



"""simple docstring"""

import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
			import torch


if is_vision_available():
			from PIL import Image

			from transformers import MgpstrProcessor, ViTImageProcessor







@require_torch
@require_vision
class    __lowercase     (					unittest.TestCase):







						"""simple docstring"""







						_A		:							Optional[Any]							       =		ViTImageProcessor if is_vision_available() else None







						@property
						def 						__UpperCamelCase							(self       ):
											return self.image_processor_tester.prepare_image_processor_dict()







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		List[str] 					=					(3, 32, 1_28)
											snake_case_					:		Any 					=					tempfile.mkdtemp()

											# fmt: off
											snake_case_					:		int 					=					["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
											# fmt: on
											snake_case_					:		int 					=					dict(zip(lowercase__   ,		range(len(lowercase__       )       )       )       )

											snake_case_					:		str 					=					os.path.join(self.tmpdirname   ,		VOCAB_FILES_NAMES["""vocab_file"""]       )
											with open(self.vocab_file   ,		"""w"""   ,		encoding="""utf-8"""       ) as fp:
																fp.write(json.dumps(lowercase__       ) + """\n"""       )

											snake_case_					:		Optional[int] 					=					{
											    """do_normalize""": False,
											    """do_resize""": True,
											    """image_processor_type""": """ViTImageProcessor""",
											    """resample""": 3,
											    """size""": {"""height""": 32, """width""": 1_28},
											}
											snake_case_					:		Optional[Any] 					=					os.path.join(self.tmpdirname   ,		lowercase__       )
											with open(self.image_processor_file   ,		"""w"""   ,		encoding="""utf-8"""       ) as fp:
																json.dump(lowercase__   ,		lowercase__       )







						def 						__UpperCamelCase							(self   ,		**lowercase__       ):
											return MgpstrTokenizer.from_pretrained(self.tmpdirname   ,		**lowercase__       )







						def 						__UpperCamelCase							(self   ,		**lowercase__       ):
											return ViTImageProcessor.from_pretrained(self.tmpdirname   ,		**lowercase__       )







						def 						__UpperCamelCase							(self       ):
											shutil.rmtree(self.tmpdirname       )







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Any 					=					np.random.randint(2_55   ,		size=(3, 30, 4_00)   ,		dtype=np.uinta       )

											snake_case_					:		str 					=					Image.fromarray(np.moveaxis(lowercase__   ,		0   ,		-1       )       )

											return image_input







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Union[str, Any] 					=					self.get_tokenizer()
											snake_case_					:		Any 					=					self.get_image_processor()

											snake_case_					:		List[Any] 					=					MgpstrProcessor(tokenizer=lowercase__   ,		image_processor=lowercase__       )
											processor.save_pretrained(self.tmpdirname       )
											snake_case_					:		Any 					=					MgpstrProcessor.from_pretrained(self.tmpdirname   ,		use_fast=lowercase__       )

											self.assertEqual(processor.char_tokenizer.get_vocab()   ,		tokenizer.get_vocab()       )
											self.assertIsInstance(processor.char_tokenizer   ,		lowercase__       )

											self.assertEqual(processor.image_processor.to_json_string()   ,		image_processor.to_json_string()       )
											self.assertIsInstance(processor.image_processor   ,		lowercase__       )







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		List[Any] 					=					self.get_tokenizer()
											snake_case_					:		Any 					=					self.get_image_processor()

											snake_case_					:		Optional[Any] 					=					MgpstrProcessor(tokenizer=lowercase__   ,		image_processor=lowercase__       )
											processor.save_pretrained(self.tmpdirname       )

											snake_case_					:		List[Any] 					=					self.get_tokenizer(bos_token="""(BOS)"""   ,		eos_token="""(EOS)"""       )
											snake_case_					:		Optional[Any] 					=					self.get_image_processor(do_normalize=lowercase__   ,		padding_value=1.0       )

											snake_case_					:		Dict 					=					MgpstrProcessor.from_pretrained(
											    self.tmpdirname   ,		bos_token="""(BOS)"""   ,		eos_token="""(EOS)"""   ,		do_normalize=lowercase__   ,		padding_value=1.0       )

											self.assertEqual(processor.char_tokenizer.get_vocab()   ,		tokenizer_add_kwargs.get_vocab()       )
											self.assertIsInstance(processor.char_tokenizer   ,		lowercase__       )

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







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		List[str] 					=					self.get_image_processor()
											snake_case_					:		int 					=					self.get_tokenizer()

											snake_case_					:		int 					=					MgpstrProcessor(tokenizer=lowercase__   ,		image_processor=lowercase__       )

											snake_case_					:		Any 					=					self.prepare_image_inputs()

											snake_case_					:		Optional[int] 					=					image_processor(lowercase__   ,		return_tensors="""np"""       )
											snake_case_					:		Union[str, Any] 					=					processor(images=lowercase__   ,		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       ):
											snake_case_					:		List[str] 					=					self.get_image_processor()
											snake_case_					:		Tuple 					=					self.get_tokenizer()

											snake_case_					:		List[str] 					=					MgpstrProcessor(tokenizer=lowercase__   ,		image_processor=lowercase__       )

											snake_case_					:		Any 					=					"""test"""

											snake_case_					:		str 					=					processor(text=lowercase__       )

											snake_case_					:		Optional[Any] 					=					tokenizer(lowercase__       )
											for key in encoded_tok.keys():
																self.assertListEqual(encoded_tok[key]   ,		encoded_processor[key]       )







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		List[str] 					=					self.get_image_processor()
											snake_case_					:		Dict 					=					self.get_tokenizer()

											snake_case_					:		List[Any] 					=					MgpstrProcessor(tokenizer=lowercase__   ,		image_processor=lowercase__       )

											snake_case_					:		Union[str, Any] 					=					"""test"""
											snake_case_					:		Union[str, Any] 					=					self.prepare_image_inputs()

											snake_case_					:		Tuple 					=					processor(text=lowercase__   ,		images=lowercase__       )

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

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







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Optional[Any] 					=					self.get_image_processor()
											snake_case_					:		Union[str, Any] 					=					self.get_tokenizer()

											snake_case_					:		Union[str, Any] 					=					MgpstrProcessor(tokenizer=lowercase__   ,		image_processor=lowercase__       )

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

											snake_case_					:		str 					=					processor.char_decode(lowercase__       )
											snake_case_					:		List[str] 					=					tokenizer.batch_decode(lowercase__       )
											snake_case_					:		Optional[Any] 					=					[seq.replace(""" """   ,		""""""       ) for seq in decoded_tok]

											self.assertListEqual(lowercase__   ,		lowercase__       )







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		Optional[Any] 					=					self.get_image_processor()
											snake_case_					:		List[Any] 					=					self.get_tokenizer()

											snake_case_					:		str 					=					MgpstrProcessor(tokenizer=lowercase__   ,		image_processor=lowercase__       )

											snake_case_					:		List[str] 					=					None
											snake_case_					:		Optional[int] 					=					self.prepare_image_inputs()

											snake_case_					:		Optional[Any] 					=					processor(text=lowercase__   ,		images=lowercase__       )

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







						def 						__UpperCamelCase							(self       ):
											snake_case_					:		List[Any] 					=					self.get_image_processor()
											snake_case_					:		List[str] 					=					self.get_tokenizer()

											snake_case_					:		Tuple 					=					MgpstrProcessor(tokenizer=lowercase__   ,		image_processor=lowercase__       )

											snake_case_					:		Union[str, Any] 					=					torch.randn(1   ,		27   ,		38       )
											snake_case_					:		Tuple 					=					torch.randn(1   ,		27   ,		5_02_57       )
											snake_case_					:		str 					=					torch.randn(1   ,		27   ,		3_05_22       )

											snake_case_					:		Tuple 					=					processor.batch_decode([char_input, bpe_input, wp_input]       )

											self.assertListEqual(list(results.keys()       )   ,		["""generated_text""", """scores""", """char_preds""", """bpe_preds""", """wp_preds"""]       )









"""simple docstring"""

import random







def 							SCREAMING_SNAKE_CASE__      (		SCREAMING_SNAKE_CASE__ :  int			):



					"""simple docstring"""





					snake_case_					:		Union[str, Any] 					=					num - 1
					snake_case_					:		List[str] 					=					0

					while s % 2 == 0:
										snake_case_					:		str 					=					s // 2
										t += 1

					for _ in range(5			):
										snake_case_					:		List[Any] 					=					random.randrange(2				,    num - 1			)
										snake_case_					:		Dict 					=					pow(SCREAMING_SNAKE_CASE__				,    SCREAMING_SNAKE_CASE__				,    SCREAMING_SNAKE_CASE__			)
										if v != 1:
															snake_case_					:		int 					=					0
															while v != (num - 1):
																				if i == t - 1:
																									return False
																				else:
																									snake_case_					:		str 					=					i + 1
																									snake_case_					:		int 					=					(v**2) % num
					return True







def 							SCREAMING_SNAKE_CASE__      (		SCREAMING_SNAKE_CASE__ :  int			):



					"""simple docstring"""





					if num < 2:
										return False

					snake_case_					:		Dict 					=					[
					    2,
					    3,
					    5,
					    7,
					    1_1,
					    1_3,
					    1_7,
					    1_9,
					    2_3,
					    2_9,
					    3_1,
					    3_7,
					    4_1,
					    4_3,
					    4_7,
					    5_3,
					    5_9,
					    6_1,
					    6_7,
					    7_1,
					    7_3,
					    7_9,
					    8_3,
					    8_9,
					    9_7,
					    1_0_1,
					    1_0_3,
					    1_0_7,
					    1_0_9,
					    1_1_3,
					    1_2_7,
					    1_3_1,
					    1_3_7,
					    1_3_9,
					    1_4_9,
					    1_5_1,
					    1_5_7,
					    1_6_3,
					    1_6_7,
					    1_7_3,
					    1_7_9,
					    1_8_1,
					    1_9_1,
					    1_9_3,
					    1_9_7,
					    1_9_9,
					    2_1_1,
					    2_2_3,
					    2_2_7,
					    2_2_9,
					    2_3_3,
					    2_3_9,
					    2_4_1,
					    2_5_1,
					    2_5_7,
					    2_6_3,
					    2_6_9,
					    2_7_1,
					    2_7_7,
					    2_8_1,
					    2_8_3,
					    2_9_3,
					    3_0_7,
					    3_1_1,
					    3_1_3,
					    3_1_7,
					    3_3_1,
					    3_3_7,
					    3_4_7,
					    3_4_9,
					    3_5_3,
					    3_5_9,
					    3_6_7,
					    3_7_3,
					    3_7_9,
					    3_8_3,
					    3_8_9,
					    3_9_7,
					    4_0_1,
					    4_0_9,
					    4_1_9,
					    4_2_1,
					    4_3_1,
					    4_3_3,
					    4_3_9,
					    4_4_3,
					    4_4_9,
					    4_5_7,
					    4_6_1,
					    4_6_3,
					    4_6_7,
					    4_7_9,
					    4_8_7,
					    4_9_1,
					    4_9_9,
					    5_0_3,
					    5_0_9,
					    5_2_1,
					    5_2_3,
					    5_4_1,
					    5_4_7,
					    5_5_7,
					    5_6_3,
					    5_6_9,
					    5_7_1,
					    5_7_7,
					    5_8_7,
					    5_9_3,
					    5_9_9,
					    6_0_1,
					    6_0_7,
					    6_1_3,
					    6_1_7,
					    6_1_9,
					    6_3_1,
					    6_4_1,
					    6_4_3,
					    6_4_7,
					    6_5_3,
					    6_5_9,
					    6_6_1,
					    6_7_3,
					    6_7_7,
					    6_8_3,
					    6_9_1,
					    7_0_1,
					    7_0_9,
					    7_1_9,
					    7_2_7,
					    7_3_3,
					    7_3_9,
					    7_4_3,
					    7_5_1,
					    7_5_7,
					    7_6_1,
					    7_6_9,
					    7_7_3,
					    7_8_7,
					    7_9_7,
					    8_0_9,
					    8_1_1,
					    8_2_1,
					    8_2_3,
					    8_2_7,
					    8_2_9,
					    8_3_9,
					    8_5_3,
					    8_5_7,
					    8_5_9,
					    8_6_3,
					    8_7_7,
					    8_8_1,
					    8_8_3,
					    8_8_7,
					    9_0_7,
					    9_1_1,
					    9_1_9,
					    9_2_9,
					    9_3_7,
					    9_4_1,
					    9_4_7,
					    9_5_3,
					    9_6_7,
					    9_7_1,
					    9_7_7,
					    9_8_3,
					    9_9_1,
					    9_9_7,
					]

					if num in low_primes:
										return True

					for prime in low_primes:
										if (num % prime) == 0:
															return False

					return rabin_miller(SCREAMING_SNAKE_CASE__			)







def 							SCREAMING_SNAKE_CASE__      (		SCREAMING_SNAKE_CASE__ :  int = 1_0_2_4			):



					"""simple docstring"""





					while True:
										snake_case_					:		Tuple 					=					random.randrange(2 ** (keysize - 1)				,    2 ** (keysize)			)
										if is_prime_low_num(SCREAMING_SNAKE_CASE__			):
															return num


if __name__ == "__main__":
			a_			   =					generate_large_prime()
			print(('''Prime number:''', num))
			print(('''is_prime_low_num:''', is_prime_low_num(num)))




