				_lowercase(						self	,	**A					)    ->    Any:
								return CLIPTokenizer.from_pretrained(self.tmpdirname	,	**A__					)





	def 				_lowercase(						self	,	**A					)    ->    str:
								return CLIPTokenizerFast.from_pretrained(self.tmpdirname	,	**A__					)





	def 				_lowercase(						self	,	**A					)    ->    Dict:
								return ViTImageProcessor.from_pretrained(self.tmpdirname	,	**A__					)





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





	def 				_lowercase(						self					)    ->    List[Any]:
								UpperCAmelCase  :	List[str]							  =	[np.random.randint(255	,	size=(3, 30, 400)	,	dtype=np.uinta					)]

								UpperCAmelCase  :	List[str]							  =	[Image.fromarray(np.moveaxis(A__	,	0	,	-1					)					) for x in image_inputs]

								return image_inputs





	def 				_lowercase(						self					)    ->    Union[str, Any]:
								UpperCAmelCase  :	Union[str, Any]							  =	self.get_tokenizer()
								UpperCAmelCase  :	Optional[int]							  =	self.get_rust_tokenizer()
								UpperCAmelCase  :	List[str]							  =	self.get_image_processor()

								UpperCAmelCase  :	Dict							  =	CLIPSegProcessor(tokenizer=A__	,	image_processor=A__					)
								processor_slow.save_pretrained(self.tmpdirname					)
								UpperCAmelCase  :	Any							  =	CLIPSegProcessor.from_pretrained(self.tmpdirname	,	use_fast=A__					)

								UpperCAmelCase  :	List[str]							  =	CLIPSegProcessor(tokenizer=A__	,	image_processor=A__					)
								processor_fast.save_pretrained(self.tmpdirname					)
								UpperCAmelCase  :	List[str]							  =	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	,	A__					)
								self.assertIsInstance(processor_fast.tokenizer	,	A__					)

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





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

								UpperCAmelCase  :	Optional[int]							  =	self.get_tokenizer(bos_token="""(BOS)"""	,	eos_token="""(EOS)"""					)
								UpperCAmelCase  :	int							  =	self.get_image_processor(do_normalize=A__	,	padding_value=1.0					)

								UpperCAmelCase  :	Optional[Any]							  =	CLIPSegProcessor.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	,	A__					)

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





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

								UpperCAmelCase  :	Tuple							  =	CLIPSegProcessor(tokenizer=A__	,	image_processor=A__					)

								UpperCAmelCase  :	int							  =	self.prepare_image_inputs()

								UpperCAmelCase  :	int							  =	image_processor(A__	,	return_tensors="""np"""					)
								UpperCAmelCase  :	Dict							  =	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 				_lowercase(						self					)    ->    Tuple:
								UpperCAmelCase  :	Tuple							  =	self.get_image_processor()
								UpperCAmelCase  :	Any							  =	self.get_tokenizer()

								UpperCAmelCase  :	str							  =	CLIPSegProcessor(tokenizer=A__	,	image_processor=A__					)

								UpperCAmelCase  :	List[str]							  =	"""lower newer"""

								UpperCAmelCase  :	str							  =	processor(text=A__					)

								UpperCAmelCase  :	Any							  =	tokenizer(A__					)

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





	def 				_lowercase(						self					)    ->    Any:
								UpperCAmelCase  :	List[str]							  =	self.get_image_processor()
								UpperCAmelCase  :	List[str]							  =	self.get_tokenizer()

								UpperCAmelCase  :	Union[str, Any]							  =	CLIPSegProcessor(tokenizer=A__	,	image_processor=A__					)

								UpperCAmelCase  :	Union[str, Any]							  =	"""lower newer"""
								UpperCAmelCase  :	Tuple							  =	self.prepare_image_inputs()

								UpperCAmelCase  :	str							  =	processor(text=A__	,	images=A__					)

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

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





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

								UpperCAmelCase  :	Tuple							  =	CLIPSegProcessor(tokenizer=A__	,	image_processor=A__					)

								UpperCAmelCase  :	Optional[Any]							  =	self.prepare_image_inputs()
								UpperCAmelCase  :	Dict							  =	self.prepare_image_inputs()

								UpperCAmelCase  :	Dict							  =	processor(images=A__	,	visual_prompt=A__					)

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

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






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

								UpperCAmelCase  :	Tuple							  =	CLIPSegProcessor(tokenizer=A__	,	image_processor=A__					)

								UpperCAmelCase  :	Optional[int]							  =	[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

								UpperCAmelCase  :	Dict							  =	processor.batch_decode(A__					)
								UpperCAmelCase  :	Dict							  =	tokenizer.batch_decode(A__					)

								self.assertListEqual(A__	,	A__					)






'''simple docstring'''




import math



def    __lowerCamelCase						(      _lowercase	)   ->    bool:
							assert isinstance(_lowercase			,       _lowercase	) and (
							    number >= 0
							), "'number' must been an int and positive"

							if 1 < number < 4:
														# 2 and 3 are primes
														return True
							elif number < 2 or not number % 2:
														# Negatives, 0, 1 and all even numbers are not primes
														return False

							UpperCAmelCase  :	str							  =	range(3			,       int(math.sqrt(_lowercase	) + 1	)			,       2	)
							return not any(not number % i for i in odd_numbers	)



def    __lowerCamelCase						(      _lowercase			,       _lowercase=1			,       **_lowercase	)   ->    Union[str, Any]:
							UpperCAmelCase  :	Optional[int]							  =	factor * value
							UpperCAmelCase  :	List[Any]							  =	value

							while not is_prime(_lowercase	):
														value += 1 if not ("desc" in kwargs and kwargs["desc"] is True) else -1

							if value == first_value_val:
														return next_prime(value + 1			,       **_lowercase	)
							return value

